method for selecting one or more human embryos that are likely to reach the blastocyst stage

专利摘要:
IMAGE AND EVALUATION OF EMBRYOS, OOCYTES AND STEM CELLS Methods, compositions and kits are provided to determine the development potential of one or more embryos or pluripotent cells and / or the presence of chromosomal abnormalities in one or more embryos or pluripotent cells. These methods, compositions and kits find use in the identification of embryos and oocytes in vitro that are useful in the treatment of infertility in humans.
公开号:BR112012003847B1
申请号:R112012003847-8
申请日:2010-08-23
公开日:2020-12-01
发明作者:Connie C. Wong；Kevin E. Loewke；Thomas M. Baer；Renee A. Reijo-Pera；Barry Behr
申请人:The Board Of Trustees Of The Leland Standford Junior University；
IPC主号:

专利说明:

CROSS REFERENCE TO RELATED REQUESTS
[0001] This application claims priority for Provisional Patent Application US 61 / 332,651, filed on May 7, 2010 and Provisional Patent Application US 61 / 236,085, filed on August 22, 2009, both of which are incorporated by reference in their totalities. FIELD OF THE INVENTION
[0002] This invention refers to the field of biological and clinical tests, and particularly, imaging and evaluation of zygotes / embryos, oocytes and stem cells of both humans and animals. BACKGROUND OF THE INVENTION
[0003] Infertility is a common health problem that affects 10 to 15% of couples of childbearing age. In the United States alone in 2006, approximately 140,000 in vitro fertilization (IVF) cycles were performed (cdc.gov/art). This has resulted in the culture of more than a million embryos annually with the potential for implantation and development at variable and generally poorly defined terms. The rate of live births per cycle after IVF was only 29%, while an average of 30% of live births resulted in multiple pregnancies (cdc.gov/art). Multiple pregnancies have well-documented adverse outcomes for mothers and fetuses such as miscarriage, preterm birth and low birth rate. The potential causes of IVF failure are diverse; however, since the introduction of IVF in 1978, one of the main challenges has been to identify the embryos that are most appropriate and most likely to result in full-term pregnancies.
[0004] Understanding in basic embryo development technique is limited since studies in human embryonic biology remain challenging and generally exempt from research funding. Consequently, most of the current knowledge of embryonic development derives from studies of model organisms. However, while embryos of different species go through similar stages of development, the time varies by species. These differences, and many others, can make it inappropriate to directly extrapolate from one species to another. (Taft, R.E. (2008) Theriogenology 69 (1): 10-16). The general pathways of human development, as well as the underlying fundamental molecular determinants, are unique to human embryonic development. For example, in mice, embryonic transcription is activated approximately 12 hours after fertilization, concurrent with the first cleavage of division, while in humans the activation of the embryonic gene (EGA) occurs on day 3, close to the stage of 8 cells (Bell , CE, et al. (2008) Mol. Hum. Reprod. 14: 691-701; Braude, P., et al. (1988) Nature 332: 459-461; Hamatani, T. et al. (2004) Proc Natl. Acad. Sci. 101: 10326-10331; Dobson, T. et al. (2004) Human Molecular Genetics 13 (14): 1461-1470). In addition, the genes that are modulated in early human development are unique (Dobson, T. et al. (2004) Human Molecular Genetics 13 (14): 1461-1470). In addition, in other species such as mice, more than 85% of cultured embryos reach the blastocyst stage, one of the main milestones in mammalian development, while cultured embryos have a blastocyst formation average of approximately 30 to 50%, with a high incidence of mosaicism and anomalous phenotypes, as an impediment fragmentation and development (Rienzi, L. et al. (2005) Reprod. Biomed. Online 10: 669-681; Alikani, M., et al. (2005) Mol. Hum. Reprod. 11: 335-344; Keltz , MD, et al. (2006) Fertil. Steril. 86: 321-324; French, DB, et al. (2009) Fertil. Steril.). Despite these differences, most embryo development studies pre- implantation originate from model organisms and are difficult to relate to the development of human embryos (Zernicka-Goetz, M. (2002) Development 129: 815-829; Wang, Q., et al. (2004) Dev Cell. 6: 133-144; Bell, C. E., et al. (2008) Mol. Hum. Reprod. 14: 691701; Zernicka-Goetz, M. (2006) Curr. Opin. Genet. Dev. 16: 406-412; Mtango, N. R., et al. (2008) Int. Rev. Cell. Mol. Biol. 268: 223-290).
[0005] Traditionally in IVF clinics, the viability of human embryos has been assessed by simple morphological observations such as the presence of mononucleated blastomeres of uniform size and the degree of cell fragmentation (Rijinders PM, Jansen CAM. (1998) Hum Reprod 13: 2869-73; Milki AA, et al. (2002) Fertil Steril 77: 1191-5). More recently, additional methods such as extended embryo culture (for the blastocyst stage on day 5) and chromosomal status analysis through pre-implantation diagnosis (PGD) have also been used to assess embryo quality (Milki A, et al (2000) Fertil Steril 73: 126-9; Fragouli E, (2009) Fertil Steril Jun 21 [EPub ahead of print]; El-Toukhy T, et al. (2009) Hum Reprod 6:20; Vanneste E, et (2009) Nat Med 15: 577-83). However, the potential risks of these methods also exist because they prolong the culture period and interrupt embryonic integrity (Manipalviratn S, et al. (2009) Fertil Steril 91: 305-15; Mastenbroek S, et al. (2007) N Engl J Med. 357: 9-17).
[0006] It has recently been demonstrated that time-lapse imaging can be a useful tool for observing early embryonic development. Some methods used time-lapse imaging to monitor the development of human embryos after intracytoplasmic sperm injection (ICSI) (Nagy et al. (1994) Human Reproduction. 9 (9): 1743-1748; Payne et al. (1997 ) Human Reproduction, 12: 532- 541). Polar body extrusion and pro-nuclear formation were analyzed and correlated with good morphology on day 3. However, no parameters were correlated with blastocyst formation in pregnancy outcomes. Other methods observed at the beginning of the first cleavage as an indicator to predict the viability of human embryos (Fenwick, et al. (2002) Human Reproduction, 17: 407-412; Lundin, et al. (2001) Human Reproduction 16: 2652- 2657). However, these methods do not recognize the importance of the duration of cytokinesis in intervals between early divisions.
[0007] Other methods used time-lapse imaging to measure the time and extent of cell divisions during early embryo development (WO / 2007/144001). However, these methods reveal only a basic and general method for time-lapse imaging of bovine embryos, which are substantially different from human embryos in terms of development potential, morphological behavior, molecular and epigenetic programs, and time and parameters around that surround the transfer. For example, bovine embryos take substantially more time to implant compared to human embryos (30 days and 9 days, respectively). (Taft, (2008) Theriogenology 69 (1): 10-16. In addition, no specific imaging parameters or time intervals are revealed that can predict the viability of human embryos.
[0008] More recently, time-lapse imaging has been used to observe the development of human embryos during the first 24 hours after fertilization (Lemmen et al. (2008) Reproductive BioMedicine Online 17 (3): 385- 391) . The synchrony of the nuclei after the first division proved to be correlated with the results of the pregnancies. However, this work concluded that the first early cleavage was not an important predictive parameter, which contradicts previous studies (Fenwick, et al. (2002) Human Reproduction 17: 407-412; Lundin, et al. (2001) Human Reproduction 16: 2652-2657).
[0009] Finally, no study has validated imaging parameters through correlation with the embryo's molecular programs or chromosomal composition. The methods for assessing human embryo are, therefore, deficient in several aspects and can be improved by the present methods, which involves new applications of time-lapse microscopy, image analysis, and correlation of imaging parameters with molecular profiles and chromosomal composition. The present invention addresses these issues. SUMMARY OF THE INVENTION
[0010] Methods, compositions and kits for determining the development potential of one or more embryos or pluripotent cells in one or more embryos or pluripotent cells are provided. These methods, compositions and kits find use in the identification of embryos and oocytes in vitro that have a good potential for development, that is, the ability to develop in a blastocyst, which are, therefore, useful in methods of treating infertility in human beings. human kits and the like.
[0011] In some aspects of the invention, methods are provided to determine the development potential of an embryo or a pluripotent cell. In such aspects, one or more cellular parameters of an embryo or pluripotent cell are measured to arrive at a cell parameter measurement. The cell parameter is then employed to provide a determination of the potential of the embryo or pluripotent cell, the determination of which can be used to guide a clinical course of action. In some embodiments, the cell parameter is a morphological event that is measurable by time-lapse microscopy. In some embodiments, for example, when an embryo is evaluated, the one or more cellular parameters are: duration of a cytokinesis event, for example, cytokinesis 1; time interval between cytokinesis 1 and cytokinesis 2; and time interval between cytokinesis 2 and cytokinesis 3. In certain embodiments, the duration of the cell cycle is also used as a cell parameter. In some embodiments, cell parameter measurement is employed by comparing it to a comparable cell parameter measurement of a referral embryo, and using the result of this comparison to provide a determination of the embryo's potential development potential. In some embodiments, the embryo is a human embryo. In some embodiments, the cell parameter is a gene expression level that is measured to arrive at a measure of gene expression. In some embodiments, the measure of gene expression is used by comparing it to a measure of gene expression of a pluripotent cell or reference embryo or one or more of these cells, where the result of this comparison is used to provide a determination of each development potential of the pluripotent cell or embryo. In some embodiments, the embryo is a human embryo.
[0012] In some aspects of the invention, methods are provided to classify pluripotent embryos or cells for their development potentials in relation to other pluripotent embryos or cells in the group. In said modalities, one or more cell parameters of the embryos or pluripotent cells in the group are measured to arrive at a cell parameter measurement for each of the embryos or pluripotent cells. Cell parameter measurements are then employed to determine the development potential of each of the embryos or pluripotent cells in the group relative to the other, the determination of which can be used to guide a clinical course of action. In some embodiments, the cell parameter is a morphological event that is measurable by time-lapse microscopy. In some modalities, for example, when embryos are classified, the one or more cell parameters are the duration of a cytokinesis event, for example, cytokinesis 1; time interval between cytokinesis 1 and cytokinesis 2; and time interval between cytokinesis 2 and cytokinesis 3. In certain embodiments, the duration of cell cycle 1 is also measured. In some embodiments, the cell parameter is the expression level of one or more genes. In some embodiments, one or more cell parameter measurements are employed by comparing cell parameter measurements from each of the embryos or pluripotent cells in the group to another to determine the potential for developing embryos or pluripotent cells in relation to another. In some embodiments, one or more cell parameter measurements are used by comparing each cell parameter measurement to a cell parameter measurement of an embryo or reference multipotent cell to determine the development potential for each embryo or cell pluripotent, and buy the development potentials to determine the development potential of embryos or pluripotent cells in relation to another.
[0013] In some aspects of the invention, methods are provided to provide embryos with good developmental potential for transfer to a woman for assisted reproduction (IVF). In said respects, one or more embryos are grown under conditions sufficient for embryo development. One or more cell parameters are then measured in one or more embryos to arrive at a cell parameter measurement. Measurement of the cell parameter is then employed to provide a determination of the development potential of one or more embryos. The one or more embryos that demonstrate good development potential are then transferred to a woman. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The invention is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various characteristics of the drawings are not staggered. On the contrary, the dimensions of the various characteristics are arbitrarily expanded or reduced for clarity. Included in the drawings are the following figures.
[0015] Figure 1 is a flow chart showing the processes used to evaluate embryos.
[0016] Figure 2 is a series of photographs showing cell cleavage and division over the period of 6 days. The images are marked from day 1 to day 6. The bars in scale represent 50 gm.
[0017] Figure 3 is a bar graph showing percentages of successful development in blastocysts of embryos of 1 cell (zygotes). Through the course of 4 separate experiments, a total of 100 embryos were observed up to Daia 5 to 6 through time-lapse microscopy. The percentage of cells that reach each indicated stage (blastocyst, 8 cells, 4 to 7 cells, 2 to 3 cells and 1 cell) is shown.
[0018] Figure 4 is a series of three different embryos being developed for the indicated times (upper, middle and lower lines).
[0019] Figure 5 is a diagram showing the time lapses between the stages used for current assessments, including the duration of the first cytokinesis, time between the first and the second division (measured as the time interval between the resolution of the cytokinesis 1 and the start of cytokinesis 2), and time between the 2nd and 3rd mitosis (measured as the time interval between the start of cytokinesis 2 and the start of cytokinesis 3).
[0020] Figure 6 is a 3-D dot plot showing the measurement of three events, including the duration of the first cytokinesis, the time interval between the first and second cell divisions (measured as the time interval between resolution cytokinesis 1 and the beginning of cytokinesis 2), and the time interval between the second and third cell divisions (measured as the time interval between the start of cytokinesis 2 and the start of cytokinesis 3), for a large group of embryos . Embryos that reach the blastocyst stage (marked with circles) are shown by joining on the 3-D chart, while the embryos that hold (marked with X) before reaching the blastocyst are spread across the chart.
[0021] Figure 7 is a graph showing a characteristic operating curve of the receiver (ROC) to predict blastocyst formation using the 3 dynamic morphological parameters.
[0022] Figure 8 is a radar graph of expression levels of 52 genes from 6 embryos trapped from 1 to 2 cells and 5 normal embryos from 1 to 2 cells. The difference in expression levels between normal and abnormal embryos was statistically significant for those genes highlighted in yellow and denoted with an asterisk, as determined by the Mann-Whitney test.
[0023] Figure 9 is a bar graph showing the expression levels of different genes in 2 cell embryos and normal 2 cell embryos. A selected number of time-lapse images for the embryos of 2 stuck cells are shown at the top.
[0024] Figure 10 is a bar graph showing the same genes shown in Fig. 9, in an embryo trapped in 4 cells and normal embryos in 4 cells. A selected number of time-lapse images for the embryos of 4 stuck cells are shown at the top.
[0025] Figure 11 is a series of bar graphs showing patterns of gene expression (ESSP) containing 4 distinct patterns. The times of early transfer before activation of the embryonic gene (day 2) and typical expression on day 3 are indicated.
[0026] Figure 12 shows gene expression of simple blastomer genes at different stages. (A) Gene expression of two genes, CTNNB1 and CDX2 from simple blastomeres plotted in different cell stages and shows the changes in these gene expression levels in different stages, for example, 2 cells, 3 cells, morula and blastocyst. (B) Gene expression signatures in bars representing the genes expressed in the maternal program as compared to the genes expressed in the zygotic program.
[0027] Figure 13 is a drawing of a model for use in time-lapse image analysis and correlated molecular analysis to assess embryo viability.
[0028] Figure 14 is a series of photographs showing three stages of development during in vitro oocyte maturation.
[0029] Figure 15 is a series of photographs showing the process of embryo development after in vitro maturation of the oocyte.
[0030] Figure 16 is a flow chart showing processes used to evaluate oocytes.
[0031] Figure 17 is a flowchart showing processes used to evaluate stem cells and pluripotent stem cells.
[0032] Figure 18 is a series of photographs showing the process of induced pluripotent stem cells that differ in neuron rosettes.
[0033] Figure 19 is a table of categories in which the genes evaluated for the level of expression can be categorized, including the number of genes per category. Figure 20 is a table of the four Embryonic Stage Spherical Patterns (ESSPs) that were identified during the analysis of gene expression of 141 simple embryos and simple blastomeres normally developed, and the categorization of genes in each of these categories.
[0034] Figure 21 shows the automated image analysis demonstrating the ability of imaging parameters to predict blastocyst formation. (A) Shows the results of the tracking algorithm for a single embryo. (B) Shows a set of 14 embryos that were analyzed. (C) Shows the comparison of manual image analysis for automated analysis for the duration of cytokinesis. (D) Shows the comparison of manual image analysis to automated analysis for the time between first and second mitoses. (E) Shows the comparison of good blastocyst morphology to bad blastocyst morphology.
[0035] Figure 22 is a schematic drawing of a darkfield microscope according to the present invention; the insertion on the left shows a dark laser-machined fragment adjustment field.
[0036] Figure 23 is a photograph of an arrangement of three microscopes as illustrated in Fig. 22, mounted on a support for installation in an incubator and for computer connections. Fig. 23A shows the microscopes, and Fig.23B shows the microscopes inside an incubator.
[0037] Figure 24 is an image capture software screen used in the present work, which shows embryos being reflected from 3 channels.
[0038] Figure 25 A to D is a series of four photographs showing selected time-lapse image of experiment 2, stage 2. Figs. 25A and 25B are images captured before changing media, and Figs. 25C and 25D are images captured after changing media.
[0039] Figure 26 A to D is a series of four photographs showing a selected time-lapse image of experiment 1, stage 2. Figs. 26A and 26B are images captured before changing media, and Figs. 26C and 26D are images captured after changing media.
[0040] Figures 27 A and B are drawings of a personalized petri dish in micropogues. Fig. 27A shows a drawing of the plate with dimensions, and Fig. 27B shows a 3D view of the micropogues.
[0041] Figures 28 A and B are graphs showing cell activity with and without previous image registration. Figs. 28A and 28B together show that the record clears the result and removes spikes due to the change or rotation of the embryo.
[0042] Figures 29 A and B show graphs (left) and cell photos (right) showing the cell activity of normal and abnormal embryos. Together, Fig. 29A and Fig. 29B show that, on day 3, the embryos have similar morphology, but their plots of cellular activities are drastically different and only one of them develops in a blastocyst.
[0043] Figure 30 is a graph showing the difference in pixel intensities between successive pairs of images during the development of the embryo. This can be used alone to assess embryo viability, or as a way to improve other algorithms, such as a particle filter, when determining how many particles (to predict embryo models) should be used.
[0044] Figure 31 A-G is a series of seven photographs showing the results of 2D tracking in various cell stages. Cell progress, as indicated by the numbers in the chart associated with each pair of figures: Chart 15 (Fig. 31A), 45 (B), 48 (C), 189 (D), 190 (E), 196 (F) and 234 (G). The bottom line shows the simulated images superimposed. The outlines are visible cell membranes, and the white dotted lines are occluded membranes. The picture frames are captured every 5 minutes, and only a few are displayed.
[0045] Figures 32 A and B are a series of photographs and drawings showing two successful cases of 3D cell tracking. The illustrations under each photo of an embryo show the top-down view of the 3D model, except for frame 314 and frame 228, which show side views of the models in frame 314 and frame 228, respectively. The picture frames were captured every 5 minutes.
[0046] Figure 33 is a diagrammatic representation of a particle filter for dividing 1 cell to 2 cells. The data points are the 3D locations of the cell centers. The points are shown for 1 cell models, 2 cell models, 3 cell models, and 4 cell models. The top line shows the particles after the forecast, and the bottom line shows the particles after resampling.
[0047] Figures 34 A and B are graphs showing an automated vs. image analysis comparison. manual of a set of embryos. Fig. 34A shows the comparison for the duration of the first cytokinesis, and Fig. 34B shows the comparison for the time between 1st and 2nd mitosis.
[0048] Figure 35 is a flowchart showing how image analysis is used for model embryos and measuring certain morphological parameters. DETAILED DESCRIPTION OF THE INVENTION
[0049] Before the present methods and compositions are described, it should be understood that this invention is not limited to the particular method or composition described, as these can, of course, vary. It should also be understood that the terminology used here is for the purpose of describing particular modalities only and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.
[0050] When a range of values is provided, it should be understood that each integer value of the range, to the tenth of the unit of the lower limits unless the context clearly indicates, between the upper and lower limits of the range and also specifically revealed. Each minor range between any declared value or intermediate value in an established range and any other declared or intermediate value in that declared range is included within the invention. The upper and lower limits of these smaller ranges can independently be included or excluded in the range, and each value where one, none or both of the limits are included in the smaller ranges is also included within the invention, subject to any limit specifically excluded in the declared value. . Where the declared range includes one or both of the limits, the bands excluding one or both of those limits included in the invention are also included in the invention.
[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs. Although any method and material similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All of the aforementioned publications are incorporated here as a reference for revealing and describing the methods and / or materials in relation to which the publications are cited. It should be understood that the present disclosure supersedes any disclosure in a publication incorporated into the extent to which there is a contradiction.
[0052] It should be noted that as used here and in the appended claims, the singular forms "one", "one", and "o / a" include plural referents unless the context clearly defines otherwise. Thus, for example, the reference to "a cell" includes a plurality of said cells and the reference to "the peptide" includes reference to one or more peptides and equivalents thereof, for example, polypeptides, known to those skilled in the art and so onwards.
[0053] The publications discussed here are provided solely for your disclosures prior to the filing date of this application. Nothing herein should be construed as an admission that the present invention is not entitled to anticipate said publication by virtue of a previous invention. In addition, publication dates may differ from actual publication dates which may need to be independently confirmed. DEFINITIONS
