Intercellular contact and cargo transfer between Müller glia and to microglia precede apoptotic cell clearance in the developing retina.

To clarify our understanding of glial phagocytosis in retinal development, we used real-time imaging of larval zebrafish to provide cell-type specific resolution of this process. We show that radial Müller glia frequently participate in microglial phagocytosis while also completing a subset of phagocytic events. Müller glia actively engage with dying cells through initial target cell contact and phagocytic cup formation, after which an exchange of the dying cell from Müller glia to microglia often takes place. In addition, we find evidence that Müller glia cellular material, possibly from the initial Müller cell phagocytic cup, is internalized into microglial compartments. Previously undescribed Müller cell behaviors were seen, including cargo splitting, wrestling for targets and lateral passing of cargo to neighbors. Collectively, our work provides new insight into glial functions and intercellular interactions, which will allow future work to understand these behaviors on a molecular level.

SPIRO - the automated Petri plate imaging platform designed by biologists, for biologists.

Phenotyping of model organisms grown on Petri plates is often carried out manually, despite the procedures being time-consuming and laborious. The main reason for this is the limited availability of automated phenotyping facilities, whereas constructing a custom automated solution can be a daunting task for biologists. Here, we describe SPIRO, the Smart Plate Imaging Robot, an automated platform that acquires time-lapse photographs of up to four vertically oriented Petri plates in a single experiment, corresponding to 192 seedlings for a typical root growth assay and up to 2500 seeds for a germination assay. SPIRO is catered specifically to biologists' needs, requiring no engineering or programming expertise for assembly and operation. Its small footprint is optimized for standard incubators, the inbuilt green LED enables imaging under dark conditions, and remote control provides access to the data without interfering with sample growth. SPIRO's excellent image quality is suitable for automated image processing, which we demonstrate on the example of seed germination and root growth assays. Furthermore, the robot can be easily customized for specific uses, as all information about SPIRO is released under open-source licenses. Importantly, uninterrupted imaging allows considerably more precise assessment of seed germination parameters and root growth rates compared with manual assays. Moreover, SPIRO enables previously technically challenging assays such as phenotyping in the dark. We illustrate the benefits of SPIRO in proof-of-concept experiments which yielded a novel insight on the interplay between autophagy, nitrogen sensing, and photoblastic response.

Machine learning in time-lapse imaging to differentiate embryos from young vs old mice†.

Time-lapse microscopy for embryos is a non-invasive technology used to characterize early embryo development. This study employs time-lapse microscopy and machine learning to elucidate changes in embryonic growth kinetics with maternal aging. We analyzed morphokinetic parameters of embryos from young and aged C57BL6/NJ mice via continuous imaging. Our findings show that aged embryos accelerated through cleavage stages (from 5-cells) to morula compared to younger counterparts, with no significant differences observed in later stages of blastulation. Unsupervised machine learning identified two distinct clusters comprising of embryos from aged or young donors. Moreover, in supervised learning, the extreme gradient boosting algorithm successfully predicted the age-related phenotype with 0.78 accuracy, 0.81 precision, and 0.83 recall following hyperparameter tuning. These results highlight two main scientific insights: maternal aging affects embryonic development pace, and artificial intelligence can differentiate between embryos from aged and young maternal mice by a non-invasive approach. Thus, machine learning can be used to identify morphokinetics phenotypes for further studies. This study has potential for future applications in selecting human embryos for embryo transfer, without or in complement with preimplantation genetic testing.

Testing an artificial intelligence algorithm to predict fetal heartbeat of vitrified-warmed blastocysts from a single image: predictive ability in different settings.