[0054] Methods, compositions and kits to determine the development potential of one or more embryos or pluripotent cells and / or the presence of chromosomal abnormalities in one or more embryos or pluripotent cells are provided. These methods, compositions and kits find use in the identification of embryos and oocytes in vitro that are most useful in the treatment of infertility in humans. These and other objects, advantages, and features of the invention will become apparent to those skilled in the art when they read the details of the methods and object compositions as described in more detail below.
[0055] The terms "development potential" and "development competence" are used here to refer to the ability or ability of a healthy embryo or pluripotent cell to grow or develop.
[0056] The term "embryo" is used to refer to both the zygote that is formed when two diploid gamete cells, for example, an unfertilized secondary oocyte and a sperm cell, come together to form a diploid totipotent cell, for example, a fertilized egg, and the embryo that results from the immediately subsequent cell divisions, that is, embryonic cleavage, up to the morula, that is, the 16-cell stage and the blastocyst stage (such as differentiated trophoectoderma and internal cell mass).
[0057] The term “pluripotent cell” is used here to mean any cell that has the ability to differentiate into multiple types of cells in an organism. Examples of pluripotent cells include stem cells, oocytes, and 1-cell embryos (i.e., zygotes).
[0058] The term “stem cell” is used here to refer to a cell or population of cells that: (a) has the capacity to self-renew, and (b) has the potential to generate several cell types differentiated. Often, a stem cell has the potential to generate multiple cell lines. As used here, a stem cell can be a totipotent stem cell, for example, a fertilized oocyte, which originates all the embryonic and extraembryonic tissues of an organism; a pluripotent stem cell, for example, an embryonic stem cell (ES), embryonic germ cell (EG), or an induced pluripotent stem cell (iPS), which generates all the embryonic tissues of an organism, that is, endoderm lines, mesoderm, and ectoderm; a multipotent stem cell, for example, a mesenchymal stem cell, which generates at least two of the embryonic tissues of an organism, that is, at least two lineages of endoderm, mesoderm and ectoderm, or this can be a tissue-specific stem cell , which generates multiple types of cells differentiated from a particular tissue. Tissue-specific stem cells include spherical embryonic cells of tissue, which generate the cells of a particular tissue, and somatic stem cells, which reside in adult tissues and can originate the cells of that tissue, for example, neuronal stem cells, which generate all central nervous system cells, satellite cells, which generate skeletal muscle, and hematopoietic stem cells, which generate all cells of the hematopoietic system.
[0059] The term "oocyte" is used here to refer to an unfertilized female cell, or agameta. Oocytes of the object application may be primary oocytes, in which case they may be positioned to pass or be passing through meiosis I, or secondary oocytes, in which case they are positioned to pass or be passing through meiosis II.
[0060] By "meiosis" is meant the cell cycle events that result in the production of gametes. In the first meiotic cell cycle, or meiosis I, the cell's chromosomes are duplicated and shared in two daughter cells. These daughter cells then divide into a second meiotic cell cycle, or meiosis II, which is not accompanied by DNA synthesis, resulting in gametes with a haploid number of chromosomes.
[0061] By "germ vesicle" stage is understood the stage of a maturation of primary oocyte that correlates with the prophase I of the meiosis I cell cycle, or before the first division of nuclear material. Oocytes in this stage are also called "germ vesicle oocytes", for the characteristically large nucleus, called the germ vesicle. In a normal human oocyte cultured in vitro, the germinal vesicle occurs about 6 to 24 hours after the start of maturation.
[0062] By the stage of "metaphase I" is understood the stage of a maturation of primary oocyte that is correlated with metaphase I of the cell cycle of meiosis I. In comparison to germ vesicle oocytes, the metaphase oocytes do not have a large core clearly defined. In a normal human oocyte cultured in vitro, metaphase I occurs about 12 to 36 hours after the start of maturation.
[0063] By "metaphase II" stage is meant the stage of a secondary oocyte maturation that correlates with metaphase II of the meiosis II cell cycle. Metaphase II is distinguishable by the extrusion of the first polar body. In a normal human oocyte cultured in vitro, metaphase II occurs about 24 to 48 hours after the start of maturation.
[0064] By a "mitotic cell cycle", it is understood the events in a cell that result in the duplication of chromosomes in a cell and the division of these chromosomes and a cytoplasmic material in two daughter cells. The mitotic cell cycle is divided into two phases: Interphase and mitosis. At the interphase, the cell grows and replicates its DNA. In mitosis, the cell initiates and completes cell division, first by partitioning its nuclear material, and then dividing its cytoplasmic material and its partitioned nuclear material (cytokinesis) into two separate cells.
[0065] By a "first mitotic cell cycle" or "cell cycle 1" is understood the time interval between fertilization until the conclusion of the cytokinesis event, that is, the division of the fertilized oocyte into two daughter cells. In cases where oocytes are fertilized in vitro, the time interval between the injection of human chorionic gonatropine (HCG) (usually administered before oocyte recovery) until the completion of the first cytokinesis event can be used as a substitute time interval .
[0066] By a "second mitotic cell cycle" or "cell cycle 2" is meant the second cell cycle event observed in an embryo, the time interval between the production of the daughter cells of an oocyte fertilized by mitosis and the production of a first set of grand cells of one of the daughter cells (the “daughter cell Hder”, or daughter cell A) by mitosis. At the conclusion of cell cycle 2, the embryo consists of 3 cells. In other words, cell cycle 2 can be visually identified as the time between the embryo containing 2 cells and the embryo containing 3 cells.
[0067] By a "third cell cycle" or "cell cycle 3" is understood the event of the third cell cycle observed in an embryo, typically the time interval for the production of daughter cells of an oocyte fertilized by mitosis and the production of a second set of net cells of the second daughter cell (the “backward daughter cell” or daughter cell B) by mitosis. At the conclusion of cell cycle 3, the embryo consists of 4 cells. In other words, cell cycle 3 can be visually identified as the time between the embryo containing 3 cells and the embryo containing 4 cells.
[0068] By "first cleavage event", we mean the first division, that is, the division of the oocyte into two daughter cells, that is, cell cycle 1. At the conclusion of the first cleavage event, the embryo consists of 2 cells.
[0069] By "second cleavage event", we mean the second set of divisions, that is, the division of the Hder daughter cell into two net cells and the division of the delayed daughter cell into two net cells. In other words, the second cleavage event consists of both cell cycle 2 and cell cycle 3. Upon completion of the second cleavage, the embryo consists of 4 cells.
[0070] "Third cleavage event" means the third set of divisions, that is, the divisions of the net cells. Upon completion of the third cleavage event, the embryo typically consists of 8 cells.
[0071] By "cytokinesis" or "cell division" is meant that the phase of mitosis in which a cell undergoes cell division. In other words, it is the stage of mitosis in which a cell-partitioned nuclear material and its cytoplasmic material are divided to produce two daughter cells. The period of cytokinesis is identifiable as the period, or window, of time between when a cell membrane constriction (a “cleavage groove”) is first observed and the resolution of that building event, that is, the generation of two daughter cells. The beginning of the cleavage groove can be visually identified as the point at which the curvature of the cell membrane changes from convex (rounded out) to concave (curved inward with a tooth or notched). This is illustrated in Fig.4 top panel by white arrows pointing to 2 cleavage grooves. The beginning of cell elongation can also be used to mark the beginning of cytokinesis, in which the period of cytokinesis is defined as the period of time between the beginning of cell elongation and the resolution of cell division.
[0072] By "first cytokinesis" or "cytokinesis 1" it is understood that the first cell division event after fertilization, that is, the division of a fertilized oocyte to produce two daughter cells. The first cytokinesis usually occurs about a day after fertilization.
[0073] By "second cytokinesis" or "cytokinesis 2", we understand the second cell division event observed in an embryo, that is, the division of a cell daughter of the fertilized oocyte (the "daughter cell rider", or daughter A) in a first set of two granddaughters.
[0074] By "third cytokinesis" or "cytokinesis 3", we mean the third cell division event observed in an embryo, that is, the division of other daughter cells of the fertilized oocyte (the "delayed daughter cell", or daughter B) in a second set of two granddaughters.
[0075] The term "fiduciary marker" or "fiducial marker," is an object in the field of view of an imaging system that appears in the image produced, for use as a reference point or a measurement. This can be something placed on the object being imaged, or a mark or set of marks on the lattice of an optical instrument.
[0076] The term "micropogo" refers to a container that is sized on a cell scale, preferably to provide accommodation for a simple eukaryotic cell. Pluripotent cells and embryos of interest
[0077] In the methods of the invention, one or more embryos or pluripotent cells are evaluated for their development potential by measuring one or more cell parameters of the embryos or pluripotent cells and applying these measurements to determine the development potential of the embryos or cells pluripotent. The information thus derived can be used to guide clinical decisions, for example, whether or not to transfer in vitro fertilized embryo, whether or not to transplant cell or cultured cells.
[0078] Examples of embryos that can be evaluated by the methods of the invention include 1-cell embryos (also called zygotes), 2-cell embryos, 3-cell embryos, 4-cell embryos, 5-cell embryos, 6-cell embryos , 8 cell embryos, etc. typically up to and including 6 cell embryos, any of which can be derived by any convenient method, for example, from an oocyte that has matured in vivo or from an oocyte that has matured in vitro.
[0079] Examples of pluripotent cells that can be evaluated by the methods of the invention include totipotent stem cells, for example, oocytes, such as primary oocytes and secondary oocytes; pluripotent stem cells, for example, ES cells, EG cells, iPS cells, and the like; multipotent cells, for example, mesenchymal stem cells; and spherical tissue stem cells. They can be from any stage of life, for example, embryonic, neonatal, juvenile or adult, and of any sex, that is, XX or XY.
[0080] Embryos and pluripotent cells can be derived from any organism, for example, any mammalian species, for example, human, primate, equine, bovine, porcine, canine, feline, etc. Preferably, they are derived from a human. Previously, for example, embryos cryopreserved in a 1 cell stage can be frozen and then thawed, or frozen and thawed oocytes and stem cells. Alternatively, embryos that are newly prepared from oocytes by in vitro fertilization techniques can be freshly prepared; oocytes that are recently harvested and / or recently ripened through in vitro ripening techniques or others that are derived from pluripotent stem cells differentiated into germ cells in vitro and matured into oocytes; stem cells are freshly prepared from dissociation and tissue culture by methods known in the art; and the like. They can be grown under any convenient condition known in the art to promote survival, growth, and / or development of the sample to be evaluated, for example, for embryos, under conditions such as those used in the in vitro fertilization technique; see, for example, US Patent 6,610,543, US Patent 6,130,086, US Patent 5,837,543, the disclosures of which are incorporated herein by reference; for oocytes, under conditions such as those used in the technique to promote oocyte maturation; see, for example, US Patent 5,882,928 and US Patent 6,281.03, the disclosures of which are incorporated herein by reference; for stem cells under conditions like those used in the technique to promote proliferation; see, for example, US Patent 6,777,233, US Patent 7037892, US Patent 7,029,913, US Patent 5,843,780, and US Patent 6,200,806, US Application 2009/0047263; US Order 2009/0068742, the disclosures of which are incorporated herein by reference. Generally, embryos / pluripotent cells are grown in a commercially available medium such as KnockOut DMEM, DMEM-F12, or Iscoves Modified Dulbecco's Medium that has been supplemented with serum or serum substitute, amino acids, and growth factors adjusted for embryo needs / particular pluripotent cells being evaluated. Time Lapse Imaging Analysis
[0081] In some modalities, embryos / pluripotent cells are evaluated by measuring cellular parameters by time-lapse imaging. Pluripotent embryos / cells can be grown on standard culture plates. Alternatively, pluripotent embryos / cells can be grown on standard culture plates, for example, standard culture plates with micropogues of optical quality as described here. In said usual culture plates, each micropogo maintains a single embryo / pluripotent cell, and the bottom surface of each micropogo has an optical quality finish so that the entire group of embryos within a single plate can be reflected simultaneously by a single miniature microscopy with sufficient resolution to monitor the processes of mitosis. The complete group of micropogues shares the same medium drop on the culture plate, and may also include an outer wall positioned around micropogues to stabilize the medium drop, as well as fiducial markers placed next to the micropogues. The hydrophobicity of the surface can be adjusted with plasma etching or other treatment to prevent bubbles from forming in the micropogues when filled with medium. Regardless of whether the standard culture plate or a common culture plate is used, during culture, one or more developing embryos can be grown in the same culture medium, for example, between 1 and 30 embryos can be grown per plate.
[0082] The images are obtained over time, and are then analyzed to arrive at measurements of one or more cell parameters. Time-lapse imaging can be performed with any computer-controlled microscope that is equipped for storage and digital image analysis, for example, inverted microscopes equipped with heated stages and incubation chambers, or custom built miniature microscope arrangements that fit inside a conventional incubator. The arrangement of miniature microscopes allows simultaneous culture of multiple sample plates in the same incubator, and is scalable to accommodate multiple channels without limitations over the minimum time interval between capturing successive images. The use of multiple microscopes eliminates the need to move the sample, which improves the accuracy of the system and the overall confidence in the system. The individual microscopes in the incubator can be partially or completely isolated, providing each culture plate with its own controlled environment. This allows the plates to be transformed to and from the imaging stages without disturbing the environment of the other samples.
[0083] The imaging system for time-lapse imaging can employ bright field illumination, dark field illumination, phase contrast, Hoffman modulation contrast, differential interference contrast, or fluorescence. In some embodiments, darkfield illumination can be used to provide enhanced image contrast for subsequent feature extraction and image analysis. In addition, sources of red or near infrared light can be used to reduce phototoxicity and improve the proportion of contrast between cell membranes and the inner parts of cells.
[0084] The images that are acquired can be established on a continuous basis, or as a live video, or on an intermittent basis, as in time-lapse photography, where a subject is repeatedly imaged in a static image. Preferably, the time interval between images should be between 1 and 30 minutes to capture significant morphological events as described below. In an alternative embodiment, the time interval between images could be varied depending on the amount of cellular activity. For example, during active periods, images could be taken every few seconds or every minute, while during inactive periods they could be taken every 10 or 15 minutes or more. Real-time image analysis on captured images could be used to detect when and how time intervals vary. In our methods, the total amount of light received by the samples is stimulated as being equivalent to approximately 24 minutes of exposure to low-level light for 5 days of imaging. The light intensity for time-lapse imaging systems is significantly less than the light intensity typically used in an assisted reproduction microscope due to the low power of the LEDs (example, using a 1W LED compared to a typical 100W halogen bulb. ) and high sensitivity of the camera sensor. Thus, the total amount of light energy received by an embryo using the time-lapse imaging system is comparable to or less than the amount of energy received during routine manipulation at an IVF clinic. In addition, the exposure time can be significantly shortened to reduce the total amount of light exposure to the pluripotent embryo / cell. For 2-day imaging, with images captured every 5 minutes in 0.5 seconds of exposure to light per image, the total amount of light exposure is low and less than 5 minutes.
[0085] After obtaining images, the images are extracted and analyzed by different cell parameters, for example, cell size, thickness of the pellucid zone, degree of fragmentation, symmetry of the daughter cells resulting from a cell division, the time intervals among the first mitoses, and duration of cytokinesis.
[0086] Cellular parameters that can be measured by time-lapse imaging are generally morphological events. For example, when evaluating embryos, time-lapse imaging can be used to measure the duration of a cytokinesis event, for example, cytokinesis 1, cytokinesis 2, cytokinesis 3, or cytokinesis 4, where the duration of the cytokinesis event It is defined as the time interval between the first observation of a cleavage groove (the beginning of cytokinesis) and the resolution of the cleavage groove in two daughter cells (i.e., the production of two daughter cells). Another parameter of interest is the duration of a cell cycle event, for example, cell cycle 1, cell cycle 2, cell cycle 3 or cell cycle 4, where the duration of a cell cycle event is defined as the time interval between the production of a cell (for cell cycle 1, the fertilization of an egg; for subsequent cell cycles, in a resolution of cytokinesis) and the production of two daughter cells of that cell. Other cell parameters of interest that can be measured by time-lapse imaging include the time intervals that are defined by these cell events, for example, (a) the time interval between cytokinesis 1 and cytokinesis 2, defined as any the interval between the beginning of cytokinesis 1 and the beginning of cytokinesis 2, the interval between the resolution of cytokinesis 1 and the resolution of cytokinesis 2, the interval between the beginning of cytokinesis 1 and the resolution of cytokinesis 2; or the interval between the resolution of cytokinesis 1 and the start of cytokinesis 2; or (b) the time interval between cytokinesis 2 and cytokinesis 3, definable as any of the interval between the beginning of cytokinesis 2 and the beginning of cytokinesis 3, or the interval between the resolution of cytokinesis 2 and the resolution of cytokinesis 3 , or the interval between cytokinesis 2 start and cytokinesis 3 resolution, or the interval between cytokinesis 2 resolution and cytokinesis 3 start.
[0087] For the purpose of in vitro fertilization, it is considered advantageous that the embryo is transferred to the uterus at the beginning of development, for example, by day 2 or 3, that is, until the stage of 8 cells, to reduce the loss of embryo due to the disadvantages of culture conditions in relation to the in vitro environment, and to reduce the potential adverse results associated with epigenetic errors that may occur during culture (Katari et al. (2009) Hum Mol Genet. 18 (20): 3769-78; Sepulveda et al. (2009) Fertil Steril. 91 (5): 1765-70). Thus, it is preferred that the measurement of cell parameters occur within 2 days of fertilization, although longer periods of analysis, for example, about 36 hours, about 54 hours, about 60 hours, about 72 hours, about 84 hours, about 96 hours, or more, are also contemplated by the present methods.
[0088] Examples of cell parameters in a maturing oocyte that can be evaluated by time-lapse imaging include, among others, changes in the morphology of the oocyte membrane, for example, the rate and extent of separation of the pellucid zone; changes in the morphology of the oocyte nucleus, for example, imminence, completion and germ vesicle breakdown rate (GVBD); the rate and direction of movement of granules in the cytoplasm and nucleus; the cytokinesis of the oocyte and first polar body and the movement and / or duration of extrusion of the first polar body. Other parameters include the duration of the cytokinesis of the mature secondary oocyte and the second polar body.
[0089] Examples of cell parameters in a stem cell or population of stem cells that can be evaluated by time-lapse imaging include, among others, duration of cytokinesis events, time between cytokinesis events, size and shape of stem cells before and during cytokinesis events, number of daughter cells produced by a cytokinesis event, spatial orientation of the cleavage groove, the rate and / or number of asymmetric divisions observed (that is, where a daughter cell maintains a stem cell, while the other is different), the rate and / or number of observed symmetric divisions (ie, where both daughter cells remain as stem cells or both differ) and the time interval between the resolution of a cytokinesis event and when one stem cell starts to differentiate itself.
[0090] Parameters can be measured manually, or they can be measured automatically, for example, by the image analysis software. When image analysis software is used, image analysis algorithms can be used that employ a probabilistic model estimation technique based on the sequential Monte Carlo method, for example, generating hypothesis distributions of embryo / cell models, simulating images based on a simple optical model and comparing these simulations to the observed image data. When such estimates of the probable model are used, cells can be modeled as any appropriate shape, for example, as elliptical collisions in the 2D space, ellipsoid collections in the 3D space, and the like. To deal with depth occlusions and ambiguities, the method can apply geometric constraints that correspond to the expected physical behavior. To improve robustness, images can be captured in one or more focal planes. Gene Expression Analysis
[0091] In some embodiments, embryos or pluripotent cells are evaluated by measuring gene expression. In such embodiments, the cell parameter is a level of gene expression or gene expression profile. Determining the expression of one or more genes, that is, obtaining an expression profile or evaluating expression, can be done by measuring nucleic acid transcripts, for example, from mRNAs, from one or more genes of interest, for example example, a nucleic acid expression profile; or by measuring the levels of one or more different proteins / polypeptides that are products of expression of one or more genes of interest, for example, a proteomic expression profile. In other words, the terms "expression profile" and "expression evaluation" are used widely to include a gene expression profile at RNA level or protein level.