STUDY QUESTION: Could an artificial intelligence (AI) algorithm predict fetal heartbeat from images of vitrified-warmed embryos? SUMMARY ANSWER: Applying AI to vitrified-warmed blastocysts may help predict which ones will result in implantation failure early enough to thaw another. WHAT IS KNOWN ALREADY: The application of AI in the field of embryology has already proven effective in assessing the quality of fresh embryos. Therefore, it could also be useful to predict the outcome of frozen embryo transfers, some of which do not recover their pre-vitrification volume, collapse, or degenerate after warming without prior evidence. STUDY DESIGN, SIZE, DURATION: This retrospective cohort study included 1109 embryos from 792 patients. Of these, 568 were vitrified blastocysts cultured in time-lapse systems in the period between warming and transfer, from February 2022 to July 2023. The other 541 were fresh-transferred blastocysts serving as controls. PARTICIPANTS/MATERIALS, SETTING, METHODS: Four types of time-lapse images were collected: last frame of development of 541 fresh-transferred blastocysts (FTi), last frame of 467 blastocysts to be vitrified (PVi), first frame post-warming of 568 vitrified embryos (PW1i), and last frame post-warming of 568 vitrified embryos (PW2i). After providing the images to the AI algorithm, the returned scores were compared with the conventional morphology and fetal heartbeat outcomes of the transferred embryos (n = 1098). The contribution of the AI score to fetal heartbeat was analyzed by multivariate logistic regression in different patient populations, and the predictive ability of the models was measured by calculating the area under the receiver-operating characteristic curve (ROC-AUC). MAIN RESULTS AND THE ROLE OF CHANCE: Fetal heartbeat rate was related to AI score from FTi (P < 0.001), PW1i (P < 0.05), and PW2i (P < 0.001) images. The contribution of AI score to fetal heartbeat was significant in the oocyte donation program for PW2i (odds ratio (OR)=1.13; 95% CI [1.04-1.23]; P < 0.01), and in cycles with autologous oocytes for PW1i (OR = 1.18; 95% CI [1.01-1.38]; P < 0.05) and PW2i (OR = 1.15; 95% CI [1.02-1.30]; P < 0.05), but was not significantly associated with fetal heartbeat in genetically analyzed embryos. AI scores from the four groups of images varied according to morphological category (P < 0.001). The PW2i score differed in collapsed, non-re-expanded, or non-viable embryos compared to normal/viable embryos (P < 0.001). The predictability of the AI score was optimal at a post-warming incubation time of 3.3-4 h (AUC = 0.673). LIMITATIONS, REASONS FOR CAUTION: The algorithm was designed to assess fresh embryos prior to vitrification, but not thawed ones, so this study should be considered an external trial. WIDER IMPLICATIONS OF THE FINDINGS: The application of predictive software in the management of frozen embryo transfers may be a useful tool for embryologists, reducing the cancellation rates of cycles in which the blastocyst does not recover from vitrification. Specifically, the algorithm tested in this research could be used to evaluate thawed embryos both in clinics with time-lapse systems and in those with conventional incubators only, as just a single photo is required. STUDY FUNDING/COMPETING INTERESTS: This study was supported by the Regional Ministry of Innovation, Universities, Science and Digital Society of the Valencian Community (CIACIF/2021/019) and by Instituto de Salud Carlos III (PI21/00283), and co-funded by European Union (ERDF, 'A way to make Europe'). M.M. received personal fees in the last 5 years as honoraria for lectures from Merck, Vitrolife, MSD, Ferring, AIVF, Theramex, Gedeon Richter, Genea Biomedx, and Life Whisperer. There are no other competing interests. TRIAL REGISTRATION NUMBER: N/A.

The density of the inner cell mass is a new indicator of the quality of a human blastocyst: a valid supplement to the Gardner scoring system.

STUDY QUESTION: Can the density of the inner cell mass (ICM) be a new indicator of the quality of the human blastocyst? SUMMARY ANSWER: The densification index (DI) developed in this study can quantify ICM density and provide positive guidance for ploidy, pregnancy, and live birth. WHAT IS KNOWN ALREADY: In evaluating the quality of ICM, reproductive care clinics still use size indicators without further evaluation. The main disadvantage of this current method is that the evaluation of blastocyst ICM is relatively rough and cannot meet the needs of clinical embryologists, especially when multiple blastocysts have the same ICM score, which makes them difficult to evaluate further. STUDY DESIGN, SIZE, DURATION: This observational study included data from 2272 blastocysts in 1991 frozen-thawed embryo transfer (FET) cycles between January 2018 to November 2021 and 1105 blastocysts in 430 preimplantation genetic testing cycles between January 2019 and February 2023. PARTICIPANTS/MATERIALS, SETTING, METHODS: FET, ICSI, blastocyst culture, trophectoderm biopsy, time-lapse (TL) monitoring, and next-generation sequencing were performed. After preliminary sample size selection, the 11 focal plane images captured by the TL system were normalized and the spatial frequency was used to construct the DI of the ICM. MAIN RESULTS AND THE ROLE OF CHANCE: This study successfully constructed a quantitative indicator DI that can reflect the degree of ICM density in terms of fusion and texture features. The higher the DI value, the better the density of the blastocyst ICM, and the higher the chances that the blastocyst was euploid (P < 0.001) and that pregnancy (P < 0.001) and live birth (P = 0.005) were reached. In blastocysts with ICM graded B and blastocysts graded 4BB, DI was also positively associated with ploidy, pregnancy, and live birth (P < 0.05). ROC analysis showed that combining the Gardner scoring system with DI can more effectively predict pregnancy and live births, when compared to using the Gardner scoring system alone. LIMITATIONS, REASONS FOR CAUTION: Accurate calculation of the DI value places high demands on image quality, requiring manual selection of the clearest focal plane and exposure control. Images with the ICM not completely within the field of view cannot be used. The association between the density of ICM and chromosomal mosaicism was not evaluated. The associations between the density of ICM and different assisted reproductive technologies and different culture conditions in embryo laboratories were also not evaluated. Prospective studies are needed to further investigate the impact of ICM density on clinical outcomes. WIDER IMPLICATIONS OF THE FINDINGS: ICM density assessment is a new direction in blastocyst assessment. This study explores new ways of assessing blastocyst ICM density and develops quantitative indicators and a corresponding qualitative evaluation scheme for ICM density. The DI of the blastocyst ICM developed in this study is easy to calculate and requires only TL equipment and image processing, providing positive guidance for clinical outcomes. The qualitative evaluation scheme of ICM density can assist embryologists without TL equipment to manually evaluate ICM density. ICM density is a simple indicator that can be used in practice and is a good complement to the blastocyst scoring systems currently used in most centers. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Key Research & Development Program of China (2021YFC2700603). The authors report no financial or commercial conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts? SUMMARY ANSWER: Generative AI models exhibit the capability to generate high-fidelity human blastocyst images, thereby providing substantial training datasets crucial for the development of robust AI models. WHAT IS KNOWN ALREADY: The integration of AI into IVF procedures holds the potential to enhance objectivity and automate embryo selection for transfer. However, the effectiveness of AI is limited by data scarcity and ethical concerns related to patient data privacy. Generative adversarial networks (GAN) have emerged as a promising approach to alleviate data limitations by generating synthetic data that closely approximate real images. STUDY DESIGN, SIZE, DURATION: Blastocyst images were included as training data from a public dataset of time-lapse microscopy (TLM) videos (n = 136). A style-based GAN was fine-tuned as the generative model. PARTICIPANTS/MATERIALS, SETTING, METHODS: We curated a total of 972 blastocyst images as training data, where frames were captured within the time window of 110-120 h post-insemination at 1-h intervals from TLM videos. We configured the style-based GAN model with data augmentation (AUG) and pretrained weights (Pretrained-T: with translation equivariance; Pretrained-R: with translation and rotation equivariance) to compare their optimization on image synthesis. We then applied quantitative metrics including Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) to assess the quality and fidelity of the generated images. Subsequently, we evaluated qualitative performance by measuring the intelligence behavior of the model through the visual Turing test. To this end, 60 individuals with diverse backgrounds and expertise in clinical embryology and IVF evaluated the quality of synthetic embryo images. MAIN RESULTS AND THE ROLE OF CHANCE: During the training process, we observed consistent improvement of image quality that was measured by FID and KID scores. Pretrained and AUG + Pretrained initiated with remarkably lower FID and KID values compared to both Baseline and AUG + Baseline models. Following 5000 training iterations, the AUG + Pretrained-R model showed the highest performance of the evaluated five configurations with FID and KID scores of 15.2 and 0.004, respectively. Subsequently, we carried out the visual Turing test, such that IVF embryologists, IVF laboratory technicians, and non-experts evaluated the synthetic blastocyst-stage embryo images and obtained similar performance in specificity with marginal differences in accuracy and sensitivity. LIMITATIONS, REASONS FOR CAUTION: In this study, we primarily focused the training data on blastocyst images as IVF embryos are primarily assessed in blastocyst stage. However, generation of an array of images in different preimplantation stages offers further insights into the development of preimplantation embryos and IVF success. In addition, we resized training images to a resolution of 256 × 256 pixels to moderate the computational costs of training the style-based GAN models. Further research is needed to involve a more extensive and diverse dataset from the formation of the zygote to the blastocyst stage, e.g. video generation, and the use of improved image resolution to facilitate the development of comprehensive AI algorithms and to produce higher-quality images. WIDER IMPLICATIONS OF THE FINDINGS: Generative AI models hold promising potential in generating high-fidelity human blastocyst images, which allows the development of robust AI models as it can provide sufficient training datasets while safeguarding patient data privacy. Additionally, this may help to produce sufficient embryo imaging training data with different (rare) abnormal features, such as embryonic arrest, tripolar cell division to avoid class imbalances and reach to even datasets. Thus, generative models may offer a compelling opportunity to transform embryo selection procedures and substantially enhance IVF outcomes. STUDY FUNDING/COMPETING INTEREST(S): This study was supported by a Horizon 2020 innovation grant (ERIN, grant no. EU952516) and a Horizon Europe grant (NESTOR, grant no. 101120075) of the European Commission to A.S. and M.Z.E., the Estonian Research Council (grant no. PRG1076) to A.S., and the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+) to M.Z.E. TRIAL REGISTRATION NUMBER: Not applicable.