[0092] In some embodiments, gene expression can be assessed by obtaining a nucleic acid expression profile, where the amount or level of one or more nucleic acids in the sample is determined, for example, the nucleic acid transcript of one or more genes of interest. In these embodiments, the sample that is evaluated to generate the expression profile is a sample of nucleic acid. The nucleic acid sample includes a plurality or population of distinct nucleic acids that include information on the expression of the genes of interest to the embryo or cell to be evaluated. The nucleic acid may include RNA or DNA nucleic acids, for example, mRNA, cRNA, cDNA etc., as long as the sample maintains the expression information of the host cell or tissue from which it is obtained. The sample can be prepared in a number of different ways, as is known in the art, for example, by isolating mRNA in a cell, where the isolated mRNA is used as such, amplified, used to prepare cDNA, cRNA, etc., as it is known in the differential expression technique. The sample can be prepared from a single cell, for example, a pluripotent cell from a culture of pluripotent cells of interest, or a single cell (blastomere) from an embryo of interest; or several cells, for example, a fraction of a pluripotent cell culture, or 2, 3 or 4, or more blastomeres of an embryo of interest, using standard protocols.
The expression profile can be generated from the initial nucleic acid sample using any convenient protocol. While a variety of different ways of generating expression profiles are known, such as those employed in the field of differential gene expression analysis, a representative and convenient type of protocol for generating expression profiles is the gene expression profile generation protocol. based on arrangements. Said applications are hybridization assays in which a nucleic acid that displays nucleic acids "probes" for each of the genes to be evaluated / profiled in the profile to be generated and employed. In these assays, a sample of target nucleic acids is prepared for the first time from the initial sample of nucleic acids being evaluated, where the preparation may include marking the target nucleic acids with a label, for example, a member of the production system of signal. After preparing the target nucleic acid sample, the sample is contacted with the array under hybridization conditions, through which complexes are formed between target nucleic acids that are complementary to the probe sequences attached to the surface of the array. The presence of hybridized complexes is then detected, qualitatively or quantitatively.
[0094] The specific hybridization technology that can be practiced to generate the expression profiles used in the subject methods includes the technology described in US Patents 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661,028; 5,800,992; the disclosures of which are incorporated herein by reference; as well as WO 95/21265; WO 96/31622; WO 97/10365; WO 97/27317; EP 373 203; and EP 785 280. In these methods, an array of nucleic acid "probes" that includes a probe for each of the phenotype determining genes whose expression is being evaluated and contacted with target nucleic acids as described above. Contact is carried out under hybridization conditions, for example, stringent hybridization conditions, and unbound nucleic acids are removed. The term "stringent assay conditions", as used here, refers to conditions that are compatible for producing nucleic acid binding pairs, for example, bonded surfaces and nucleic acids in the solution phase, of sufficient complementarity to provide the level desired specificity in the assay while being less compatible for forming linkage pairs between those of insufficient complementarity to provide the desired specificity. The stringent test conditions are the sum or combination (totality) of the hybridization and wash conditions.
[0095] The pattern resulting from the nucleic acid hybridization provides information on expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, normally, at what level, where expression data, i.e., the expression profile (for example, in the form of a transcriptosome), can be both qualitative and quantitative.
[0096] Alternatively, methods based on non-arrangements to quantify the level of one or more nucleic acids in a sample can be employed, including those based on amplification protocols, for example, assays based on Polymerase Chain Reaction (PCR), including quantitative PCR, reverse transcription PCR (RT-PCR), real-time PCR, and the like.
[0097] In some embodiments, gene expression can be assessed by obtaining a proteomic expression profile, where the amount or level of one or more proteins / polypeptides in the sample is determined, for example, the protein / polypeptide encoded by gene of interest. In these modalities, the sample that is evaluated to generate the expression profile employed in the methods is a sample of protein. Where the expression profile and the proteomic expression profile, that is, a profile of one or more protein levels in a sample, any convenient protocol for assessing protein levels can be employed where the level of one or more proteins in the tested and determined sample.
[0098] While a variety of different ways of assessing protein levels are known in the art, a representative and convenient type of protocol for assessing protein levels and ELISA. In ELISA and ELISA-based assays, one or more antibodies specific for the proteins of interest can be immobilized on a selected solid surface, preferably a surface that exhibits protein affinity as wells of a polystyrene microtiter plate. After washing to remove incomplete adsorbed material, the wells of the assay plate are covered with a “blocking” protein, which does not specify that it is known to be antigenically neutral with respect to the test sample such as bovine serum albumin (BSA), casein or milk powder solutions. This allows the blocking of non-spherical adsorption sites on the immobilizing surface, thus reducing the background caused by the non-spherical binding of the amphigene on the surface. After washing to remove the unbound blocking protein, the surface immobilizes and is contacted with the sample to be tested under conditions that are conducive to the formation of immune complexes (amphigene / antibody). Said conditions include diluting the sample with diluents such as BSA or bovine gamma globulin (BGG) in phosphate buffered saline (PBS) / Tween or PBS / Triton-X 100, which also tends to assist in the reduction of non-specific background, and allow the sample is incubated for about 2-4 hours at temperatures in the range of about 25 ° to 27 ° C (although other temperatures can be used). After incubation, the contact surface with an antiserum is washed to remove non-immunocomplexed material. An exemplary washing procedure includes washing with a solution such as PBS / Tween, PBS / Triton-X 100 or borate buffer. The occurrence and amount of immunocomplex complex formation can then be determined by subjecting the immunocomplexes bound to a second antibody containing specificity for the target that differs from the first antibody and detecting the binding of the second antibody. In certain embodiments, the second antibody will have an associated enzyme, for example, urease, peroxidase or alkaline phosphatase, which will generate a colored precipitate upon incubation with an appropriate chromogenic substrate. For example, a peroxidase-conjugated urease or anti-human IgG can be used for a period of time and under conditions that favor the development of immune complex formation (for example, incubation for 2 hours at room temperature in a solution containing PBS such as PBS / Tween). After said incubation with the second antibody and washing to remove unbound material, the amount of maracaga is quantified, for example, by incubation with a chromogenic substrate such as urea and purple bromocresol in the case of a urease marker or 2,2 'acid. -azino-di- (3-ethyl-benzthiazoline) -6-sulfonic (ABTS) and H2O2, in the case of a peroxidase marker. Quantification is thus achieved by measuring the degree of color generation, for example, using a visible spectrum spectrophotometer.
[0100] The previous format can be changed by first connecting the sample to the assay plate. Then, the primary antibody is incubated with the assay plate, followed by detection of the bound primary antibody using a second antibody specifically labeled for the primary antibody.
[0101] The solid substrate on which the antibody or antibodies are immobilized can be prepared by a wide variety of materials and in a wide variety of forms, for example, microtiter plate, microperolas, stem, resin particles, etc. The substrate can be chosen to maximize the signal for minimum proportions, to minimize background bonding, as well as to facilitate separation and cost. Washes can be performed in a manner more appropriate for the substrate to be used, for example, by removing a pearl or stem from a reservoir, emptying or diluting a reservoir such as a microtiter plate or by rinsing a pearl, particle, chromatographic column or filter with a washing solution or solvent.
[0102] Alternatively, non-ELISA-based methods for measuring the levels of one or more proteins in a sample can be employed. Representative examples include, but are not limited to, mass spectrometry, proteomic arrays, xMAPTM microsphere technology, flow cytometry, western blotting and immunohistochemistry.
[0103] The resulting data provides information on expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, normally, on what level, and where expression can be both qualitative and quantitative.
[0104] When generating the expression profile, in some modalities, a sample is evaluated to generate an expression profile that includes expression data for at least one gene / protein, sometimes a plurality of genes / proteins, where by plurality at least two different genes / proteins are understood and often at least about 3, usually at least about 10 and more usually at least about 15 different genes / proteins or more, such as 50 or more, or 100 or more, etc. .
[0105] In its broadest sense, the evaluation of expression can be qualitative or quantitative. As such, where detection is qualitative, the methods provide a reading or evaluation, for example, evaluation, of whether or not the target analyte, for example, nucleic acid or expression product, is present in the sample to be evaluated. In still other modalities, the methods provide a quantitative detection of whether the target analyte is present in the sample to be evaluated, that is, an evaluation or analysis of the actual quantity or relative abundance of the target analyte, for example, nucleic acid or protein in the sample. to be evaluated. In said embodiments, quantitative detection can be absolute or, if the method is a method of detecting two or more different analytes, for example, target nucleic acids or proteins, in a sample, and relative. Accordingly, the term "quantify" when used in the context of quantification of a target analyte, for example, nucleic acids or proteins, in a sample, can refer to absolute or relative quantification. Absolute quantification can be achieved by including known concentrations of one or more control and reference analytes, that is, normalizing, the detected level of the target analyte with known control analytes (for example, by generating a standard curve ). Alternatively, relative quantification can be achieved by comparing the detected levels or amounts between two or more different target analytes to provide a relative quantification of each of the two or more different analytes, for example, in relation to each other.
[0106] Examples of genes whose expression levels are predictive of developmental zygote potential include Cophiline (NM_005507), DIAPH1 (NM_001079812, NM_005219), ECT2 (NM_018098), MYLC2 / MYL5 (NM_002477), DGCR8 (NM_022720), DICER1 (NM_030621, NM_177438), TARBP2 (NM_004178, NM_134323, NM_134324), CPEB1 (NM_001079533, NM_001079534, NM_001079535, NM_030594), Symplekin / SYMPK (NM_00_1), NM_004192) , NM_001098210, NM_001904), DNMT3B (NM_006892, NM_175848, NM_175849, NM_175850), TERT (NM_198253, NM_198255), YY1 (NM_003403), IFGR2 / IFNGR2 (NM_00557), E11 (E37), BT3 , NM_001130971, NM_015537). Other genes whose expression levels can serve as predictors of cell parameters of embryonic potential are provided in Fig. 8. To arrive at a measure of the gene expression level, the expression level is generally evaluated and then normalized to a pattern of control, for example, the mobile of expression in the sample of a gene that is known as constant through development, for example, GAPDH or RPLPO, or of a gene whose expression is not known at that time point.
[0107] Gene expression levels can be determined from a single cell, for example, a blastomer from an embryo of interest, or an isolated oocyte, or a cell isolated from a stem cell culture, etc., or be determined from an embryo, for example, 2, 3, or 4, or more blastomeres of an embryo of interest, up to and including the complete embryo of interest, or multiple cells from a stem cell culture, up to and including the complete stem cell culture, etc.
[0108] In other aspects, the present invention comprises a protocol for carrying out simultaneous genotyping and analysis of gene expression in a single cell. For embryos, this can be used to improve pre-implantation genetic diagnosis (PGD), a procedure where a single cell is removed from an embryo and its DNA and tested for karyotypic defects or the presence of spherical disease genes. Our method allows for simultaneous genetic analysis and gene expression. The method involves the following steps: (1) collecting a single cell in a small volume of medium or buffer, (2) performing one-step reverse transcription and amplification in polymerase chain reaction (PCR) using a mixture of analyze genotyping and gene expression, (3) collect an appendage of the amplified cDNA after less than 18 cycles of PCR to preserve the linearity of amplification, (4) use the cDNA appendage to perform gene expression analysis with standard techniques such as Quantitative real-time PCR, (5) use the remaining sample to perform a second round of PCR to further amplify genetic information for genotyping purposes, and (6) genotyping using standard techniques such as gel elephanttrophoresis. Determine Image Development Potential and / or Gene Expression Analysis
[0109] Once measurements of cell parameters have been obtained, measurements are employed to determine the development potential of the pluripotent embryo / cell. As discussed above, the terms "development potential" and "competence for development" refer to the possibility or ability of a pluripotent cell or tissue to grow or develop. For example, in the case of an oocyte or embryo, the potential for development may be the ability or ability of the oocyte or embryo to grow or develop into a healthy blastocyst. As another example, in the case of a stem cell, the potential for development and the ability or ability to grow or develop in one or more cells of interest, for example, a neuron, a muscle, a B or T cell, and the like . In some embodiments, the potential for development of an oocyte or embryo and the ability or capacity of that oocyte or embryo to develop into a healthy blastocyst; to be successfully implanted in a uterus; to go through gestation; and / or being born alive. In some embodiments, the development potential of a pluripotent cell and the ability or capacity of that pluripotent cell to develop into one or more cells of interest, for example, a neuron, a muscle, a B or T cell, and the like; and / or to contribute to a tissue of interest in vivo.
[0110] By “good development potential”, it is understood that the pluripotent embryo / cell is statistically possible to develop as desired, that is, it has 55%, 60%, 70%, 80%, 90%, 95% or more chance, for example, 100% chance, to develop as desired. In other words, 55 out of 100, 60 out of 100, 70 out of 100, 80 out of 100, 90 out of 100, 95 out of 100, or 100 out of 100 embryos or pluripotent cells that demonstrate the measurement of the cell parameter used to arrive at determining good development potential, in fact, develops as desired. Redecorously, “weak development potential” means that the pluripotent embryo / cell is not statistically possible to develop as desired, that is, it has 50%, 40%, 30%, 20%, 10%, 5% or less chance, for example, 0% chance, to develop as desired. In other words, only 50 out of 100, 40 out of 100, 30 out of 100, 20 out of 100, 10 out of 100, or 5 out of 100 or less of embryos or pluripotent cells that demonstrate the measurement of the cell parameter used to arrive at the determination of fraction development potential do, in fact, develop as desired. As used here, “normal” or “healthy” pluripotent embryos and cells demonstrate good development potential, while “abnormal” pluripotent embryos and cells have development potential.
[0111] In some embodiments, cell parameter measurement is used directly to determine the developmental potential of the pluripotent embryo / cell. In other words, the absolute value of the meditation alone is sufficient to determine the potential for development. Examples of these modalities using time-lapse imaging to measure cell parameters include, but are not limited to, the following, any of which alone or in combination are indicative of good development potential in a human embryo: (a) a cytokinesis 1 that lasts about 0 to 30 minutes, for example, about 6 to 20 minutes, on average about 12 to 14 minutes; (b) a cell cycle 1 that lasts about 20 to 27 hours, for example, about 25 to 27 hours; (c) a time interval between the resolution of cytokinesis 1 and the imposition of cytokinesis 2 which is about 8 to 15 hours, for example, about 9 to 13 hours, with a mean value of about 11 +/- 2 , 1 hour; (d) a time interval, that is, synchronicity, between the beginning of cytokinesis 2 and the beginning of cytokinesis 3 which is about 0 to 5 hours, for example, about 0 to 3 hours, with an average time of about 1 +/- 1.6 hours. Examples of direct measurements, any of which alone or in combination are indicative of poor developmental potential in a human embryo, include, among others: (a) a cytokinesis 1 that lasts more than about 30 minutes, for example, about 32, 35, 40, 45, 50, 55, or 60 minutes or more; (b) a cell cycle 1 that lasts more than about 27 hours, for example, 28, 29, or 30 or more hours; (c) an interval of time between the resolution of cytokinesis 1 and the beginning of cytokinesis 2 that lasts more than 15 hours, for example, about 16, 17, 18, 19, or 20 or more hours, or less than 8 hours, for example, about 7, 5, 4, or 3 or less hours; (d) a time interval between the beginning of cytokinesis 2 and the beginning of cytokinesis 3 which is 6, 7, 8, 9, or 10 or more hours.
[0112] In some modalities, cell parameter measurement is employed by comparing it to a cell parameter measurement of a referendum, or control, embryo / pluripotent cell, and using the result of this comparison to provide a determination of the potential for development of the embryo / pluripotent cell. The terms "referendum" and "control" as used here mean a standardized embryo or cell to be used to interpret the cell parameter measurement of a certain embryo / pluripotent cell and designates a determination of its development potential. The reference or control can be a pluripotent embryo / cell that is known to have a desired phenotype, for example, good development potential, and therefore can be a positive reference or pluripotent embryo / cell control. Alternatively, the reference / control pluripotent embryo / cell may be a pluripotent embryo / cell known to have a desired phenotype, and therefore be a negative reference / control pluripotent embryo / cell.
[0113] In certain modalities, the cell parameter measurement obtained is compared to a cell parameter measurement comparable from a single reference / control pluripotent cell / embryo to obtain information regarding the embryo / cell phenotype being evaluated. In still other modalities, the cell parameter measurements obtained are compared to comparable cell parameter measurements from two or more different embryos or reference / control pluripotent cells to obtain deeper information regarding the embryo / cell phenotype evaluated. For example, cell parameter measurements obtained from the embryos or pluripotent cells being evaluated can be compared to both positive and negative embryos or pluripotent cells to obtain information regarding whether the embryo / cell has the phenotype of interest.
[0114] As an example, cytokinesis 1 in a normal human embryo, that is, with good development potential, and about 0 to 30 minutes, more generally about 6 to 20 minutes, on average about 12 to 14 minutes, that is, about 1, 2, 3, 4, or 5 minutes, more generally about 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 minutes, in some cases 21, 22, 23, 24, 25, 26, 27, 28, 29, or up to about 30 minutes. A longer period to complete cytokinesis 1 in the embryo being evaluated as compared to that observed for a reference embryo and indicative of poor development potential. As a second example, cell cycle 1 in a normal embryo, that is, from the time of fertilization until the completion of cytokinesis 1, is usually completed in about 20 to 27 hours, more generally in about 25 to 27 hours, ie , about 15, 16, 17, 18, or 19 hours, more generally about 20, 21, 22, 23, or 24 hours, and more generally about 25, 26 or 27 hours. A cell cycle 1 that is longer in the embryo being evaluated as compared to that observed for a reference embryo is indicative of poor development potential. As a third example, the resolution of cytokinesis 1 and the imposition of cytokinesis 2 in normal human embryos is about 8 to 15 hours, more often about 9 to 13 hours, with a mean value of about 11 +/- 2, 1 hour; that is, 6, 7, or 8 hours, more generally about 9, 10, 11, 12, 13, 14 or up to about 15 hours. A shorter or longer cell cycle 2 in the embryo being evaluated as compared to that observed for a reference embryo and indicative of poor development potential. As a fourth example, the time interval between the beginning of cytokinesis 2 and the beginning of cytokinesis 3, that is, the synchronicity of the second and third mitoses, in normal human embryos is generally about 0 to 5 hours, more generally about 0, 1, 2 or 3 hours, with an average time of about 1 +/- 1.6 hours; a longer time interval between the completion of cytokinesis 2 and cytokinesis 3 in the embryo being evaluated as compared to that observed in a normal reference embryo and indicative of poor development potential. Finally, as an example of how this modality can be applied when using gene expression levels as parameters for evaluating development potential, lower levels of Cofiline expression, DIAPH1, ECT2, MYLC2, DGCR8, Dicer, TARBP2, CPEB1, Symplekin , YBX2, ZAR1, CTNNB1, DNMT3B, TERT, YY1, IFGR2, BTF3 and / or NELF, that is, 1.5 times, 2 times, 3 times, 4 times, 5 times, 10 times, 20 times, 50 times, or 100 times less expression, in 2-cell embryos being evaluated as compared to those observed for a normal 2-cell reference embryo and indicative of poor developmental potential, while expression that is equal to or greater than that observed for an embryo normal reference of 2 cells and indicative of good development potential. Other examples can be derived from empirical data, for example, observing one or more reference embryos or pluripotent cells next to the embryo / pluripotent cell to be evaluated. Any pluripotent referendum embryo / cell can be employed, for example, a normal referendum sample with good development potential, or an abnormal referendum sample with poor development potential. In some cases, more than one reference sample can be employed, for example, both the reference standard sample and an abnormal reference sample can be used.
[0115] In some embodiments, it may be desirable to use cell parameter measurements that are achieved by time-lapse microscopy or by the expression profile, but not by both time-lapse microscopy and expression profile. In other embodiments, it may be desirable to use cell parameter measurements that are achieved by time-lapse microscopy as well as cell parameter measurements that are achieved by expression profile.
[0116] As discussed above, one or more parameters can be measured and used to determine the development potential of an embryo or pluripotent cell. In some modalities, a measurement of a single parameter may be sufficient to arrive at a determination of development potential. In some embodiments, it may be desirable to employ measurements of more than one parameter, for example, 2 cell parameters, 3 cell parameters, or 4 cell parameters or more.
[0117] In certain modalities, evaluating multiple parameters may be desirable as evaluation for multiple parameters can provide greater sensitivity and specificity. Sensitivity means the proportion of real positives that are correctly identified as such. This can be described mathematically as:

[0118] Thus, in a method in which "positive" are embryos that have good development potential, that is, that will develop into blastocysts, and "negative" are embryos that have poor development potential, that is, that will not develop into blastocysts, a sensitivity of 100% means that the test recognizes all embryos that will develop into blastocysts as such. In some embodiments, the sensitivity of the assay can be about 70%, 80%, 90%, 95%, 98% or more, for example, 100%. Specificity means the proportion of negatives that are correctly identified as such. This can be described mathematically as:

[0119] Thus, in a method in which positive are embryos that have good potential for development, that is, that will develop in blastocysts, and negative are embryos that have poor development potential, that is, that will not be developing in blastocysts, a specificity of 100% means that the test recognizes all embryos that will not develop into blastocysts, that is, they will be stopped before the blastocyst stage, as such. In some embodiments, the specificity of the assay can be about 70%, 80%, 90%, 95%, 98% or more, for example, 100%.
[0120] As demonstrated in the example section below and in figure 7, the use of three parameters provides sensitivity of 94% and specificity of 93% with a cutoff point of 3 times the standard deviations of the blastocyst distribution. In other words, the methods of the invention are able to correctly identify the number of embryos that will develop in blastocysts 94% of the time (sensitivity), and the number of embryos that will be stopped before the blastocyst stage 93% of the time (specificity ). In addition, the specified average values and / or cut-off points can be modified depending on the data set to calculate these values as well as the spherical application.
[0121] In some modalities, the evaluation of an embryo or pluripotent cell includes generating a written report that includes the evaluation of the technician of the subject embryo / pluripotent cell, for example, an “evaluation of development potential”, an “evaluation of abnormalities chromosomal ”, etc. Thus, a subject method can also include a step of generating or extracting a report providing the results of such an assessment, the report of which can be provided in the form of an electronic medium (for example, an electronic display on a computer monitor), or in in the form of a tangkel medium (for example, a report printed on paper or another tangwel medium).
[0122] A “report,” as described here, is an electronic or tangible document that includes report elements that provide information related to an assessment achieved by the methods of the invention. A subject report can be completely or partially electronically generated. A subject report includes at least an assessment of the development potential of the subject embryo or pluripotent cell, an assessment of the probability of the existence of chromosomal abnormalities, etc. A subject report may also include one or more of: 1) information regarding the ease of testing; 2) information from service providers; 3) subject data; 4) sample data; 5) a session of the detailed evaluation report, providing information regarding how the evaluation was achieved in, for example, a) measurements taken from cell parameters, b) reference values used, if any; and 6) other features.
[0123] The report may include information about the test facility, the information of which is relevant to the hospital, clinic, or laboratory in which sample collection and / or data generation was conducted. Sample collection can include how the sample was generated, for example, how it was taken from a subject, and / or how it was grown, etc. The generation of data can include how the images were obtained or the gene expression profiles were analyzed. This information may include one or more details regarding, for example, the name and location of the test facility, the identity of the laboratory technician who performed the test and / or who entered the data, the date and time the test was performed conducted and / or analyzed, the location where the sample and / or resulting data are stored, the batch number of the reagents (e.g., kit, etc.) used in the assay, and the like. The report fields with this information can usually be filled in using the information provided by the user.
[0124] The report may include information about the service provider, which may be located outside the health unit in which the user is located, or within the health unit. Examples of such information may include the name and location of the service provider, the name of the reviewer, and, when necessary or desired, the name of the person who conducted the sample preparation and / or data generation. The report fields with this information can generally be filled with data entered by the user, which can be selected from pre-handwritten selections (for example, using a scroll menu). Other service provider information in the report may include contact information for technical information about the result and / or the interpretative report.
[0125] The report may include a section of subject data, including the medical history of the subjects from which the oocytes or pluripotent cells were harvested, age of the patient, characteristics of the in vitro fertilization cycle (for example, fertilization rate, day 3 of stimulating hormone mobile (FSH)), and, when oocytes are harvested, zygote / embryo cohort parameters (e.g., total number of embryos). These subject data can be integrated to improve embryo evaluation and / or assist in determining the optimal number of embryos to transfer. The report may also include administrative data on the subject (that is, data that are not essential for assessing the development potential), such as information to identify the subject (for example, name, subject's date of birth (DOB), gender, email and / or home address, medical record number (MRN), room and / or bed number in a health unit), insurance information, and the like, the name of the subject's doctor or other health professional who requested it the assessment of development potential and, if different from the requesting physician, the name of a team physician who is responsible for the subject's care (for example, primary care physician).
[0126] The report may include a section of sample data, which can provide information about the biological sample analyzed in the evaluation, such as the type of sample (embryo or pluripotent cell, and type of pluripotent cell), how the sample was manipulated ( eg storage temperature, preparation protocols) and the dates and time of collection. The report fields with this information can generally be filled with data entered by the user, some of which can be provided as pre-handwritten selections (for example, using a drop-down menu).
[0127] The report may include an assessment section of the report, which may include information regarding how the assessments / determinations were achieved as described here. The interpretative report may include, for example, time-lapse images of the embryo or pluripotent cell being evaluated, and / or results of gene expression. The evaluation part of the report may optionally also include a recommendation section. For example, where the results indicate good embryo development potential, the recommendations may include a recommendation that a limited number of embryos be transplanted into the uterus during fertility treatment as recommended in the art.
[0128] It will be readily appreciated that the reports may include additional elements or modified elements. For example, where electronic, the report may contain hyperlinks that indicate internal or external databases that provide more detailed information about the selected elements of the report. For example, the patient data elements of the report may include a hyperlink to an electronic patient record, or a website to access that patient record, whose patient record is maintained in a confidential database. This last modality may be of interest in a hospital system or clinical environment. When in an electronic format, the report is recorded in an appropriate physical medium, such as a medium read on a computer, for example, on a computer memory, zip drive, CD, DVD, etc.
[0129] It will be readily appreciated that the report may include all or some of the elements above, with the provision that the report generally includes at least the elements sufficient to provide the analysis requested by the user (for example, an assessment of development potential) . Utility
[0130] As discussed above, the methods of the invention can be used to evaluate embryos or pluripotent cells to determine their development potentials. This determination of development potential can be used to direct clinical decisions and / or actions. For example, to increase pregnancy rates, doctors often transfer multiple embryos to patients, potentially resulting in multiple pregnancies that are at high risk for both mothers and fetuses. Using the results obtained from the methods of the invention, the potential for development of embryos being transferred to develop into fetuses is determined before transplantation, allowing the doctor to decide how many embryos to transfer in order to maximize the chance of a successful pregnancy while minimizing the risk.
[0131] Evaluations made by the following methods of the invention may also find use in embryos or pluripotent cells classified in a group of embryos or pluripotent cells for their development potentials. For example, in some cases, multiple embryos may be able to develop into blastocysts, that is, they will have good potential for development. However, some embryos will be more likely to reach the blastocyst stage or a higher quality blastocyst than another, that is, they will have better development potential than other embryos. In said cases, the methods of the invention can be used to classify embryos in the group. In said methods, one or more cell parameters for each embryo / pluripotent cell is measured to arrive at a cell parameter measurement for each embryo / pluripotent cell. One or more cell parameter measurements of each of the embryos or pluripotent cells are then employed to determine the development potential of the embryos or pluripotent cells in relation to the other. In some embodiments, measurement of the cell parameter of each of the embryos or pluripotent cells is employed by comparing them directly to one another to determine the potential for developing embryos or pluripotent cells. In some embodiments, cell parameter measurement for each of the embryos or pluripotent cells is employed by comparing cell parameter measurement for a cell parameter measurement of an embryo / pluripotent reference cell to determine the potential for development for each embryo / pluripotent cell, and then compare the determined development potentials for each embryo / pluripotent cell to determine the development potential of the embryos or pluripotent cells in relation to one another. In this way, a doctor who evaluates, for example, multiple zygotes / embryos, can choose only the best quality embryos, that is, those with the best potential for development, to transfer in order to maximize the chances of success of a complete pregnancy. while minimizing risk.
[0132] Evaluations made following the methods of the invention may also find use in determining the potential for development of oocytes that are matured in vitro and stem cells that are cultured in vitro. Information about the potential for oocyte development obtained by the methods of the invention may direct the selection of the oocyte physician to fertilize, resulting in a greater likelihood of success in deriving blastocysts from these oocytes. Likewise, information about the potential for stem cell development can inform the selection of the stem cell doctor to use in procedures to, for example, reconstruct or replace tissue in vivo in a subject in need of it. Reagents, Devices and Kits
[0133] Reagents, devices and kits are also provided to practice one or more of the methods described above. The reagents, devices and kits that are the object of them can vary enormously. The reagents and devices of interest include those mentioned above with respect to the measurement methods of any of the aforementioned cell parameters, where said reagents may include culture plates, culture medium, microscopes, imaging software, imaging analysis software , nucleic acid primers, nucleic acid probe arrays, antibodies, signal producing system reagents, etc., depending on the particular measurement protocol to be performed. For example, reagents may include PCR primers that are spherical to one or more of the Cophilin, DIAPH1, ECT2, MYLC2 / MYL5, DGCR8, Dicer / DICER1, TARBP2, CPEB1, Symplekin / SYMPK, YBX2, ZAR1, CTNNB1, DNMT3B genes , TERT, YY1, IFGR2 / IFNGR2, BTF3, and NELF, as described above. Other examples of reagents include arrays that comprise probes that are specific for one or more of the genes of interest, or antibodies to the proteins encoded by these genes of interest.
[0134] In addition to the above components, the object kits will also include instructions for the practice of the subject methods. These instructions may be present in the object kits in a variety of ways, one or more of which may be present in the kit. One way in which these instructions can be present is information printed on an appropriate medium or substrate, for example, a piece or pieces of paper on which the information is printed, on the kit packaging, on a package insert, etc. Other media, on the other hand, could be a medium read on a computer, for example, floppy disk, CD, etc., in which the information was recorded. Other means that may be present are a website address that can be used over the internet to access information on a removed website. Any convenient means can be present in the kits. Automated cell imaging with a microscope setup
[0135] Some of the methods described above require the ability to observe embryo and stem cell development through time-lapse imaging. This can be achieved using a system containing a multi-channel mini-microscope mount that can be adjusted within a standard incubator. This allows multiple samples to be imaged quickly and simultaneously without having to physically move the plates. An illustrative prototype, shown in Fig. 22, consists of a 3-channel microscopic array with dark field illumination, although other types of illumination can be used. By "three channels," it is understood that there are three independent imaging microscopes of three different culture plates simultaneously. A stepper motor is used to adjust the focal position to focus or obtain stacking of 3D images. White light LEDs are used for illumination, although we have observed that for human embryos, using red light or near infrared (IR) LEDs can improve the contrast ratio between cell membranes and the inner parts of cells. This increased contrast ratio can assist both manual and automated image analysis. In addition, moving to the infrared region can reduce phototoxicity for the samples. The images are captured by low-cost, high-resolution webcams, but other types of cameras can be used.
[0136] As shown in Fig. 22, each microscope of the prototype system described above is used to image a culture plate that can contain anywhere from 1-30 embryos. The microscope collects light from a weak red LED connected to a heatsink to assist any heat generated by the LED, which is too small for short time exposures. The light passes through a conventional dark field patch to interrupt direct light through condensing lenses and over a specimen labeled "petri dish," which is a culture dish containing the embryos being cultured and studied. The culture plate may have powders that help to maintain the order of the embryos and prevent their movement while the plate is carried to and from the incubator. The powders can be spread out together enough so that the embryos can share the same portion of medium. The scattered light is then passed through a microscope objective, then through an achromatic doublet, and over a CMOS sensor. The CMOS sensor acts as a digital camera and is connected to a computer for image analysis and tracking as described above.
[0137] This design is easily scalable to provide significantly more channels and different lighting techniques, and can be modified to accommodate fluid devices for feeding samples. In addition, the project can be integrated with a feedback control system, where culture conditions such as temperature, CO2 (to control pH) and medium are optimized based on real-time feedback and imaging data. This system was used to obtain time-lapse videos of human embryo development, which is useful in determining embryo viability for in vitro fertilization (IVF) procedures. Other applications include stem cell therapy, drug screening, and tissue engineering.
[0138] In one device mode, illumination is provided by a white Luxeon light-emitting diode (LED) mounted on an aluminum heatsink and powered by a BuckPuck current-regulated conductor. LED light is passed through colimaging lenses. The collimated light then passes through a customized machined laser patch, as shown in Fig. 22, and is focused on a hollow cone of light using a spherical condenser lens. The light that is directly transmitted through the sample is discarded by the objective, while the light that is scattered through the sample is collected. In one embodiment, Olympus lenses with 20X magnification are used, although smaller magnifiers can be used to increase the field of view, or larger magnifiers can be used to increase resolution. The collected light is then passed through an achromatic doublet lens (ie try tubes) to reduce the effects of chromatic and spherical aberration. Alternatively, the light collected from the imaging objective can be passed through another objective, pointed in the opposite direction, which acts as a replacement for the tube lens. In one configuration, the imaging lens can be a 10X objective, while the tube lens can be a 4X objective. The resulting image is captured by a CMOS sensor with 2 megapixel resolution (1600 x 1200 pixels). Different types of sensors and resolutions can also be used.
[0139] Fig. 23A shows a photograph of a multi-channel microscope arrangement, containing 3 identical microscopes. All optical components are mounted on lens tubes. In the operation of the arrangement system, the petri dishes are loaded on acrylic platforms that are assembled in stages with 2 axes of manual inclination, which allows adjustment of the image plane in relation to the optical axis. These stages are fixed to the base of the microscope and do not move after the start of the alignment. The lighting modules, which consist of LEDs, collimating lenses, patch stops, and condensing lenses, are mounted in xyz manual stages for positioning and focusing the illumination light. The imaging modules, which consist of objectives, achromatic lenses, and CMOS sensors, are also mounted in xyz manual stages for positioning the field of view and focus of the objectives. All 3 imaging modules are connected to linear blades and supported by a single lever cylinder, which is operated using a stepper motor. This allows for computer controlled focus and automatic capture of image stacks. Other methods of autofocus as well as performance can be used.
[0140] The microscope arrangement was placed inside a standard incubator, as shown in Fig. 23B. The CMOS image sensors are connected via USB connection to a single hub located inside the incubator, which is routed to an external PC along with other lines of communication and power. All electrical cables leave the incubator through the center of a rubber stopper sealed with silicone glue.
[0141] The microscope array described above was used to record time-lapse images of early human embryo development and documented growth of the zygote to blastocyst stages. Four different experiments monitored a total of 242 embryos. Of this group, 100 were imaged until the 5th or 6th; the others were removed from the imaging stations at various time points for gene expression analysis. A screen capture of the image capture software and imaged embryos is shown in Fig. 24. The images were captured every 5 minutes with roughly 1 second of low light exposure per image. The total amount of light received by the samples was equivalent to 24 minutes of continuous exposure, similar to the total level experienced in an IVF clinic during manipulation. The duration of 1 second of light exposure can be reduced. Prior to working with human embryos, we conducted extensive control experiments with pre-implantation mouse embryos to ensure that both blastocyst formation rates and gene expression patterns were not affected by the imaging process.
[0142] Figs. 25 and 26 show images selected from time-lapse sequences. The images are shown for day 1, day 2.5, day 4, and day 5.5. For the sequence shown in Fig. 25, 3 of 9 embryos developed into blastocysts, and for the sequence shown in Fig. 26, 5 of 12 embryos developed into blastocysts. The individual embryos were monitored over time, even though their positions in the photographic field changed as the embryos were subjected to a medium change on day 3. The use of sequential medium is necessary to achieve the specific requirements of the stage of the developing embryos. . During the exchange of media, the embryos were removed from the imaging station for a few minutes and transferred to new petri dishes. To maintain the traceability of the identity of each embryo during the change of medium, the transfer of samples from one plate to another was filmed to verify that the embryos were not mixed. This process was also used during the collection of samples for analysis of gene expression. The issue of tracking the embryo's identity can be mitigated by using pogues to aid the arrangement of the embryos in a particular order. Petri dish with micropogues
[0143] When transferring petri dishes between different stages, embryos can sometimes move around, thus making it difficult to maintain the traceability of the embryo's identity. This presents a challenge when time-lapse imaging is performed in one stage and the embryos are subsequently moved to a second stage for embryo selection and transfer. One method is to grow embryos in individual petri dishes. However, this requires that each embryo has its own drop of medium. In a typical IVF procedure, it is generally desired to grow all of the patient's embryos in the same petri dish and in the same drop of half drop. To address this problem, we designed a customized petri dish with micropogues. This prevents the embryos from moving and maintaining their arrangements on the petri dish when transferred to and from the incubator or imaging stations. In addition, the powders are small enough and spread out together so that they can share the same drop of medium and all are viewed simultaneously through the same microscope. The bottom surface of each micropogo has an optical quality finish. Fig. 27A shows a drawing with dimensions for one embodiment. In this version, there are 25 micropogues closely spaced within a 1.7 x 1.7 mm field of view. Fig. 27B shows a 3D view of the micropogues, which are recessed approximately 100 microns on the surface of the plate. Fiduciary markers, including letters, numbers, and other markers, are included on the plate to aid identification.
[0144] All references cited here are incorporated as a reference in their entirety. EXAMPLES
[0145] The following examples are presented to provide those skilled in the art with a disclosure and description of how to prepare and use the present invention, and are not intended to limit the scope of what the inventors regard as their inventions nor are they intended to represent that the experiments below are all or the only experiments carried out. Efforts have been made to ensure accuracy with respect to the numbers used (eg quantities, temperature, etc.) but some experimental errors and deviations can be accounted for. Unless otherwise indicated, parts are parts by weight, molecular weight and weighted average molecular weight, temperature and degrees Centigrade, and pressure and the atmospheric pressure or near it.
[0146] Sample Source
[0147] All embryos used in this study were collected over a period of several years and fertilized and cryoperserved by multiple embryologists. The average number of embryos per patient in our study was 3, and all deity groups found in a routine IVF center were included. Notably, all embryos used for these experiments were generated by IVF (as opposed to ICSI), so the embryos were derived from sperm that had relatively normal function (at least in terms of their ability to penetrate the cumulus, zone, and oolemma and form a pro-nucleus). The stimulation protocols were standard long-term lupron protocols (cdc.gov/art). The cryopreservation of supernumerary human embryos was achieved by placing them in a freezing medium (1,2-propanediol 1.5 M + sucrose 0.2 M) for 25 minutes at room temperature (22 + 2oC). The embryos were then frozen using a slow freezing protocol (-1oC / min at -6.5oC; hold for 5 min; sow; hold for 5 min; - 0.5oC / min at -80oC; dip in titrated nitrogen). Committee. No protected health information could be associated with embryos.
[0148] A large set of cryopreserved embryos has been validated and the following observations have been made: 1) The embryos demonstrated indicative time of normal development of the embryo in terms of milestones including: Cleavage to 2 cells (occurred early day 2), onset of degradation RNA (occurred on days 1 to 3), cleavage to 4 and 8 cells (occurred late on day 2 and day 3, respectively), activation of the embryonic genome (on day 3 of the 8 cell stage), and morula formation and blastocyst (occurred on Days 4 and 5, respectively). 2) Embryos have demonstrated efficiency in reaching the blastocyst stage that is typical of embryos obtained in a kinetic environment. This is possibly due to the fact that the embryos were cryopreserved in the 2PN stage and represented the arrangement of embryos found in an IVF clinic since no "screening" of those that could and could not develop before the cryopreservation in stage 1 ( as it is typical of cryopreserved embryos late in the development of the day 3 or blastocyst stages). Thus, our data confirm that these embryos had similar blastocyst formation rates compared to those observed in typical IVF clinics. 3) Previous studies have shown that embryos that are frozen in the 2PN stage have a similar potential for development, implantation, clinical pregnancy and birth when compared to fresh embryos. Other studies have also shown similar results for frozen oocytes suggesting that the earliest developmental events in the human embryo maintain an appropriate post-cryopreservation timeline. 4) We focus on parameters that were not dependent on fertilization time or defrost time. The first parameter we measured (duration of the first cytokinesis) is short-lived (about 10 to 15 min) and is not dependent on the time of fertilization in this study (this is able to be measured independently in all embryos without counting the result Final). In addition, all subsequent parameters are measured in relation to this initial measurement point and purchased between embryos that succeed in developing the blastocyst and those that fail. 5) Finally, we note that the fresh (not frozen) embryos that are 3PN are known to develop in the same timeframe as normal fresh embryos; we compared the parameters in fresh 3PN embryos that were obtained from Stanford IVF clinics, and it was noted that they were no different from our cryopreserved embryos or published reports.