Deep learning to extract the meteorological by-catch of wildlife cameras.

Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro-scales, and deep learning tools rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, ecologically relevant meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africa's Maloti-Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. We achieve 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. For two-class weather classification (overcast vs. sunshine) in a novel location in Svalbard, Norway, we achieve 79.3% accuracy (93.9% consensus accuracy), outperforming a benchmark model from the computer vision literature (75.5% accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabelled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open-top chambers shortens early snow events in autumn, and (2) image-derived sunshine marginally outperforms sensor-derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras.

Multiple collapses of blastocysts after full blastocyst formation is an independent risk factor for aneuploidy - a study based on AI and manual validation.

BACKGROUND: The occurrence of blastocyst collapse may become an indicator of preimplantation embryo quality assessment. It has been reported that collapsing blastocysts can lead to higher rates of aneuploidy and poorer clinical outcomes, but more large-scale studies are needed to explore this relationship. This study explored the characteristics of blastocyst collapse identified and quantified by artificial intelligence and explored the associations between blastocyst collapse and embryo ploidy, morphological quality, and clinical outcomes. METHODS: This observational study included data from 3288 biopsied blastocysts in 1071 time-lapse preimplantation genetic testing cycles performed between January 2019 and February 2023 at a single academic fertility center. All transferred blastocysts are euploid blastocysts. The artificial intelligence recognized blastocyst collapse in time-lapse microscopy videos and then registered the collapsing times, and the start time, the recovery duration, the shrinkage percentage of each collapse. The effects of blastocyst collapse and embryo ploidy, pregnancy, live birth, miscarriage, and embryo quality were studied using available data from 1196 euploid embryos and 1300 aneuploid embryos. RESULTS: 5.6% of blastocysts collapsed at least once only before the full blastocyst formation (tB), 19.4% collapsed at least once only after tB, and 3.1% collapsed both before and after tB. Multiple collapses of blastocysts after tB (times ≥ 2) are associated with higher aneuploid rates (54.6%, P > 0.05; 70.5%, P < 0.001; 72.5%, P = 0.004; and 71.4%, P = 0.049 in blastocysts collapsed 1, 2, 3 or ≥ 4 times), which remained significant after adjustment for confounders (OR = 2.597, 95% CI 1.464-4.607, P = 0.001). Analysis of the aneuploid embryos showed a higher ratio of collapses and multiple collapses after tB in monosomies and embryos with subchromosomal deletion of segmental nature (P < 0.001). Blastocyst collapse was associated with delayed embryonic development and declined blastocyst quality. There is no significant difference in pregnancy and live birth rates between collapsing and non-collapsing blastocysts. CONCLUSIONS: Blastocyst collapse is common during blastocyst development. This study underlined that multiple blastocyst collapses after tB may be an independent risk factor for aneuploidy which should be taken into account by clinicians and embryologists when selecting blastocysts for transfer.

Enhancing clinical utility: deep learning-based embryo scoring model for non-invasive aneuploidy prediction.

BACKGROUND: The best method for selecting embryos ploidy is preimplantation genetic testing for aneuploidies (PGT-A). However, it takes more labour, money, and experience. As such, more approachable, non- invasive techniques were still needed. Analyses driven by artificial intelligence have been presented recently to automate and objectify picture assessments. METHODS: In present retrospective study, a total of 3448 biopsied blastocysts from 979 Time-lapse (TL)-PGT cycles were retrospectively analyzed. The "intelligent data analysis (iDA) Score" as a deep learning algorithm was used in TL incubators and assigned each blastocyst with a score between 1.0 and 9.9. RESULTS: Significant differences were observed in iDAScore among blastocysts with different ploidy. Additionally, multivariate logistic regression analysis showed that higher scores were significantly correlated with euploidy (p < 0.001). The Area Under the Curve (AUC) of iDAScore alone for predicting euploidy embryo is 0.612, but rose to 0.688 by adding clinical and embryonic characteristics. CONCLUSIONS: This study provided additional information to strengthen the clinical applicability of iDAScore. This may provide a non-invasive and inexpensive alternative for patients who have no available blastocyst for biopsy or who are economically disadvantaged. However, the accuracy of embryo ploidy is still dependent on the results of next-generation sequencing technology (NGS) analysis.

Assessment of artificial intelligence model and manual morphokinetic annotation system as embryo grading methods for successful live birth prediction: a retrospective monocentric study.

PURPOSE: The introduction of the time-lapse monitoring system (TMS) and the development of predictive algorithms could contribute to the optimal embryos selection for transfer. Therefore, the present study aims at investigating the efficiency of KIDScore and iDAScore systems for blastocyst stage embryos in predicting live birth events. METHODS: The present retrospective study was conducted in a private IVF Unit setting throughout a 10-month period from October 2021 to July 2022, and included the analysis of 429 embryos deriving from 91 IVF/ICSI cycles conducted due to infertility of various etiologies. Embryos incubated at the Embryoscope+ timelapse incubator were analyzed through the established scoring systems: KIDScore and iDAScore®. The main outcome measure was the comparison of the two scoring systems in terms of live birth prediction. Embryos with the higher scores at day 5 (KID5 score/iDA5 score) were transferred or cryopreserved for later use. RESULTS: Embryos with high KID5 and iDA5 scores positively correlated with the probability of successful live birth, with KID5 score yielding a higher efficiency in predicting a successful reproductive outcome compared to a proportionally high iDA5 score. KID5 demonstrated conservative performance in successfully predicting live birth compared to iDA5 score, indicating that an efficient prediction can be either provided by a relatively lower KID5 score or a relatively higher iDA5 score. CONCLUSION: The developed artificial intelligence tools should be implemented in clinical practice in conjunction with the conventional morphological assessment for the conduction of optimized embryo transfer in terms of a successful live birth.

Investigating developmental characteristics of biopsied blastocysts stratified by mitochondrial copy numbers using time-lapse monitoring.

BACKGROUND: For in vitro fertilization (IVF), mitochondrial DNA (mtDNA) levels in the trophectodermal (TE) cells of biopsied blastocysts have been suggested to be associated with the cells' developmental potential. However, scholars have reached differing opinions regarding the use of mtDNA levels as a reliable biomarker for predicting IVF outcomes. Therefore, this study aims to assess the association of mitochondrial copy number measured by mitoscore associated with embryonic developmental characteristics and ploidy. METHODS: This retrospective study analyzed the developmental characteristics of embryos and mtDNA levels in biopsied trophectodermal cells. The analysis was carried out using time-lapse monitoring and next-generation sequencing from September 2021 to September 2022. Five hundred and fifteen blastocysts were biopsied from 88 patients undergoing IVF who met the inclusion criteria. Embryonic morphokinetics and morphology were evaluated at 118 h after insemination using all recorded images. Blastocysts with appropriate morphology on day 5 or 6 underwent TE biopsy and preimplantation genetic testing for aneuploidy (PGT-A). Statistical analysis involved generalized estimating equations, Pearson's chi-squared test, Fisher's exact test, and Kruskal-Wallis test, with a significance level set at P < 0.05. RESULTS: To examine differences in embryonic characteristics between blastocysts with low versus high mitoscores, the blastocysts were divided into quartiles based on their mitoscore. Regarding morphokinetic characteristics, no significant differences in most developmental kinetics and observed cleavage dysmorphisms were discovered. However, blastocysts in mitoscore group 1 had a longer time for reaching 3-cell stage after tPNf (t3; median: 14.4 h) than did those in mitoscore group 2 (median: 13.8 h) and a longer second cell cycle (CC2; median: 11.7 h) than did blastocysts in mitoscore groups 2 (median: 11.3 h) and 4 (median: 11.4 h; P < 0.05). Moreover, blastocysts in mitoscore group 4 had a lower euploid rate (22.6%) and a higher aneuploid rate (59.1%) than did those in the other mitoscore groups (39.6-49.3% and 30.3-43.2%; P < 0.05). The rate of whole-chromosomal alterations in mitoscore group 4 (63.4%) was higher than that in mitoscore groups 1 (47.3%) and 2 (40.1%; P < 0.05). A multivariate logistic regression model was used to analyze associations between the mitoscore and euploidy of elective blastocysts. After accounting for factors that could potentially affect the outcome, the mitoscore still exhibited a negative association with the likelihood of euploidy (adjusted OR = 0.581, 95% CI: 0.396-0.854; P = 0.006). CONCLUSIONS: Blastocysts with varying levels of mitochondrial DNA, identified through biopsies, displayed similar characteristics in their early preimplantation development as observed through time-lapse imaging. However, the mitochondrial DNA level determined by the mitoscore can be used as a standalone predictor of euploidy.

Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rate.

RESEARCH QUESTION: Could EMBRYOLY, an artificial intelligence embryo evaluation tool, assist embryologists to increase first cycle pregnancy rate and reduce cycles to pregnancy for patients? DESIGN: Data from 11,988 embryos were collected via EMBRYOLY from 2666 egg retrievals (2019-2022) across 11 centres in France, Spain and Morocco using three time-lapse systems (TLS). Data from two independent clinics were also examined. EMBRYOLY's transformer-based model was applied to transferred embryos to evaluate ranking performances against pregnancy and birth outcomes. It was applied to cohorts to rank sibling embryos (including non-transferred) according to their likelihood of clinical pregnancy and to compute the agreement with the embryologist's highest ranked embryo. Its effect on time to pregnancy and first cycle pregnancy rate was evaluated on cohorts with multiple single blastocyst transfers, assuming the embryologist would have considered EMBRYOLY's ranking on the embryos favoured for transfer. RESULTS: EMBRYOLY's score correlated significantly with clinical pregnancies and live births for cleavage and blastocyst transfers. This held true for clinical pregnancies from blastocyst transfers in two independent clinics. In cases of multiple single embryo transfers, embryologists achieved a 19.8% first cycle pregnancy rate, which could have been improved to 44.1% with the adjunctive use of EMBRYOLY (McNemar's test: P < 0.001). This could have reduced cycles to clinical pregnancy from 2.01 to 1.66 (Wilcoxon test: P < 0.001). CONCLUSIONS: EMBRYOLY's potential to enhance first cycle pregnancy rates when combined with embryologists' expertise is highlighted. It reduces the number of unsuccessful cycles for patients across TLS and IVF centres.

Formation of the first plane of division relative to the pronuclear axis predicts embryonic ploidy.

RESEARCH QUESTION: Is there a relationship between the pronuclear axis and the first cleavage plane formation in human pronuclear-stage embryos, and what are the effects on ploidy and clinical pregnancy rates? DESIGN: Transferred embryos were followed up until their prognoses. A total of 762 embryos formed two cells and reached the blastocyst stage after normal fertilization in a time-lapse incubator. Embryos were classified into three groups: group A: embryos in which the first plane of division was formed parallel to the axis of the pronucleus; group B: embryos in which cases of oblique formation were observed; and group C: embryos in which cases of perpendicular formation were observed. RESULTS: The euploidy rate was significantly higher in groups A and B than those in group C (P < 0.01), whereas the aneuploidy rate was significantly higher in group C (P < 0.01) than in groups A and B. No differences were found between the three groups in frequency of positive HCG-based pregnancy tests, frequency of clinical pregnancies, miscarriage rates or delivery rates. CONCLUSIONS: The formation pattern of the first plane of division relative to the pronuclear axis was a predictor of embryonic ploidy, with a reduced rate of euploidy and a high probability of aneuploidy observed when the first plane of division was perpendicular to the pronuclear axis.

The AMSlide for noninvasive time-lapse imaging of arbuscular mycorrhizal symbiosis.

Arbuscular mycorrhizal (AM) symbiosis, the nutritional partnership between AM fungi and most plant species, is globally ubiquitous and of great ecological and agricultural importance. Studying the processes of AM symbiosis is confounded by its highly spatiotemporally dynamic nature. While microscopy methods exist to probe the spatial side of this plant-fungal interaction, the temporal side remains more challenging, as reliable deep-tissue time-lapse imaging requires both symbiotic partners to remain undisturbed over prolonged time periods. Here, we introduce the AMSlide: a noninvasive, high-resolution, live-imaging system optimised for AM symbiosis research. We demonstrate the AMSlide's applications in confocal microscopy of mycorrhizal roots, from whole colonisation zones to subcellular structures, over timeframes from minutes to weeks. The AMSlide's versatility for different microscope set-ups, imaging techniques, and plant and fungal species is also outlined. It is hoped that the AMSlide will be applied in future research to fill in the temporal blanks in our understanding of AM symbiosis, as well as broader root and rhizosphere processes.

Time-Lapse Macro Imaging with Dissolution Tests for Exploring the Interrelationship Between Disintegration and Dissolution Behaviors of Solid Dosages.