[0149] Experimental plan
[0150] In four experimental sets, we tracked the development of 242 embryos in a pro-nuclear stage (61, 80, 64 and 37, respectively). In each set of experiments, human zygotes were thawed on day 1 and cultured in small groups on multiple plates. Each plate was observed independently with time-lapse microscopy under dark field illumination in separate imaging stations. At approximately 24-hour intervals, an embryo plate was removed from the imaging system and collected in single embryos and single cells (blastomeres) for analysis of gene expression by quantitative, real-time, high-performance PCR. Each plate typically contained a mixture of embryos that reached the stage of development at the time of harvest (called "normal") and those that were interrupted or delayed in earlier stages, or fragmented extensively (called "abnormal"). Embryos were analyzed as single intact embryos or were disassociated in single blastomeres followed by gene-specific RNA amplification. A subset of embryos (100 out of 242) was imaged until day 5 or 6 to monitor blastocyst formation.
[0151] Human embryo culture and microscopy
[0152] Human embryos were thawed by removing cryopras from the liquid nitrogen storage tank and placed at room temperature. Once the vial was thawed, they were opened and the embryos were viewed under a dissecting microscope. The contents of the flasks were then poured into the bottom of a 3003 culture plate. The embryos were located in the drop and the survival of each embryo was assessed and recorded. At room temperature, the embryos were transferred to a 3037 culture plate containing 1.2 M 1.0 propanediol + 0.2 M sucrose for 5 minutes, then 0.5 M propanediol + 0.2 M sucrose for 5 minutes , and 1.2 0.0 M propanediol + 0.2 M sucrose for 5 minutes. Subsequently, the embryos were grown in Quinn's Advantage Cleavage Medium (CooperSurgical) supplemented with 10% Quinn's Advantage Protein Substitute (SPS; CooperSurgical) between day 1 to 3, and Quinn's Advantage Blastocyst Medium (CooperSurgical) with 10% SPS after day 3 using microdroplets under oil. All experiments used the same type of stage-cleavage medium, except for two stages during the first experiment, which used a Global medium (LifeGlobal, Guilford, CT). In this small subset (12 embryos), the embryos had a slightly lower rate of blastocyst formation (3 out of 12, or 25%) but the sensitivity and specificity of our predictive parameters were both 100% for this group.
[0153] Time-lapse imaging was performed on multiple systems to accommodate concurrent analysis of multiple samples as well as to validate data consistency across different platforms. The systems consisted of 7 individual microscopes: (1) two modified Olympus IX-70/71 microscopes equipped with Tokai Hit heating stages, white light Luxeon LEDs, and a dark field illumination aperture; (2) two modified Olympus CKX-40/41 microscopes equipped with heating stages, Luxeon white LEDs, and Hoffman Modulation Contrast Lighting (note: these systems were used only during the first 4 experiments after which it was decided that dark field illumination was preferred for measuring parameters); and (3) a customized miniature microscope arrangement constructed of 3 channels that fits inside a standard incubator, equipped with white light Luxeon LEDs and openings for dark field illumination. We did not see any significant difference in developmental behavior, blastocyst formation rate, or gene expression profile between embryos grown in these different systems; in fact, our parameters for predicting blastocysts were consistent across multiple systems and experiments.
[0154] The light intensity for all systems was significantly lower than the light typically used in an assisted reproduction microscope due to the low energy of LEDs (in relation to a typical 100W Halogen lamp) and high sensitivity of the sensors of the camera. Using a force gauge, determined that the energy of a typical assisted reproduction microscope (Olympus IX-71 Hoffman Modulation Contrast) at a wavelength of 473 nm varies roughly from 7 to 10 mW depending on the magnification, while the energy of our Imaging systems were measured to be between 0.2 and 0.3 mW at the same wavelength. The images were captured at an exposure time of 1 second every 5 minutes for up to 5 or 6 days, resulting in approximately 24 minutes of exposure to continuous light. At an energy of 0.3 mW, this is roughly equivalent to 1 minute of exposure under a typical assisted reproduction microscope.
[0155] To track the identity of each embryo during the correlated imaging and gene expression experiment, we installed a video camera on the stereomicroscope and recorded the sample transfer process during the medium exchange and sample collection. We conducted control experiments with pre-implantation mouse embryos (n = 56) and a small subset of human embryos (n = 22), and we did not observe any significant difference (p = 0.96) in the blastocyst formation rate between the imaged embryos and controls.
[0156] High performance qRT-PCR analysis
[0157] For qRT-PCR analysis of single embryos or single blastomeres, the embryos were first treated with Tyrode's Acid solution to remove the pellucid zone. To collect simple blastomeres, the embryos were incubated in Quinn’s Advantage medium free of Ca2 + Mg2 + with HEPES (CooperSurgical) for 5 to 20 minutes at 37 ° C with strict pipetting. The samples were collected directly in 10 µl of reaction buffer; then the reaction of a reverse transcription / pre-amplification step was carried out as previously described. Groups of primers and probe mixes of 20X ABI assay-on-demand qRT-PCR (Applied Biosystems) were used as spherical primers for the genes during reverse transcription and pre-amplification reactions. High-throughput qRT-PCR reactions were performed with Fluidigm Biomark 96.96 Dynamic Arrays as previously described using the ABI on-demand test of qRT-PCR probes. All samples were loaded in 3 or 4 technical replicates. The analysis of the qRT-PCR data was performed with qBasePlus (Biogazelle), Microsoft Excel, and customized software. Certain genes have been omitted from the analysis of the data due to their poor data quality (e.g., weak PCR amplification curves) or low consistency due to lack of expression in the evaluated embryos. For blastomeric age analysis, the maternal transcript group used included DAZL, GDF3, IFITM1, STELLAR, SYCP3, VASA, GDF9, PDCD5, ZAR1 and ZP1, while the embryonic gene group includes ATF7IP, CCNA1, EIF1AX, EIF4A3 , H2AFZ, HSP70.1, JARID1B, LSM3, PABPC1, and SERTAD1. The expression value of each gene in relation to the reference genes GAPDH and RPLP0, as well as in relation to the measurement, was calculated using the geNorm and AACt methods. GAPDH and RPLP0 were selected as reference genes for this study empirically based on the value of gene stability and coefficient of variation: 1.18 and 46% for GAPDH and 1.18 and 34% for RPLP0. These were the most stable among the 10 housekeeping genes we tested and well within the range of a typical heterogeneous sample set. Second, we observed that in simple blastomeres, as expected, the amount of RPLP0 and GAPDH transcripts decreased by approximately 1 Ct by dividing the stage between 1 cell and 8 cells, congruent with the expectations that each cell inherits approximately half of the group. mRNA with each cleavage division, in the absence of new transcripts before the EGA during the first 3 hours of human development. Third, we observed that the level of expression of these reference genes in the simple blastomeres remained between the stages of 8 cells to the morula, after EGA started. In the intact embryo cell, the Ct values of both RPLP0 and GAPDH remained largely constant throughout development until the morula stage with a slight increase in the blastocyst stage perhaps due to the increased transcript levels in the larger numbers of blastomeres present. Most of the gene expression analysis performed in this study focused on the developmental stages before the morula stage, however, when the reference gene expression level was extremely stable.
[0158] Automated cell tracking
[0159] Our cell tracking algorithm uses a probabilistic structure based on Monte Carlo sequential methods, which in the computer's field of view is generally referred to as the particle filter. The particular filter tracks the propagation of three main variables that vary over time: state, control and measurement. The state variable is a model of an embryo and is represented as an ellipse pair. The control variable is an input that transforms the state variable and consists of our cell propagation and division model. The measurement variable is an observation of the state and consists of our images acquired by the lapse of microscopic rhythm. Our estimate of the current state of each time step is represented with a later probability distribution, which is approximated by a set of heavy samples called particles. We use the terms particles and embryo models interchangeably, where a particle is a hypothesis of an embryo model at any given time. After initialization, the particle filter repeatedly applies three steps: forecasting, measuring, and updating.
[0160] Forecast: The cells are represented as ellipses in the 2D space, and each cell has an orientation and overlap index. The overlap index specifies the relative height of the cells. In general, there are two types of behavior that we want to predict: cell movement and cell division. For the movement of the cell, our control input takes a particle and, randomly, disturbs each parameter for each cell, including position, orientation and length of the major and minor axes. The disturbance is randomly sampled from a normal distribution variance with relatively small (5% of the values initiated). For cell division, we use the following approach. At a certain point in time, for each particle, we designate a 50% probability that one of the cells will divide. This value was chosen emphatically, and covers a wide range of possible cell divisions, maintaining a good coverage of the current configuration. If a division is foreseen, then the cell in division is chosen at random. When a cell is chosen to divide, we apply symmetric division along the major axis of the ellipse, producing two daughter cells of equal size and shape. Then, we randomly disturb each value for the daughter cells. Finally, we randomly selected the overlap indexes of the two daughter cells, maintaining their collective overlap in relation to the rest of the cells.
[0161] After applying the control input, we convert each particle into a simulated image. This is achieved by projecting the etphptic shape of each cell onto the simulated image using the overlap index. The corresponding pixel values are set to a binary value of 1 and expanded to create a membrane thickness comparable to the observed image data. Since the embryos are partially transparent and out of the focus of light they are collected, the cell membranes at the bottom of the embryo are only visible a few times. Therefore, occluded cell membranes are added with a 10% probability. In practice, it has been found that these occluded membrane points are crucial for modeling the exact shape, but it is important to make them sparse enough so that they do not look like a visible edge.
[0162] Medication: Once we generate a distribution of hypothetical models, the corresponding simulated images are compared with the actual microscope image. The microscope image is pre-processed to create a binary image of cell membranes using a prince of the method based on curvature followed by thresholding. The accuracy of the comparison is assessed using a truncated symmetric chamfer distance, which is then used to assign a weight, or probability, to each particle.
[0163] Update: After weights are assigned, the particles are selected in proportion to these weights to create a new set of particles for the next iteration. This concentrates the distribution of particles in the most likely region. Particles with low probability are discarded, while particles with high probability are multiplied. Resampling of particles is performed using the low variance method.
[0164] Once the embryos have been modeled, we can extract the dynamics of imaging parameters such as the duration of cytokinesis and time between mitosis, as discussed in the main text. Our cell tracking software was previously implemented in Matlab, and computing times ranged from a few seconds to half a minute for each image, depending on the number of particles. Our current version of the software is implemented in C, and computing times vary from 1 to 5 seconds, depending on the number of particles. EXAMPLE 1
[0165] Imaging analysis to determine the potential for embryo development. METHODS
[0166] Frozen human embryo cells 1, also referred to as zygotes, were thawed and placed in culture and under culture conditions like those used in IVF procedures. As described in more detail above, these embryos appear to be representative of the typical in vitro fertilization (IVF) population as they were frozen in the 2PN stage and, thus, indiscriminately cryopreserved. This is in contrast to embryos typically cryopreserved in later stages of development after the transfer of those perceived to be of the highest quality during fresh cycles. For some experiments, the embryos were placed on a standard culture plate. For other experiments, the embryos were grown in a customized culture plate with micropogues of optical quality.
[0167] Growth embryos, typically between 1 to 30 per plate, were followed up individually by time-lapse imaging with a computer-controlled microscope equipped for digital image storage and analysis. In some cases, rhythm-lapse imaging was performed with inverted microscopes equipped with heated stages and incubation chambers. In other cases, time-lapse imaging was performed with customized miniature microscopic arrangements that fit inside a conventional incubator, which allowed for the concurrent culture of multiple sample plates in the same incubator and was scalable to accommodate multiple channels without limitations in the minimum time interval between successive image capture. The use of multiple microscopes also eliminates the need to move the sample, which improves the accuracy of the system and the overall confidence in the system. Imaging systems use dark field illumination, which provided enhanced image contrast for further feature extraction and image analysis, although it was noted that other illuminations would have been sufficient. The individual microscopes in the incubator were isolated from each other, providing each culture plate with its own controlled environment. This allows the plates to be transformed to and from the imaging stages without disturbing the environment of the other samples.
[0168] Time-lapse images were collected for subsequent analysis of cell morphology, including measurement of at least one of the following cell parameters: the duration of the first cytokinesis, the interval the rhythm between first and second cell division, and the interval between time between the second and third cell division. The images shown in the figures were taken at an exposure time of 1 second every 5 minutes for up to 5 or 6 days. As described in more detail below, the first cytokinesis generally occurs one day after fertilization and lasts between about 14 minutes. The first and second cell divisions are generally separated by an average of about 11 hours. The second and third cell divisions are generally separated by an average of about 1 hour. Thus, the imaging took place over a period of time of approximately 36 hours (more or less several hours) after fertilization. RESULTS
[0169] The development schedule of a healthy pre-implantation human embryo in the culture has been documented for a period of six days a day of time-lapse imaging (Fig. 2). It was observed that a normal human zygote undergoes a first cleavage division early on day 2. Subsequently, the embryo cleaves to a late embryo of 4 cells and 8 cells on day 2 and day 3 respectively, before compacting into a morula in the day 4. The first morphologically evident cell differentiation is observed on day 5 and 6 during blastocyst formation, when totipotent blastomeres differentiate into trophoectodermal cells, which generates extra embryonic structures such as the placenta, or internal cell mass, which develops in the fetus in vivo and pluripotent embryonic stem cells in vitro.
[0170] Next, we track the development of 242 embryos normally fertilized in four sets of independent experiments and document the distribution of normal and interrupted embryos between samples that were grown for day 5 or 6. Of the 242 embryos, 100 were grown for day 5 or 6 and the rate of blastocyst formation was found to be between 33% to 53%, similar to the rate of blastocyst formation in riparian IFV chronic (Fig. 3). The remaining interrupted embryos at the different stages of development, most commonly between 2 cells and 8 cells, were defined as abnormal (Fig. 3). In order to identify quantitative imaging parameters that predict success in embryo development for the blastocyst stage, we extracted and analyzed various parameters from time-lapse videos, including blastomer size, thickness of the pellucid zone, degree fragmentation, the length of the first two cell cycles, time intervals between the first mitoses and the duration of the first cytokinesis. During the analysis of video images of both normal and abnormal developing embryos, we observed that many interrupted embryos experienced abnormal cytokinesis during the first cell division. Normal embryos completed cytokinesis in a narrow time window of 14.3 +/- 6.0 min from the appearance of cleavage grooves to complete the separation of daughter cells, in a flat and controlled manner. This is shown in the top Fig. 4. In contrast, abnormal embryos commonly showed one of two abnormal cytokinesis phenotypes. In the milder phenotype, the cytokinesis morphology and mechanism appeared normal, but the time required to complete the process was longer, ranging from a few additional minutes to an hour (Fig. 4). Occasionally, an embryo that has undergone a slightly prolonged cytokinesis still developed into a blastocyst. In the most severe phenotype, the cytokinesis morphology and mechanism were disturbed. For example, as shown in the example in the lower panel of Fig. 4, the embryos formed a unilateral cleavage groove and were subjected to an unusual series of membrane wrinkling events for several hours before finally breaking down into smaller components. Other variations of this type of behavior have also been observed. In addition, abnormal embryos demonstrating these more severe phenotypes have often become fragmented, providing direct evidence that embryo fragmentation is likely to be a by-product of abnormal cytokinesis subsequently resulting in abnormal embryo development.
[0171] Detailed analysis of our imaging results indicated that normal embryos followed rigorous cytokinesis and mitosis times during the initial divisions, before the activation of the embryonic gene (EGA) begins, suggesting that the potential for embryo development is predetermined inherited maternal programs. In particular, we observed three time intervals, or parameters, in the cell cycles of the early stage embryo that were strictly regulated: (1) duration of the first cytokinesis, (2) time interval between the first and second mitosis, and (3) synchronicity of the second and third mitoses. The relationship between these three time intervals and the morphological changes is shown in Fig. 5. For normal embryos, we measure these parameters as being approximately 14.3 +/- 6.0 minutes, 11.1 + / 2.1 hours, and 1.0 +/- 1.6 hours, respectively (shown here as mean standard deviation plus / minus).
[0172] Imaging was also performed on a small set (n = 10) of fresh (non-cryopreserved) embryos that were 3PN (triploid) since the stage of a single cell. 3PN embryos have been shown to follow the same schedule of reference events as fresh normal embryos through at least the first three cell cycles. These embryos were imaged before our main experiments to validate the imaging systems (but for technical reasons they were not followed up outside of a blastocyst). Out of this set of fresh embryos, 3 of the embryos followed a schedule of similar events as our 2PN cryopreserved embryos with cytokinesis duration ranging from 15 to 30 min, time between the first and second mitoses ranging from 9.6 to 13.8 hours , and time between second and third mitosis ranging from 0.3 to 1.0 hour. However, in 7 of the embryos we observed a unique cytokinesis phenotype that was characterized by the simultaneous appearance of 3 cleavage grooves, a slightly prolonged cytokinesis, and, finally, the separation into three daughter cells (Fig. 4). These embryos had a cytokinesis duration ranging from 15 to 70 min (characterized as the time between the beginning of the cleavage groove until complete separation in 3 daughter cells), time between the first and second mitoses (3 cells for 4 cells) varying from 8.7 to 12.7 hours, and time between second and third mitosis (4 cells to 5 cells) ranging from 0.3 to 2.6 hours. This observation, together with the varied range of cytokinesis phenotypes presented by abnormal embryos, suggests that our cryopreserved embryos are not delayed in development by the cryopreservation process and behave similarly to fresh zygotes that cleave into 2 blastomeres.
[0173] Embryos that have reached the blastocyst stage could be predicted, with sensitivity and specificity of 94% and 93% respectively, having a first cytokinesis between 0 to 33 min, a time between first and second mitosis of between 7.8 to 14.3 hours, and a time between the second and third mitosis of between 0 and 5.8 hours (Fig. 6). On the other hand, it was predicted that embryos that showed values outside one or more of these windows were interrupted. All normal embryos successfully developed in a blastocyst showed similar values in all three parameters. In contrast, the abnormal embryos showed a very high amount of variability in the periods of time it took to complete the intervals (Fig. 6). We observed that (1) a longer period of time to complete the first cytokinesis than normal indicates poor development potential; (2) a greater or lesser interval between first and second cell divisions than normal indicates weak potential for development; and (3) a longer time interval between second and third cell divisions than normal indicates poor development potential. Thus, these parameters were predictive of the embryo's ability to proceed with blastocyst formation and blastocyst quality.
[0174] Finally, we observed that while each parameter was autonomously predictive of the embryo's development potential, the use of all three parameters provided sensitivity and specificity that both exceeded 90%, with a cutoff point of 3 times the standard deviations. The receiver operation characteristic (ROC) curve for these parameters is shown in Fig. 7. The curve in this Figure shows the rate of true positives (sensitivity) versus the rate of false positives (1 - specificity) for various standard deviations from cutoff. To reach this ROC, the following numbers were used: Number of true positives = 34 (correctly predicted to reach blastocyst), number of true negatives = 54 (correctly predicted to interrupt), number of false positives = 4 (incorrectly predicted to arrive at blastocyst), number of false negatives = 2 (incorrectly predicted to interrupt). DISCUSSION
[0175] Our analysis indicates that embryos that follow a strict calendar in mitosis and cytokinesis during the first three cleavage divisions are much more likely to develop into the blastocyst phase and form a high-quality blastocyst with an expanded internal cell mass (ICM ). Dynamic morphological parameters can be used to select the optimal embryos for transfer or cryopreservation during an IFV procedure. These parameters can also be used to distinguish between different qualities of a blastocyst, allowing a classification of relative potentials of embryo development within a group. The standard practice in IVF techniques is to transfer in the 8 cell stage (day-3). Some clinics choose to grow embryos for the blastocyst stage (day 5), since the blastocyst transfer has up to twice the implantation rates compared to the transfer on day 3. However, many techniques avoid prolonged culture due to the risk increased number of epigenetic disorders. Predictive imaging parameters can be used to predict embryo viability by a 4 cell stage (on day 2) and before activation of the embryonic gene. This may allow embryo transfer or cryopreservation an entire day earlier than is typically practiced and before the embryos undergo significant changes in their molecular programs. This can also allow the most ideal embryos to be selected for PGD or other types of analysis. EXAMPLE 2
[0176] Validation of imaging parameters through gene expression analysis, and use of gene expression analysis to determine development potential. METHODS
[0177] Frozen human embryo cells 1, also referred to as zygotes, were thawed and placed in culture and under culture conditions like those used in IVF procedures. For some experiments, the embryos were placed on a standard culture plate. For other experiments, the embryos were grown in a customized culture plate with micropogues of optical quality.
[0178] Embryos were removed from the culture and the imaging system and collected as individual embryos or individual cells (blastomeres) for analysis of gene expression. Each plate usually contained a mixture of embryos, with some reaching the expected stage of development at the time of harvest, and others interrupted at early stages of development or extensively fragmented. Those that reached the expected stage of development at the time of harvest were classified as "normal", while those that were discontinued were considered "abnormal. For example, when an embryo plate was removed from the imaging stage on day 2 late for the sample collection, any embryo that had reached the stage of 4 cells and beyond could be identified as normal, while those that failed to reach the stage of 4 cells would be labeled as interrupted. These interrupted embryos were classified by the stage of development in which they were became interrupted, so that an embryo with only 2 blastomeres on day 2 late could be analyzed as an embryo interrupted in 2. Cells were taken to exclude embryos that morphologically appeared to be dead and porous at the time of sample collection (for example , degenerated blastomeres) .Only embryos that looked alive (both for normal when interrupted) were used for analysis of gene expression. However, it is possible that embryos that appeared normal at the time of collection could eventually be interrupted if they were allowed to grow at a late stage. Representative analysis of gene expression of embryos from each of these classes was performed by quantitative RT-PCR (qRT-PCR). At approximately 24 hour intervals, embryos were collected from individual imaging systems for analysis of gene expression in high-throughput qRT-PCR with multiplex reactions of up to 96 genes evaluated against 96 samples. The analysis of gene expression was performed with the Fluidigm Biomark System, which can perform up to 9216 simultaneous reactions of qRT-PCR based on TaqMan in quantities of nanoliters. RESULTS