OBJECTIVE: This study aims to establish a Flow-through Visualization Dissolution System (FVDS) that combines time-lapse macro-imaging and a flow-through cell to simultaneously elucidate dissolution and disintegration profiles. METHODS: Three cefaclor extended-release tablets (CEC-1, CEC-2, CEC-3) from different manufacturers were subjected to dissolution tests using both the US Pharmacopeia basket method and the FVDS method. Two dissolution media plans were implemented in FVDS: i) Plan I involved dissolution in pH1.0 medium for 12 h; ii) Plan II initiated dissolution in pH1.0 medium for 1 h, followed by pH6.8 phosphate buffer for 11 h. The resulting dissolution data were fitted using classic mathematical models. Pixel information was further extracted from images obtained using FVDS and plotted over time. RESULTS: The basket method showed the cumulative dissolution of all three tablets in pH1.0, pH4.0 and water reached 80% within 6 h, but remained below 60% in the pH6.8 medium. The f2 values indicated CEC-2 was similar to CEC-1 in the pH4.0 medium, pH6.8 medium and water. Using FVDS with medium plan II, the cumulative dissolution of CEC-1 and CEC-2 reached about 80% showing similarity, while no similarity was observed between CEC-3 and CEC-1. The f2 factor of the percentage area change profiles also showed consistent results in the dissolution profile of medium plan II. However, FVDS with medium plan I cannot distinguish between CEC-2 and CEC-3. CONCLUSION: FVDS offers an alternative to traditional dissolution methods by integrating imaging analysis as a complementary tool to disintegration and dissolution testing methods.

Detrimental effects of electromagnetic radiation emitted from cell phone on embryo morphokinetics and blastocyst viability in mice.

Electromagnetic radiation (EMR) has deleterious effects on sperm motility and viability, as well as oocyte membrane and organelle structure. The aim was to assess the effects of cell phone radiation on preimplantation embryo morphokinetics and blastocyst viability in mice. For superovulation, 20 female mice were treated with intraperitoneal (IP) injections of 10 IU pregnant mare's serum gonadotropin (Folligon® PMSG), followed by 10 IU of human chorionic gonadotropin (hCG) after 48 h. The zygotes (n = 150) from the control group were incubated for 4 days. The experimental zygotes (n = 150) were exposed to a cell phone emitting EMR with a frequency range 900-1800 MHz for 30 min on day 1. Then, all embryos were cultured in the time-lapse system and annotated based on time points from the 2-cell stage (t2) to hatched blastocyst (tHDyz), as well as abnormal cleavage patterns. Blastocyst viability was assessed using Hoechst and propidium iodide staining. Significant increases (P < 0.05) were observed in the cleavage division time points of t2, t8, t10, and t12 of the experimental group compared with the controls. In terms of blastocyst formation parameters, a delay in embryo development was observed in the experimental group compared with the controls. Data analysis of the time intervals between the two groups showed a significant difference in the s3 time interval (P < 0.05). Also, the rates of fragmentation, reverse cleavage, vacuole formation, and embryo arrest were significantly higher in the experimental group (P < 0.05). Furthermore, the cell survival rate in the experimental group was lower than the control group (P < 0.05). Exposure to EMR has detrimental consequences for preimplantation embryo development in mice. These effects can manifest as defects in the cleavage stage and impaired blastocyst formation, leading to lower cell viability.

Time-lapse imaging of morula compaction for selecting high-quality blastocysts: a retrospective cohort study.

PURPOSE: Before blastocyst development, embryos undergo morphological and metabolic changes crucial for their subsequent growth. This study aimed to investigate the relationship between morula compaction and blastocyst formation and the subsequent chromosomal status of the embryos. METHODS: This retrospective cohort study evaluated embryo development (n = 371) using time-lapse imaging; 94 blastocysts underwent preimplantation genetic testing for aneuploidy (PGT-A). RESULTS: The embryos were classified as fully (Group 1, n = 194) or partially (Group 2, n = 177) compacted. Group 1 had significantly higher proportions of good- and average-quality blastocysts than Group 2 (21.6% vs. 3.4%, p = 0.001; 47.9% vs. 26.6%, p = 0.001, respectively). The time from the morula stage to the beginning and completion of compaction and blastocyst formation was significantly shorter in Group 1 than in Group 2 (78.6 vs. 82.4 h, p = 0.001; 87.0 vs. 92.2 h, p = 0.001; 100.2 vs. 103.7 h, p = 0.017, respectively). Group 1 embryos had larger surface areas than Group 2 embryos at various time points following blastocyst formation. Group 1 blastocysts had significantly higher average expansion rates than Group 2 blastocysts (653.6 vs. 499.2 µm2/h, p = 0.001). PGT-A revealed a higher proportion of euploid embryos in Group 1 than in Group 2 (47.2% vs. 36.6%, p = 0.303). CONCLUSION: Time-lapse microscopy uncovered a positive relationship between compaction and blastocyst quality and its association with embryo ploidy. Hence, compaction evaluation should be prioritized before blastocyst selection for transfer or cryopreservation.

Complex electrical measurements of waste rock during acid mine drainage generation and release: Kinetic column tests.

Acid mine drainage (AMD) emanating from waste rock piles (WRPs) at mining sites is a global concern. Successful rehabilitation of these sites requires effective characterization and monitoring of the waste rock during AMD generation/release. Traditional approaches involve ex-situ analysis of waste rock and porewater samples collected via corings and monitoring wells; however, this is highly disruptive, costly, and provides sparsely distributed point information across enormous volumes typical of WRPs. Geoelectrical techniques are a promising approach for non-invasive continuous imaging; however, their application has been limited to 'one-off' imaging with few studies on monitoring waste rock evolution. The objective of this study is to assess the geoelectrical signatures of changing waste rock during AMD generation/release. Field waste rock samples were extracted from three mine WRPs and first characterized for mineralogy and acid generation potential. Kinetic tests were then performed on each sample using leaching columns and humidity cells, with simultaneous measurements of effluent quality and complex electrical conductivity (real and imaginary components measure conduction and polarization, respectively). Results show that real conductivity was highly sensitive to changes associated with AMD leachate quality (e.g., 28,800 to 68 mg/L acidity) and surface of the waste material. Imaginary conductivity measurements identified changes in the waste mineralogy over time, though these signatures were not very distinct, which is likely due to low sulfide contents and limited oxidation (e.g., 0.59 wt% sulfide and 33% air saturation). This study improves our understanding of geoelectrical signatures associated with real waste rock, demonstrating the potential application of the electrical resistivity tomography and induced polarization techniques for mine waste investigations.

Monitoring carbon-based remediation of DNAPL-contaminated groundwater via spectral induced polarization.

Colloidal activated carbon (CAC) is an emerging remedial enhancement fluid that is injected into the subsurface to adsorb hazardous industrial compounds for subsequent removal. CAC-enhanced remediation relies on accurate subsurface characterization and monitoring to ensure CAC reaches intended treatment locations. The objective of this study was to assess the effectiveness of the spectral induced polarization (SIP) technique to track CAC migration within porous media and its adsorption of the chlorinated solvent, tetrachloroethylene (PCE). Dynamic column experiments were performed with cyclic injection and flow of groundwater, CAC, and PCE within porous media, and simultaneous measurements of SIP and effluent quality. Results showed an increase in both the real and imaginary conductivities of the SIP response during injection/flow of CAC within porous media. Real conductivity returned to pre-CAC levels during subsequent flushing of CAC with groundwater, which had left behind only carbon-coated soil grains; however, imaginary conductivity identified the change in polarizability due to the alterations on the grain surface. The subsequent adsorption of aqueous phase PCE did not generate a distinctive change in SIP response, mainly due to the low 50 mg/L concentrations used. Overall, this study suggests that SIP can be a valuable tool to effectively and non-invasively track the migration of injected CAC within porous media for contaminant adsorption, suggesting it can be used to enhance the implementation and management of environmental remediation programs.

Morphokinetic features in human embryos: Analysis by our original high-resolution time-lapse cinematography-Summary of the past two decades.

Background: The pioneering work by Dr. Payne et al. in time-lapse cinematography for observation of the morphokinetic features of human embryos inspired us to develop a new in vitro culture system with high-resolution time-lapse cinematography (hR-TLC) back in 2001. Methods: This in vitro culture system was capable of maintaining stable culture and was constructed on an inverted microscope stage. Embryos were observed and photographed noninvasively for an extended period, up to 7 days. The obtained images were displayed at a speed of 30 frames per second and individually analyzed. Results: Using hR-TLC, human fertilization and subsequent embryonic development were visualized, revealing the time course of phenomena and many unusual dynamics. Conclusion: In this review, we summarize the results of our hR-TLC analysis of early human embryonic development over the past 20 years. In the near future, it is expected that the vast amount of information obtained by hR-TLC will be integrated into the AI system for further analysis and to provide feedback that will have the potential to improve clinical practice. In the era of SDGs and environmental awareness, we should be cautious about the direction in which AI can be utilized to avoid any further harm to the planet.