[0179] In order to elucidate the molecular mechanisms that may be underlying morphological events, a correlation of gene expression profiles was performed. The expression levels of 96 different genes belonging to different categories were tested per sample, including housekeeping genes, germ cell markers, maternal factors, EGA markers, trophoblast markers, internal cell mass markers, pluripotency markers, epigenetic regulators, factors transcription agents, hormone receptors and others (Table 1, in Figure 19). Two slightly different, but overlapping, sets of genes were evaluated in two different experimental sets, providing a unique set of diagnostic genes for the target human embryo. The unique gene sets have been compiled from data on gene expression in embryos of model organisms or in human embryonic stem cells, as well as from our own unprecedented microarray data. The state of expression of these sets of genes in pre-implantation human embryos is revealed for the first time in the present study.
[0180] The expression value of each gene in relation to reference genes GAPDH and RPLPO, as well as in relation to the average gene, was calculated using geNorm (El Toukhy T, et al. (2009) Hum Reprod) and AACt ( Vanneste E, et al. (2009) Nat Med 15: 577- 83) methods. The value of genetic stability and coefficient of variation were 1.18 and 46% for GAPDH and 1.18 and 34% for RPLPO, the most stable among the 10 housekeeping genes we tested and well within the range of a heterogeneous sample set. In simple blastomeres, as expected, the amount of RPLPO and GAPDH transcripts decreased by approximately 1 Ct per division between the 1 cell and 8 cell stages, due to the half-cleavage reduction effect, as well as the lack of EGA during the first 3 days of human development. The expression level of these reference genes in the simple blastomeres remained stable between the stages of 8 cells to the morula. As for the total embryo, the Ct values of both RPLPO and GAPDH remained largely constant throughout development until the morula phase. The mobile expression of RPLPO and GAPDH and increased significantly in blastocysts, probably due to the increased number of blastomeres present. These variations did not affect the validity of RPLPO and GAPDH as reference genes. Most of the gene expression analysis performed in this study focused on the developmental stages before the morula stage, when the reference gene expression level was extremely stable.
[0181] Differential gene expression between normal and abnormal embryos. Fig. 8 shows the average expression level of 52 genes of 6 abnormal 1- for 2 cell embryos and 5 normal 1- for 2 cell embryos plotted on a radar graph on a logarithmic scale. The interrupted embryos in general showed a reduced amount of mRNA compared to normal embryos that facilitated the most severely affected cytokinesis, RNA processing and miRNA biogenesis. The genes highlighted with an asterisk indicate a statistically significant difference (p <0.05) between normal and abnormal embryos, as determined by the Mann-Whitney test. These 18 genes are Cofilina, DIAPH1, ECT2, MYLC2, DGCR8, Dicer, TARBP2, CPEB1, Symplekin, YBX2, ZAR1, CTNNB1, DNMT3B, TERT, YY1, IFGR2, BTF3 and NELF. Each gene belongs to a group, as indicated in the Figure, namely Cytokinesis: Cofilina, DIAPH1, ECT2 and MYCL2; miRNA biogenesis: DGCR8, Dicer and TARBP2; RNA processing: YBX2; maternal factors: ZAR1; housekeeping: CTNNB1; pluripotency: DNMT3B, TERT and YY1; receptor: IGFR2, and transcription factor: BTF3 and NELF. In most cases, the expression of these genes was greater than normal 1 - and 2 cell embryos than in interrupted 1 - and 2 cell embryos.
[0182] Interestingly, certain categories of determined genes were more affected in abnormal embryos than others. For example, in abnormal embryos, most housekeeping genes, hormone receptors and maternal factors have not been significantly altered in gene expression, while many genes involved in miRNA cytokinesis and biogenesis have shown significantly reduced expression. In addition, among the genes that were affected, some genes showed a much greater difference between normal and abnormal embryos than others. For example, genes involved in the miRNA biogenesis pathway, such as DGCR8, Dicer and TARBP2, showed very low levels of expression in abnormal embryos. Notably, CPEB1 and Symplekin, two of the most severely affected genes, belonging to the same molecular mechanism that regulates the storage of maternal mRNA and reactivation by manipulating the length of the poly (A) transcript tail (Bettegowda, A. et al. (2007 ) Front. Biosci. 12: 3713-3726). These data suggest that the embryo's abnormality correlates with defects in the embryo's mRNA regulation program.
[0183] Correlating cytokinesis with gene expression profiles. Gene expression analysis was performed with genes encoding key components of cytokinesis. The identity of each embryo was tracked through the installation of a camera on the stereomicroscope and video recording of the sample transfer process during the exchange of media and collection of samples. When evaluating the gene expression profiles of abnormal embryos, we observed a strong correlation between abnormal cytokinesis and lower level of gene expression in key components of cytokinesis. Interestingly, the gene expression profiles of abnormal embryos were as diverse and variable as their abnormal morphological phenotypes.
[0184] Gene expression of cytokinesis was found to vary between normal 2-cell embryos and abnormal 2-cell embryos (Fig. 9) and as between normal and abnormal 4-cell embryos (Fig. 10). Figs. 9 and 10 show the relative expressions of the genes that are most highly expressed in normal 2-cell human embryos (Fig. 9) and normal 4-cell embryos (Fig. 10), correlated with different cytokinesis phenotypes. As depicted in Fig. 9, an interrupted 2-cell embryo that showed abnormal membrane wrinkling during the first cytokinesis had significantly reduced mobile expression of all cytokinesis regulatory genes tested. The genes that show differences in Fig. 9 are aniline, cofiline, DIAPH1, DIAPH2, DNM2, ECT2, MKLP2, MYCL2 and RhoA. Normal expression levels are shown in the bars on the right and can be seen as higher in each gene. In the photographs above the graphs in Figure 9, showing abnormal embryos from two cells, the scale bar represents 50 µm. Fig. 10 shows results from an interrupted embryo of 4 cells that went through abnormal cytokinesis with a unilateral cytokinesis groove and extremely prolonged cytokinesis during the first division showed decreased expression in the cytokinesis regulators Aniline and ECT2. The Scale bar in Fig. 10 also represents 50 µm.
[0185] Embryonic stage specific gene expression patterns. Fig. 11 shows four Embryonic Stage Specific Patterns (ESSPs) that were identified during the analysis of gene expression of 141 normally developed simple embryos and simple blastomeres. The genes that fit into each of the four ESSPs are listed in Table 2 (Fig. 20). The graphs in Fig. 11 were created by grouping genes based on similar expression patterns and an average of their expression values (in relation to the reference genes). The relative expression level of an ESSP was calculated by weighting the average expression levels of genes with similar expression patterns. Gene expression levels are plotted against different stages of cells, that is, 1c = a cell; M = morula, B = blastocyst. In fig. 11, the relative expression of genes in each of the four ESSPs is shown as a developmental function, from 1 cell (1c) to morula and blastocyst. ESSP1 shows inheritance materina, ESSP2 shows activation of the transcription of the gene, ESSP3 shows activation of the late stage, and ESSP4 shows persistent transcriptions. As indicated in ESSP2, the typical transfer point in an IVF clinic occurs on day 3, when the embryos undergo significant developmental changes, due to activation of the embryonic gene. Time-lapse imaging data indicates that an embryo's development potential can be identified by the 4-cell stage, thus allowing early embryo transfer on day 2 and before this gene activation. This early transfer is useful for improving the success rate of IVF procedures.
[0186] Table 2 (Fig. 20) lists the genes that belong to each of the four identified ESSPs. The relative gene expression level of each gene was calculated against reference genes (GAPDH and RPLPO) and in relation to the average of the gene. The pattern of expression of each gene against the embryo's development schedule followed by one of the following four ESSPs: Pattern ESSP (1) in early stage: genes that start high, slowly degrade, and turn off before blastocyst, pattern ESSP (2) Intermediate stage: genes that turn into a stage of 4 cells, pattern ESSP (3) late stage: genes that turn into a morula or blastocyst, and pattern ESSP (4) Constant: genes that have relatively constant expression values.
[0187] ESSP1 described the pattern of maternally inherited genes. These transcriptions started with a high level of expression in the zygote phase and subsequently declined as the embryos developed into blastocysts. The half-life of these transcripts was approximately 21 hours. Classical maternal factors of other model organisms, such as GDF9 and ZAR1, as well as spastic genes of germ cells (oocyte) VASA and DAZL were in this category. ESSP2 included the activated embryonic genes, which were first transcribed in the embryos after the 4 cell stage. Some genes in this category appeared to have two activation waves, the first and smallest in the 5 to 6 cell stage, and the second and largest in the 8 cell stage. EGA genes known from other organism models, such as EIF1AX31 and JARID1 B32, fell into this category. ESSP3 was composed of genes activated late that were not expressed until the blastocyst stage, including the trophoblast marker GCM1. ESSP4 contained persistent transcripts that maintained stable expression with respect to a reference gene throughout development. The half-life of such genes was 193 hours, approximately 9 times longer than ESSP1. This category included a mix of housekeeping genes, transcription factors, epigenetic regulators, hormone receptors and others. These 4 patterns of gene expression were confirmed in another set of experiments using 61 samples of simple normal embryos and blastomeres.
[0188] Abnormal embryos exhibit abnormal cytokinetic and abnormal mitotic behavior during the first divisions, correlated with highly irregular gene expression profiles, especially in the genes involved in embryonic RNA management. Thus, one can combine these methodologies to provide methods that can be used to predict the viability of pre-implantation of the embryo. The results suggest that abnormal embryos start life with defective programs in RNA processing and miRNA biogenesis, causing excessive degradation of maternal mRNA. The stochastic nature of such unregulated RNA degradation leads to random destruction of transcripts, causing the wide variety of abnormal phenotypes observed in abnormal embryos. The decreased miRNA level generates defects in the regular degradation of maternal RNA, leading to interruption of development at different stages.
[0189] Analysis of individual blastomer. In order to assess when molecular differentiation started in pre-implantation human embryos, the CDX2 expression level in simple blastomeres harvested from 17 embryos at different stages of development was analyzed. Fig. 12A shows the relative expression level of two genes, CTBBN1 (dark bars) and CDX2 (light bars) as a function of the development stage, from 2 cells to a blastocyst. As can be seen, CDX2 was expressed sporadically at low levels, in some simple embryo blastomeres before the 4 cell stage (Fig. 12A). However, from the 6 cell stage, each embryo contained at least 1 blastomer that expressed CDX2 to a significant level. The expression level of the CTNNB1 housekeeping gene is also shown in fig. 12A remained constant between blastomeres from the same embryo, indicating that the heterogeneous CDX2 expression pattern was not a qPCR artifact. Data from an independent experiment show similar observances. These results indicate that molecular differentiation in pre-implantation human embryos can occur as early as immediately after the 4 cell stage.
[0190] Interestingly, the inspiration of gene expression profiles in simple blastomeres revealed embryos that contained blastomeres with gene expression signatures corresponding to different ages of development. The gene expression profile of any embryo at any given time is equal to the sum of degradation of maternal mRNA and EGA. A younger blastomer at an early age of development generally contains a high amount of maternal transcripts and a low amount of zygotic genes, and the opposite is true for an older blastomer at a more advanced age of development. In this experiment, the material program was defined as the average expression values of 10 ESSP1 markers (maternal transcripts), and the embryonic program by the average expression values of 10 ESSP2 markers (embryonic transcripts). The maternal transcription group used includes DAZL, GDF3, IFITM1, STELLAR, SYCP3, VASA, GDF9, PDCD5, ZAR1 and ZP1, while the embryonic gene group includes ATF7IP, CCNA1, EIF1 AX, EIF4A3, H2AFZ, HSP70,1, JARID1 B, LSM3, PABPC1, and SERTAD1. Among the 6 blastomeres successfully collected from this particular 8-cell embryo, 3 blastomeres showed a genetic signature expression similar to the blastomeres of a normal 3-cell embryo sample, while the other 3 blastomeres were similar to the blastomeres of a sample normal 8 cell embryo (Fig. 12B). The most likely explanation for this observation is the interruption of a sub-population of cells within the embryo. This phenotype of partial interruption was also observed in another embryo of 9 cells and 2 morulas among the tested samples. The fact that the maternal transcriptional level remained high in the interrupted blastomeres, which spent the same amount of time in culture as their normal sister cells, indicates that the degradation of maternal RNA is not a spontaneous process that simply occurs over time. time, but most likely requires the operation of the specific RNA degradation mechanism such as microRNAs (miRNAs). These data also provide additional evidence that degradation of maternal mRNA is a preserved developmental event during mammalian embryogenesis and is necessary for normal embryo development (Bettegowda, A., et al. (2008) Reprod. Fertil. Dev. 20: 45-53). In addition, these data suggest that the individual blastomeres in an embryo are autonomous and can develop independently of each other. In addition, these results indicate that the gene expression level tests described here can be used to test for an mRNA level (which is indicative of gene expression level) in a cell to be tested, where the RNA is from gene known as part of the maternal program, and the persistence of said mobile expression in a late stage of embryonic development is correlated with a probability of abnormal outcome, or part of the embryonic program, in which the absence of time is indicative of a probability abnormal result. The maternal program genes evaluated here are ZAR1, PDCD5, NLRP5, H5F1, GDF9 and BNC2. Other genes of maternal effect are known and can be used.
[0191] Activation of the embryonic gene. The present methods are at least in part based on the findings that abnormal interrupted developmental embryos usually show abnormal cytokinesis and mitotoxic time during the first three divisions before EGA (activation of the embryonic gene) occurs. This suggests that the fate of the embryo's development is largely determined by maternal inheritance, a finding in remarkable terms with a mathematical model of pre-implantation human development carried out by Hardy et al. in 200134. In addition, abnormalities in cytokinesis and mitosis strongly correlate with decreased maternal transcription levels in genes that regulate miRNA biogenesis and maternal mRNA masking, storage and reactivation. miRNAs regulate translation by promoting mRNA degradation in a variety of biological processes, including developing organisms and differentiation (Blakaj, A. & Lin, H. (2008) J. Biol. Chem. 283: 9505-9508; Stefani, G . & Slack, FJ (2008) Nat. Rev. Mol. Cell Biol. 9: 219230). The growing evidence from model organisms shows that miRNAs may be the main regulators of degradation in maternal transcription in early embryos (Bettegowda, A., et al. (2008) Reprod. Fertil. Dev. 20: 45-53). Thus, defects in miRNA biogenesis are likely to lead to abnormal embryo development. On the other hand, the inability to adequately control maternal mRNAs can also cause weak embryogenesis. Mammalian oocytes synthesize a large set of maternal RNA transcripts needed to support early embryo growth before the mother is born. These transcriptions are suppressed and stored for an extended period of time, until they are reactivated after fertilization. Defects in this maternal RNA management program are likely to affect the quantity and quality of maternal transcriptions and thus compromise the chance of successful development.
[0192] Model to assess embryo viability. Fig. 13 shows a model for human embryo development in correlated imaging and molecular analysis. The blastocyst zygote development schedule is shown including critical short times for predicting successful blastocyst development and an embryo development diagram. The main molecular data, as diagrammed, indicate that human embryos start life with a distinct set of oocyte RNAs that are inherited from the mother. This set of RNAs is maintained and packaged appropriately by specific RNA management programs in the egg. After fertilization, the degradation of a subset of maternal egg-specific RNAs (ESSP1; Embrionary Stage Specific Pattern) must be degraded as the transition from oocyte to embryo begins. In parallel, other RNAs are ideally divided equally for each blastomer as development continues (ESSP4). Successful degradation and partitioning of RNAs culminates in activation of the embryonic genome (EGA) and transcription of the ESSP2 genes in an autonomous cell manner. Notably, during cleavage divisions, embryonic blastomeres can be stopped or progress independently. The result of the development of the non-embryo autonomous cell is that individual blastomeres can interrupt or progress and as the embryo of 8 cells progresses to the morula stage and in addition, the quality of the blastocyst will be affected by the number of cells that are interrupted or progress beyond 8 cells. Data imaging demonstrates that there are critical periods of development that predict success or failure: first cytokinesis, the second cleavage division and synchronicity of the second and third cleavage divisions. These parameters can be measured automatically using the cell tracking algorithm and software previously described. The described systems and methods can be used to diagnose embryo results with key imaging predictors and can allow the transfer of smaller embryos early in development (prior to EGA). EXAMPLE 3
[0193] Oocyte imaging in ripening and subsequent embryo development. RESULTS
[0194] One of the main limitations of current procedures is the quality and availability of oocytes. For example, current IVF protocols recruit oocytes from the small clinic, providing a small number of oocytes (for example, 1-20) for fertilization. In addition, approximately 20% of oocytes recovered after hormonal stimulation during IVF procedures are classified as immature, and are typically discarded due to the reduced potential for embryo development under current culture conditions.
[0195] A method of increasing the oocyte pool and through in vitro maturation. Fig. 14 shows three stages of development during in vitro maturation, including germinal vesicle, metaphase I, and metaphase II. The germinal vesicle and the stages of metaphase I are classified as immature oocytes, while metaphase II is classified as mature due to the presence of the first polar body, which occurs in 24-48 hours after the start of maturation in vitro. Fig. 15 shows the development of an oocyte embryo that has matured in vitro.
[0196] Another method to increase the oocyte pool and recruit oocytes from the primary and secondary pool, providing up to several hundred oocytes. In this procedure, dormant cells are recruited from the ovary and programmed in vitro to produce oocytes with normal chromosome composition, epigenetic status, RNA expression, and morphology. In other aspects, oocytes can be derived from pluripotent stem cells differentiated in vitro in germ cells and matured in human oocytes.
[0197] As illustrated in Fig. 14, the process of maturing an oocyte in vitro is marked by various cellular changes that can be used to define cellular parameters for measurement and analysis in the objects of the invention. These include, for example, changes in the morphology of the oocyte membrane, for example, the rate and extent of separation of the pellucid zone; changes in the morphology of the oocyte nucleus, for example, the imminence, completion and rate of breakdown of the germinal vesicle (GVBD); the rate and direction of movement of the granules in the cytoplasm and nucleus; and the movement and extrusion of the first polar body. EXAMPLE 4
[0198] Imaging of stem cell differentiation. RESULTS
[0199] Time-lapse image analysis can also be used to assess the viability, development potential, and outcome of other cell types, such as stem cells, induced pluripotent stem cells (iPSCs), and human embryonic stem cells ( hESCs). The development potential of stem cells can be assessed using time-lapse image analysis to measure changes in morphology during cell development and differentiation (Fig. 17). The differentiated cells can then be analyzed and selected for transplantation in vivo or other use. Various stem cell parameters can be extracted and analyzed from time-lapse image data, such as cytokinesis duration, time between mitosis events, cell size and shape, number of cells, cell movement, division patterns , differentiation, asymmetric division (in which one daughter cell maintains a stem cell while the other differs), symmetrical division (where both daughter cells remain stem cells or both differ), and destination specification (to determine precisely when a stem cell is differentiates).
[0200] The basic formula for stem cell therapy is that undifferentiated stem cells can be grown in vitro, differentiated into typical cell types, and subsequently transplanted into containers for tissue regeneration and / or injured organs. Time-lapse image analysis can be used as a non-invasive, high-performance device to identify stem cells that form non-tumorigenic differentiated progeny capable of integration into mature tissues. Potential applications include the neurological treatment of disorders such as Alzheimer's and Parkinson's, disorders of the vascular system and cttrditictis diseases, muscle disorders and skeletal disorders such as arthritis, autoimmune diseases and cancers, as well as drug discovery by target assessment and new therapies.
[0201] In humans, injured tissues are usually replaced by continuous recruitment and differentiation of stem cells in the body. However, the body's ability to regenerate is reduced with age. An example of this is urinary incontinence that results from sphincter deficiency. Aging is believed to be one of the main causes of sphincter deficiency due to the number of muscle fibers and nerve density decreasing with age. To treat patients with incontinence, iPSCs can be derived from fibroblasts cultured from vaginal wall tissues to produce differentiated muscle cells. These differentiated cells can then be implanted in vivo. Before implantation, time-lapse image analysis can be used to characterize iPSCs with respect to pluripotency, differentiation, methylation and tumorigenicity. Other applications include time-lapse imaging of iPSCs that are derived from skin cells of patients with Parkinson's and differentiated into neurons for transplantation (Fig. 18). EXAMPLE 5
[0202] Validation of imaging parameters through automated analysis
[0203] As evidenced by our time-lapse imaging data, human embryo development is a highly variable process between embryos within a cohort and embryos can exhibit a wide variety of behaviors during cell division. Thus, manual characterization of certain developmental events such as the duration of highly abnormal cytokinesis (Fig. 4) can be subjected to interpretation. To validate our imaging parameters and the ability to systematically predict the formation of a blastocyst, we have developed an algorithm for automatic tracking of cell divisions up to the stage of 4 cells. Our tracking algorithm employs a probabilistic model imaging technique based on Monte Carlo sequential methods. This technique works by generating hypothesis distributions of embryo models, simulating the images based on a simple optical model, and comparing these simulations to the observed image data (Fig. 21a).
[0204] Embryos were modeled as a companion of ellipses with position, orientation and superimposed index (to represent the relative heights of the cells). with these models, the duration of cytokinesis and time between mitosis can be extracted. Cytokinesis is typically defined by the first appearance of the cytokinesis groove (in which polar indentations form near the cleavage axis) for complete separation of daughter cells. We simplified the problem by approaching cytokinesis according to the length of the stretching before cell division from 1 cell to 2. A cell is considered elongated in the axes that exceed 15% (chosen empirically). The time between mitosis is simple to extract by counting the number of cells in each model.
[0205] We tested our algorithm on a set of 14 human embryos (Fig. 21b) and compared the automated measurements for manual image analysis (Fig. 21c, Fig. 21d). In this data set, 8 of the 14 embryos reached the blastocyst stage with good morphology (Fig. 21e superior). Automated measurements were closely related to manual measurements, and all 8 embryos were correctly predicted to reach a blastocyst. 2 of the 14 embryos reached a blastocyst with poor morphology (poor quality of internal cell mass; Fig. 21e inferior). For these embryos, the manual evaluation indicated that 1 could reach a blastocyst and 1 could be interrupted, while the automated evaluation predicted that both would be interrupted. Finally, 4 of the 14 embryos were interrupted for blastocyst stage, and were all correctly predicted to interrupt by both methods.
[0206] Particle Filter Structure
[0207] The particle filter is a model estimation technique based on the Monte Carlo simulation. It is used to estimate unknown or “hidden” models by generating distributions by hypothetical models and comparing these models to the observed data. Its ability to accommodate the dynamics of arbitrary movement and measurement uncertainties make it an ideal candidate for tracking cell divisions.
[0208] The particle filter tracks the propagation of three main variables over time: state x, control u, and measurement z. The variable state x is a model of the embryo we want to estimate and is represented as a collection of ellipses (for 2D) or ellipsoids (for 3D). The control variable u is an input that transforms the state variable and consists of our propagation and division model. The measurement variable z is an observation of the state and consists of our images acquired by the microscopic rhythm lapse. These parameters are described in more detail in the following sections.
[0209] An estimate of the current state x at each time step is represented with a later probability distribution. This posterior is generally referred to as crenga and is defined as the conditional probability of the current stage xt given all measurements of images past zi: t and control past ui: t

[0210] The particle filter approaches the rear with a set of heavy samples, or particles, denoted as:
where M is the number of particles. The terms particulate and embryo models are used interchangeably here. Thus, a simple particle xt [m] (where 1 <= m <= M) and a hypothesis of the embryo model at time t.
[0211] After initialization, the particle filter repeatedly applies three steps: The first step is prediction, in which each particle is propagated using the control input:

[0212] The resulting set of particles is an approximation of the previous probability. The second step is the update measurement, where each particle is assigned a weight of importance corresponding to the probability of the current measurement:

[0213] The set of heavy particles is an approximation of the posterior bel (xt).
[0214] A key component of the particle filter comes in the third step, in which the set of particles is re-sampled according to their weights. This resampling step focuses on the distribution of particles in the most likely region.
[0215] Cellular Representation
[0216] Cells are represented as ellipses in 2D space. Each cell has a main axis, a minor axis, and a two-dimensional position in Cartesian coordinates, given the equation:

[0217] Each ellipse also has a main direction 9 (yaw), which allows it to rotate in the xy plane. Since ellipses almost always overlap with each other, we also denote an overlap index h, which specifies the order of overlap (or the relative height of the cells). The parameters for each embryo model over time are therefore presented as:
where N is the number of cells in a certain model.
[0218] Cell Disorder and Division
[0219] The first stage of the particle filter and forecast, in which each particle is propagated using the control input: For our application, there are two types of behavior that we want to model. This first type of behavior includes cell movement, which includes translation, rotation of the yaw angle, and changes in the length of the main and minor axes. The second type of behavior is cell division, in which the cell divides into two new cells.
[0220] To model cell movement, our control input takes a particle and randomly disturbs each value for each cell: xoi, yoi, ai, bi, 9i. The disturbance is randomly sampled from a normal distribution with relatively small variance (typically adjusted to 5% of the initialized values).
[0221] For cell division model, we use the following approach. At a certain point in time, for each particle, we designate a 50% probability that one of the cells will divide. This value was chosen empirically, and covers a wide range of possible cell divisions, maintaining a good coverage of the current configuration. If a division is foreseen, then the cell in division is chosen at random. A more sophisticated model could take into account additional factors such as the number of cells in a particle and the history of its division patterns, and could potentially create models based on observed behavior from actual data.
[0222] When a cell is chosen to divide, a symmetrical division along the main axis of the ellipse, producing two daughter cells of equal size and shape is applied. Each value for the daughter cells is then randomly disturbed. The disturbance is again sampled from a normal distribution but with a greater variance (10% of the initialized values) to accommodate great variability in the new cell formats. Finally, the overlap indexes of the two daughter cells are randomly selected, maintaining their collective overlap in relation to the rest of the cells.
[0223] Image simulation
[0224] After applying the control input for each particle, the particle representation must be converted into a simulated image that can be compared to the actual images. Simulating image accuracy can be a difficult task, and generally requires the use of ray traceability techniques and optical models. In addition to the attempt to simulate reactive images, the method of the present invention focuses on the simulation characteristics that are easily identifiable in the images. Specifically, images of cell membranes are stimulated.
[0225] There are two physical observations that must be taken into account. First, although the microscope is focused on a single plane through the embryo, the depth of field is quite wide and light out of focus is collected from almost the entire embryo. And second, the embryos are partially transparent, which means that the cell membranes at the bottom of the embryo can sometimes (but not always) be seen through the cells at the top of the embryo.
[0226] With these physical observations in mind, the image simulation model has now been described. For each cell The corresponding pixel values are set to a binary value of 1 and spread out to create a membrane thickness comparable to the observed image data. The overlap index h specifies the order in which the cells are on top of each other. Because occluded cell membranes are only visible from time to time, if occluded points are detected, they are placed in the simulated image with low probability (typically around 10%). In practice, while these occluded membrane points are necessary for precise and important shape modeling to make them sparse enough so that they do not look like a visible edge.
[0227] Pre-Processing Image
[0228] The measurement variable z will now be described. One goal of the method of the present invention is to extract binary images of cell membranes from the microscope images for comparison of the simulated images. These membranes have high curvature and high contrast, but are not easily extracted using intensity or limit techniques based on color. Thus, a detector based on curvature of the principal is employed. This method used the Hessian operator:
where Ixx, Ixy, and Iyy are second order partial derivatives evaluated in pixel location and Gaussian scale. The Hessian 2x2 matrix eigenvalues provides information about the main curvatures, while the eigenvalue sign distinguishes “valleys” from “ridges''43. To detect peaks of lightness or ridges, the primary curvature at each pixel is calculated as
where 12 is the minimum eigenvalue. To detect membranes of varying thickness, the Hessian operator over a range of scales (ie omin <= o <= omax) is applied, and the maximum curvature over this range is extraicd. Finally, the image of Hessian is limiting to create a binary image of extinct cell membranes. The threshold level is typically adjusted to twice the standard deviation of pixel values in Hessian.
[0229] Particle Weights
[0230] As described in the section entitled “Particle Filter Structure,” the second main step of the particle filter is a measurement update, in which the particles are designated with weight corresponding to the probability of the current measurement given a particular model. In our case, the weight of importance is determined by comparing the pre-processed microscope image discussed above, for the stimulated image also discussed above.
[0231] This problem has been investigated previously, in which the particle filter weights were calculated by comparing the simulated images to real images using standardized mutual information. This approach is similar to the idea of combining the occupancy network, which looks for pixel locations that are both occupied (value 1) or both empty (value 0). These methods can be problematic when the simulated and real images are similar in format but slightly misaligned. On the other hand, the method being described uses a probability function based on the chamfered distance, which measures the average value of the closest distances from one point to another. Two sets of points A (in the set of real numbers of size m), and B (in the set of numbers of size n), corresponding to the non-zero pixels in the simulated image and real image, respectively, are defined. The direct chamfer distance from the set of points A to B is given as:

[0232] The distance in reverse chamfer is defined in the same way. The present method employs symmetrical chamfer distance, which provides a measure of how well the simulated image matches the real image, as well as how well the real image matches the simulated image:

[0233] In practice, individual distance measurements are truncated to reduce the influence of speed. To reduce computing time, distances are determined by looking at the pixel locations in the transform distance of the images.
[0234] Chamfered distance is used as a measure of the probability of our data measurement given the estimated model. Or be, at time t, for image measurement zt and a particle model xt [m], the weight of importance of the particle is given as:

[0235] Constant 1 is typically set to 1 and can be varied to control the "flatness" of the probability distribution.
[0236] Resampling of particle and Dynamic Allocation
[0237] The third main step of the particle filter is resampling, where the particles are selected in proportion to their weights to create a new set of particles. Particles with low probability are discarded, while particles with high probability are multiplied. There has been a lot of previous work on the development of efficient resampling algorithms. The present method uses the low variance approach.
[0238] An important issue in particle filters is the choice of the number of particles. The simplest choice is to use a fixed value, say M = 1000. Then, for each time step, the set of particles M is transformed into another set of the same size. In the context of the application, there may be relatively longer periods of time during which the cells are inactive or only slightly changing in size and position. The advantage of this observation is that it takes to reduce the processing load by dynamically allocating the number of particles according to the amount of cellular activity. That is, when the cells are active and divide, we increase the number of particles, and when the cells are inactive, we reduce the number of particles.
[0239] To measure the degree of cell activity, the sum of squares (SSD) differences in pixel intensities between the new image (obtained by the microscope) and the previous image is calculated. To reduce the speed, the images are first smoothed with a Gaussian filter, and the SSD value is smoothed over time with a causal movement average. The number of particles is then dynamically adjusted in proportion to this value and truncated to be within the limits 100 <M <1000. Fig. 30 is a graph showing how the number of particles can be allocated to an embryo that divides from the stage of 1 cell to 4 cells. It should be noted that this method merely provides a measure of the amount of “activity” in the image, but it does not distinguish between cell division and embryo movement (translation and / or rotation) because a previous image registration has not been performed. In this situation (determination of the number of particles) this is acceptable since the number of particles should increase in any event. In practice, we also adjust the number of particles based on the number of cells in the most likely embryo model. That is, more particles are generated when it is believed that more cells are present in the images.
[0240] Two-dimensional Tracking Limitations
[0241] The 2D cell tracking algorithm described above is useful for determining the number of cells in the embryo as well as their 2D forms. However, this is limited by the fact that there is no underlying physical representation. This may or may not be important for automatically tracking cell divisions to assess embryo viability. For example, certain parameters such as the duration of cytokinesis, and the time between cell divisions, can be measured using the 2D cell tracking algorithm. In the next section, we extend our 2D model to 3D. In order to deal with occlusions and ambiguities of depth that arise from estimates of 3D formats of 2D images, geometric restrictions and restrictions in the conservation of cell volume are applied.
[0242] Cellular representation and tracking in three dimensions
[0243] This section describes an algorithm for 3D cell division tracking. Many of the 2D algorithm steps pass through this algorithm, with a few key exceptions. There is a new cell representation for 3D use. The cells are now represented as ellipsoids in 3D space, given by the equation:

[0244] Each ellipsoid also has a tfder 9 address, step y, and a list. Thus, the representation of each model embryo in time is given to you as:

[0245] An important effect of this revised model is that there may be ambiguities associated with interfering 3D shapes in 2D images. For example, a cell that is spherical in shape could look similar to a cell with a major main axis and a major pitch axis. This is not a major concern, as as will be shown later, particle distribution will maintain these multiple hypotheses until sufficient information is available to create a distinction (for example, from an event such as cell division).
[0246] Ellipsoids are considered rigid; that is, deformation is not explicitly modeled. However, we allow a small amount of overlap between neighboring ellipsoids, and in these overlap regions we assume that the cells are flattened against each other. This is an important consideration since it is commonly observed in embryos, and we count on this in the following sections.
[0247] Cell Disturbance and Division
[0248] Our 3D model of cell division and disturbance is similar to the model in Section 4, “Cell Disorder and Division,” with a few exceptions. The 3D format estimate can be used to apply volume conservation. This prevents the cells from growing arbitrarily large, particularly in the z direction. Volume conservation is applied in two situations. First, for cell disturbance, the axes a and b are varied, and calculated so that the volume is conserved for that individual cell. Second, for cell division, the following restriction is applied:
where transcript p denotes a relative cell and subscripts dl and d2 denote the two daughter cells. In practice, we allow a slight violation of these restrictions, leaving the total volume of the embryo floating between plus / minus 5% of the original volume. This is used to compensate for potential inaccuracies in the initial volume estimate.
[0249] When a cell is chosen to divide in 3D, its division is modeled as follows. First, for the single cell chosen, a division along the long axis of the ellipse, which could be a, b, or c depending on the configuration, is applied. The daughter cells are initialized to be equal in size and further spared, taking into account the rotation of the parent cell. Its parameters are then disturbed to cover a wide range of possible configurations, again using a normal distribution with a set of variance for 10% of the initialized values.
[0250] Geometrical Restrictions
[0251] The issues of occlusion and ambiguity of depth are partially mitigated by preserving the volume. However, restrictions on the spatial relationships of neighboring ellipsoids are also necessary. The first restriction is that cells are prohibited from overlapping by more than 20% in radius. For cells that overlap by an acceptable amount, the assumption that they flattened over each other again is made. The particle model being described represents this phenomenon by ignoring the points within the interseging ellipsoids during image simulation. This was empirically motivated and correlates well with physically observed behavior.
[0252] A second constraint that keeps cells in close and imposed proximity. This restriction is directly related to the physical behavior of human embryos, where cells are restricted by a membrane called the pellucid zone. The zone is modeled like a spherical shell and uses this to impose boundary conditions. The radius of the zone is adjusted to 30% greater than the radius of the embryo of 1 cell.
[0253] These restrictions are applied as follows. For each particle at a certain time, a random control input is applied to generate a new particle, as discussed above. If the physical restrictions have been violated, the new particle is discarded and a new random control is applied. If a new particle is not generated after a certain number of attempts, then that particle is discarded.
[0254] Image simulation
[0255] The advantage of dark field illumination, used in the examples, is that cell membranes disperse light more than the interior of cells. This effect is more pronounced in places where the cell membranes are parallel to the optical axis (z axis). Thus, in order to stimulate the images, these places are sought in our 3D models, which are not necessarily located at the ellipsoid equators due to their rotation. The same rules regarding visible and occluded eggs, as discussed above, are then followed.
[0256] 2D example of cell tracking
[0257] This example belongs to automated cell microscopy and uses the algorithm described above for 2D tracking of cell divisions. This model is designed to track the number of cells in the images as well as the 2D contours of the cell membranes. The first step is image acquisition, which motivates the subsequent image simulation and image pre-processing sections. The time-lapse imaging sequences for this example were obtained with a customized inverted Olympus IX-50 microscope with a 10X objective. The microscope is modified for dark field illumination, where a hollow cone of light is focused on the sample by placing a circular opening between the light source and the condensing lens. The objective lens collects light that is dispersed throughout the sample and directly rejects the transmitted light, producing a clear image on a dark background. An advantage of dark field illumination is that cell membranes tend to disperse light more than the interior of the cell, thus improving their contrasts. The microscope is equipped with a heated stage and a customized incubation chamber to allow embryo culture for up to 5 or 6 days. The images were captured at 5 minute intervals by an Olympus digital SLR camera mounted on the IX-50 side door.
[0258] Imaging of embryos started when they were zygotes, or fertilized eggs with a coarse spherical shape. To initialize the particle set, Hessian is thresholded and computed as described in Section 6, “Image preprocessing,” and adjusts a formula to it using least squares. All particles are then initialized with random orientations sampled in a uniform distribution.
[0259] Fig. 31 shows the results of the 2D algorithm for tracking cell divisions from 1 cell to 4 cell stages. The results show that cell membranes are successfully extracted by the algorithm, even for cells towards the bottom that are partially occluded. It should be noted that in most particle filter applications, the best 'simple' model is generally represented as a weighted sum of state parameters of the particle distribution. However, for the results presented here, the particle with the highest probability is presented.
[0260] Example of 3D cell tracking
[0261] Fig. 32 shows two successful applications of the 3D algorithm described above to track from the stage of 1 cell to 4 cells. Fig. 33 is a diagram showing an example of how the particles are distributed during the division of 1 cell into 2 cells (corresponding to the first example shown in Fig. 32). This plot shows the 3D location of the centers of each cell. As the cells begin to divide, the forecasts show an ambiguity in terms of which daughter cell will be on top of the other, but this is resolved within a couple of frames.
[0262] Extracting Forecast Parameters
[0263] Since the embryos were modeled using the methods previously described, certain parameters can be extracted from the models. Typically, the best model or the most likely is used. These parameters include, for example, the duration of the first cytokinesis, the time between the first and second cell divisions, and the time between the second and third cell divisions. The duration of cytokinesis may be approximately by measuring how long a cell model is elongated before separating into two cells. Elongation can be measured by looking at the ratio of the major to minor axes of the ellipse. Other parameters that can be extracted from the models include the time between fertilization and the first cell division, cell shapes and symmetries and division processes, division angles, fragmentation, etc. Parameters can be extracted using the 2D cell tracking algorithm or the 3D cell tracking algorithm.
[0264] Cytokinesis is defined by the first appearance of cytokinesis groove for complete separation of daughter cells. Since our embryo models consist of non-deformable ellipses, identifying the appearance of the cytokinesis groove is a challenging task. One method could allow ellipses to deform, but this results in a more complex tracking problem. Another method could be to look at changes in curvature in the pre-processed microscope image; however, this negates the purpose of mooring to measure our predictive parameters directly from embryo models. Thus, we simplified the problem by approximating the duration of the first cytokinesis according to the duration of the cell elongation before dividing 1 cell into 2 cells. The elongation is quantified by calculating the proportion of the main axis to a minor axis b of the ellipse. A cell is considered elongated if:

[0265] This 15% value was chosen empirically and works for this particular data set; however, other values can be used. Once an embryo model has been divided into 2 cells, we can extract the approximate duration of the first cytokinesis by calculating the elongation duration for the 1 cell model.
[0266] In principle, measuring time between mitosis events and simple. For example, the time between the first and second mitosis can be measured as the time between the 2 cell model and the 3 cell model. However, in some cases, embryos may exhibit unusual and random behavior. This includes, for example, an embryo that changes from 1 cell to 2 cells, from 2 cells to an apparent 3 or 4 cells, and then back to 2 cells. The described algorithm is capable of tracking this type of behavior, but it presents a challenge for determining the time interval between mitosis events.
[0267] One way to deal with this behavior is as follows: Instead of measuring the time between a 2-cell model and a 3-cell model (to find the time between the first and second mitoses), this can be approximated by simple counting the number of image frames in which a 2 cell model is more likely. This works well in some cases, but it is not always representative of the real time between mitosis events. These events can also be dealt with by applying a restriction to models based on the number of cells. That is, when choosing the best or most likely model of distribution in each iteration, it may be that the number of cells in the model is always the same or increases, but never decreases. After applying this restriction, it is simple to calculate the time between mitosis events. This restriction is also useful for filtering the tracking results which may show small amounts of vibrations, which may occasionally occur when a model switches back and forth between a 1 cell and 2 cell model, for example.
[0268] Method to Extract Forecast Parameters
[0269] Fig. 35 shows a flow chart that summarizes the methods described above. The flowchart shows how a single embryo can be analyzed (although this can be applied to multiple embryos or other types of cells and stem cells). In the first stage, an image of an embryo is obtained with a time-lapse microscope ("measurement"). This image can be saved to a file and opened later. The image is usually pre-processed to increase certain characteristics, although this is not necessary. Models of possible embryo configurations, and images are simulated from these models ("forecast"). The simulated image includes images of cell membranes, as previously described, or images that more accurately represent the microscope images before pre-processing. The models are then compared to the pre-processed microscope image (“comparison”). Using this comparison, the best forecast is maintained, while the worst forecast is discarded. The resulting set of forecasts is then used for the next image. After performing this process for multiple sequential images, it is possible to measure morphological parameters directly from the best model, such as, for example, the duration of cytokinesis and the time between mitosis events. These parameters can be used to assess embryo viability, as previously discussed. EXAMPLE 7
[0270] Automated analysis of cellular activity
[0271] The methods described above require the ability to track cell development through microscopy. For embryos, it is desirable to track multiple embryos, which are being grown together on the same plate. The anaHatic methods used here require that images be taken periodically (for example, every 1-30 minutes for 1-5 days for embryos; different time intervals can be used for other cell types such as stem cells). An imaging method was therefore designed to automatically track the development of the embryo.
[0272] In time-lapse microscopy, cells grow under controlled and imaged conditions over an extended period of time to monitor processes such as motility (movement within the environment), proliferation (growth and division), and changes in morphology ( size and shape). Due to the duration of the experiments and the vast amounts of image data generated, extracting parameters such as the duration and time between cell divisions can be a tedious task. This is particularly true for high performance applications where multiple samples are imaged simultaneously. Thus, there is a need for image analysis software that can extract the desired information automatically.
[0273] A way to assess the viability of the embryo and measure the amount of “cell activity” in the images. This can be achieved by simply taking sequential pairs of images and comparing them to their pixel values. More specifically, to measure the amount of cell activity for each new image, the sum of squared differences (SSD) in pixel intensities is calculated between the new image, denoted as I ', and the previous image, denoted as I ', over all overlapping pixels i:

[0274] To reduce the rddo, images can first be smoothed with a Gaussian filter. Fig. 28 shows a plot of cell activity from 1 to day 3 for a single embryo. As shown, there are multiple spikes corresponding to the division of 1 cell into 2 cells, the division of 2 cells to 4 cells, and the division of 4 cells to 8 cells in a human embryo. Peak widths are representative of cell division times.
[0275] One of the limitations of this approach is that the SSD metrics only measure the amount of activity in the image, and events such as embryo movement (such as displacement or rotation) can look very similar to cell division. One solution to this problem is to perform an image registration before calculating the SSD. Image registration is the process of finding a geometric relationship between two images to align them in the same coordinate system, and can be accomplished using a variety of different techniques. For example, a Levenberg-Marquardt iterative non-linear routine variation can be used, which records images minimizing the SSD in the overlapping pixel intensities. LM algorithm transforms the pixel locations using a 3x3 homography matrix:
where pixel target locations x 'and y' are normalized as:
[0276] So:

[0277] The homography matrix can be applied to a variety of image transformations, and a reasonable choice in this application could be rigid body (Euclidean) transformations. This could align the images of the embryos in translation in plane rotation (along with the camera axis). However, it is possible to generalize slightly and use a related transformation, which allows the image to be tilted. This generalization may or may not be desirable depending on the signal that is trying to be measured. The equations of motion thus become:

[0278] The first LM algorithm calculates the partial derivatives of and with respect to the unknown motion parameters hk using the chain rule:

[0279] For the parameters of related movements, these partial derivatives become:

[0280] Then, using these partial derivatives, the LM algorithm computes the approximate matrix of Hessian A (in the set of real numbers of size 6x6) and weighted gradient vector b (in the set of real numbers of size 6x1) added to the contribution of each pixel:

[0281] Finally, the movement parameters can be updated by adding incremental movement:
where constant 1 regulates the size of the movement update step and I is the identity matrix.
[0282] In each iteration of the algorithm, the first image is deformed according to the updated movement estimate and compared to the second image by SSD computation of pixel intensities in overlapping areas. The present application assumes that the movement of the embryo between consecutive images is very small, and therefore only a small fixed number of iterations are performed. Fig. 28B shows a cell activity plot without (28A) and (28B) image records made for each pair of images. Since the error function of the Levenberg-Marquardt routine is the SSD, one simply plots the residual error for each record. Fig. 29 compares cell activity plots for normal and abnormal embryo development. On day 3, the point at which an embryologist could typically assess morphology, the embryos look similar and could potentially both be considered viable. However, their cell activity plots are drastically different, as one embryo passes through a typical cell division while the other divides from an embryo of 1 cell into multiple cells and fragments. As expected, the embryo has a normal activity plot, which ultimately reaches a blastocyst by day 5.5.
[0283] Other types of image registration can be used before calculating the SSD at pixel intensities. This includes, for example, cross-correlation, normalized cross-correlation, cross-phase correlation, mutual information, feature detection and tracking, transformation of scale invariant feature (SIFT), optical flow, and downward gradient. Image pre-processing may or may not be desirable before registration, as a feature or contrast enhancement.
[0284] Model to assess embryo viability.
[0285] Fig. 13 shows a model for human embryo development in correlated imaging and molecular analysis. The blastocyst zygote development schedule is shown including critical short times for predicting successful blastocyst development and an embryo development diagram. The main molecular data, as diagrammed, indicate that human embryos start life with a distinct set of oocyte RNAs that are inherited from the mother. This set of RNAs is maintained and packaged appropriately by special RNA management programs in the egg. After fertilization, the degradation of a subset of spherical maternal RNAs for the egg (ESSP1; Embrionary Stage Spherical Pattern) must be degraded as the transition from oocyte to embryo begins. In parallel, other RNAs are ideally divided equally for each blastomer as development continues (ESSP4). Successful degradation and partitioning of RNAs culminates in activation of the embryonic genome (EGA) and transcription of the ESSP2 genes in an autonomous cell manner. Notably, during cleavage divisions, embryonic blastomeres can be stopped or progress independently. The result of the development of the non-embryo autonomous cell is that individual blastomeres can interrupt or progress and as the embryo of 8 cells progresses to the morula stage and in addition, the quality of the blastocyst will be affected by the number of cells that are interrupted or progress beyond 8 cells. Data imaging demonstrates that there are critical periods of development that predict success or failure: first cytokinesis, the second cleavage division and synchronicity of the second and third cleavage divisions. These parameters can be measured automatically using the cell tracking algorithm and software previously described. The described systems and methods can be used to diagnose embryo results with key imaging predictors and can allow the transfer of smaller embryos early in development (prior to EGA). Comparison of automated vs. image analysis manual
[0286] Fig. 34 shows a comparison of automated image analysis for manual image analysis for a set of 14 embryos. Embryos 1 to 10 (as labeled in the plots) reached the blastocyst stage with varying morphology. Embryos 11 to 14 interrupted and that did not reach blastocyst. Fig. 34A shows the comparison for measuring the duration of the first cytokinesis, and Fig. 34B shows the comparison for measuring the time between 1st and 2nd mitosis. As shown, the two methods show good agreement in general. Small amounts of discrepancy for the duration of the first cytokinesis are expected, as can be attributed to the fact that our automated analyzes do an approximation when measuring the stretch, as previously discussed. In some cases, there is a greater disagreement between automated and manual analysis for both the duration of cytokinesis as well as the time between 1st and 2nd mitosis. This occurs for some of the abnormal embryos, and is caused by unusual behavior that is difficult to characterize both manually and automatically. For this group of embryos, and using just the first two criteria (duration of the first cytokinesis and time between 1st and 2nd mitosis), the automated algorithm has zero false positives. This could be extremely important in an IVF procedure where false positives are to be avoided. The manual image analysis had a false negative (embryo 9), while the automated algorithm had two false negatives (embryos 9 and 10). However, while both embryos 9 and 10 technically reached the blastocyst stage, they showed poor morphology compared to other blastocysts and could be less optimal candidates for transfer. For manual image analysis, embryo 14 could be a false positive based on these two criteria, and the third parameter of duration between 2nd and 3rd mitosis is necessary to generate a true negative. However, the automated algorithm takes the correct forecast using only the first two criteria. These results indicate that our automated algorithm can successfully predict blastocyst vs. non-blastocyst as well as differentiating between different qualities of blastocyst. Thus, for situations when multiple embryos are determined to have good potential for development, it is possible to calculate a classification of their relative qualities, to select the top 1 or 2 embryos to transfer during IVF procedures.
[0287] The foregoing merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to design various arrangements, although not explicitly described or shown here, carry out the principles of the invention and are included within its scope and scope. In addition, all the examples and conditional languages recited here are primarily intended to assist in understanding the principles of the invention and the concepts contributed by the inventors to promote the technique, and are interpreted as being without limitation to said specifically recited examples and conditions. In addition, all statements that indicate the main elements, aspects and modalities of the invention, as well as specific examples thereof, include both equivalent structures and functionalities thereof. In addition, it is understood that said equivalents include both known equivalents and equivalents developed in the future, that is, any developed element that performs the same function, regardless of the structure. The scope of the present invention, therefore, is not intended to be limited to the exemplary modalities and described herein. On the contrary, the scope and spirit of the present invention is accomplished by the appended claims.

权利要求:
Claims (8)
[0001]
1. Method for selecting one or more human embryos that are likely to reach the blastocyst stage, characterized by understanding the steps of: - cultivating one or more human embryos in conditions sufficient for embryo development; - perform time-lapse imaging of said one or more embryos during at least one event of cytokinesis or cell cycle; - measuring at least one cell parameter comprising: (a) the duration of the first cytokinesis; or (b) the time between the first and the second mitosis; or (c) the time between the second and third mitosis; and - selecting an embryo when said at least one cell parameter is: (i) a duration of the first cytokinesis that is from 0 minutes to 33 minutes; or (ii) a time interval between the first and second mitosis, which is 7.8 to 14.3 hours; or (iii) a time interval between the second and third mitosis, which is from 0 to 5.8 hours; - then select an embryo that is likely to reach the blastocyst stage.
[0002]
2. Method, according to claim 1, characterized by comprising the steps of: - measuring: (a) the duration of the first cytokinesis; and (b) the time between the first and the second mitosis; and - select an embryo when: (i) the duration of the first cytokinesis is 0 minutes to 33 minutes; and (ii) the time interval between the first and second mitosis is 7.8 to 14.3 hours.
[0003]
3. Method, according to claim 1, characterized by comprising the steps of: - measuring: (a) the duration of the first cytokinesis; and (c) the time between the second and third mitosis; and - select an embryo when: (i) the duration of the first cytokinesis is 0 minutes to 33 minutes; and (iii) the time interval between the second and third mitosis is 0 to 5.8 hours.
[0004]
4. Method, according to claim 1, characterized by comprising the steps of: - measuring: (b) the time between the first and the second mitosis; and (c) the time between the second and third mitosis; and - select an embryo when: (ii) the time interval between the first and second mitosis is 7.8 to 14.3 hours; and (iii) the time interval between the second and third mitosis is 0 to 5.8 hours.
[0005]
5. Method, according to claim 1, characterized by comprising the steps of: - measuring: (a) the duration of the first cytokinesis; and (b) the time between the first and the second mitosis; and (c) the time between the second and third mitosis; and - select an embryo when: (i) the duration of the first cytokinesis is 0 minutes to 33 minutes; and (ii) the time interval between the first and second mitosis is 7.8 to 14.3 hours; and (iii) the time interval between the second and third mitosis is 0 to 5.8 hours.
[0006]
6. Method, according to claim 1, characterized by comprising the measurement of the duration of the first cytokinesis and selection of an embryo when the duration of the first cytokinesis is 0 minutes to 33 minutes.
[0007]
7. Method, according to claim 1, characterized by comprising the measurement of the time between the first and the second mitosis and selection of an embryo when the time interval between the first and the second mitosis is 7.8 to 14.3 hours.
[0008]
8. Method, according to claim 1, characterized by comprising the measurement of time between the second and third mitosis and selection of an embryo when the time interval between the second and third mitosis is 0 to 5.8 hours.

类似技术:

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BR112012003847B1|2020-12-01|method for selecting one or more human embryos that are likely to reach the blastocyst stage

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法律状态:
2018-04-10| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2019-07-02| B07A| Application suspended after technical examination (opinion) [chapter 7.1 patent gazette]|

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2019-10-15| B25G| Requested change of headquarter approved|Owner name: THE BOARD OF TRUSTEES OF THE LELAND STANDFORD JUNI Owner name: THE BOARD OF TRUSTEES OF THE LELAND STANDFORD JUNIOR UNIVERSITY (US) |

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2020-03-10| B06A| Patent application procedure suspended [chapter 6.1 patent gazette]|

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2020-08-18| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2020-12-01| B16A| Patent or certificate of addition of invention granted [chapter 16.1 patent gazette]|Free format text: PRAZO DE VALIDADE: 10 (DEZ) ANOS CONTADOS A PARTIR DE 01/12/2020, OBSERVADAS AS CONDICOES LEGAIS. |

优先权:

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申请号 | 申请日 | 专利标题

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US23608509P| true| 2009-08-22|2009-08-22|

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US61/236,085|2009-08-22|

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