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.

RoPod, a customizable toolkit for non-invasive root imaging, reveals cell type-specific dynamics of plant autophagy.

Arabidopsis root is a classic model system in plant cell and molecular biology. The sensitivity of plant roots to local environmental perturbation challenges data reproducibility and incentivizes further optimization of imaging and phenotyping tools. Here we present RoPod, an easy-to-use toolkit for low-stress live time-lapse imaging of Arabidopsis roots. RoPod comprises a dedicated protocol for plant cultivation and a customizable 3D-printed vessel with integrated microscopy-grade glass that serves simultaneously as a growth and imaging chamber. RoPod reduces impact of sample handling, preserves live samples for prolonged imaging sessions, and facilitates application of treatments during image acquisition. We describe a protocol for RoPods fabrication and provide illustrative application pipelines for monitoring root hair growth and autophagic activity. Furthermore, we showcase how the use of RoPods advanced our understanding of plant autophagy, a major catabolic pathway and a key player in plant fitness. Specifically, we obtained fine time resolution for autophagy response to commonly used chemical modulators of the pathway and revealed previously overlooked cell type-specific changes in the autophagy response. These results will aid a deeper understanding of the physiological role of autophagy and provide valuable guidelines for choosing sampling time during end-point assays currently employed in plant autophagy research.

Mammalian lures monitored with time-lapse cameras increase detection of pythons and other snakes.

Background: Enhancing detection of cryptic snakes is critical for the development of conservation and management strategies; yet, finding methods that provide adequate detection remains challenging. Issues with detecting snakes can be particularly problematic for some species, like the invasive Burmese python (Python bivittatus) in the Florida Everglades. Methods: Using multiple survey methods, we predicted that our ability to detect pythons, larger snakes and all other snakes would be enhanced with the use of live mammalian lures (domesticated rabbits; Oryctolagus cuniculus). Specifically, we used visual surveys, python detection dogs, and time-lapse game cameras to determine if domesticated rabbits were an effective lure. Results: Time-lapse game cameras detected almost 40 times more snakes (n = 375, treatment = 245, control = 130) than visual surveys (n = 10). We recorded 21 independent detections of pythons at treatment pens (with lures) and one detection at a control pen (without lures). In addition, we found larger snakes, and all other snakes were 165% and 74% more likely to be detected at treatment pens compared to control pens, respectively. Time-lapse cameras detected almost 40 times more snakes than visual surveys; we did not detect any pythons with python detection dogs. Conclusions: Our study presents compelling evidence that the detection of snakes is improved by coupling live mammalian lures with time-lapse game cameras. Although the identification of smaller snake species was limited, this was due to pixel resolution, which could be improved by changing the camera focal length. For larger snakes with individually distinctive patterns, this method could potentially be used to identify unique individuals and thus allow researchers to estimate population dynamics.

Quantification of Mycobacterium tuberculosis Growth in Cell-Based Infection Assays by Time-Lapse Fluorescence Microscopy.

Quantification of Mycobacterium tuberculosis (Mtb) growth dynamics in cell-based in vitro infection models is traditionally carried out by measurement of colony forming units (CFU). However, Mtb being an extremely slow growing organism (16-24 h doubling time), this approach requires at least 3 weeks of incubation to obtain measurable readouts. In this chapter, we describe an alternative approach based on time-lapse microscopy and quantitative image analysis that allows faster quantification of Mtb growth dynamics in host cells. In addition, this approach provides the capability to capture other readouts from the same experimental setup, such as host cell viability, bacterial localization as well as the dynamics of propagation of infection between the host cells.

Analysing adherence to guidelines for time-lapse imaging information on UK fertility clinic websites.

This study aims to systematically analyze the provision of information on Time-lapse Imaging (TLI) by UK fertility clinic websites. We conducted an analysis of 106 clinic websites that offer fertility treatment to self-funded patients. The analysis aimed to examine whether these clinics offer TLI, the associated cost for patients, and the clarity and quality of the provided information. Out of the 106 websites analysed, 71 (67%) claimed to offer TLI. Among these websites, 25 (35.2%) mentioned charging patients between £300 and £850, 25 (35.8%) claimed not to charge patients, and 21 (29.6%) did not provide any cost information for TLI. Furthermore, 64 (90.1%) websites made claims or implied that TLI leads to improved clinical outcomes by enhancing embryo selection. Notably, 34 (47.9%) websites did not mention or provide any links to the HFEA rating system. It is crucial to provide patients with clear and accurate information to enable them to make fully informed decisions about TLI, particularly when they are responsible for the associated costs. The findings of this study raise concerns about the reliability and accuracy of the information available on fertility clinic websites, which are typically the primary source of information for patients.

Association between embryo morphokinetic development and intracytoplasmic sperm injection with epididymal sperm via time-lapse imaging.

The objective of this study was to investigate the impact of sperm source on embryo morphokinetics and the clinical outcomes of intracytoplasmic sperm injection (ICSI) cycles by considering the clustering of data (multiple embryos per patient that share a comparable developmental timing). This matched cohort study was performed at a private university-affiliated in vitro fertilization center. Women who underwent ICSI with epididymal sperm between January 2019 and December 2020 (the percutaneous epididymal sperm aspiration group, n = 32 cycles) were matched with women who underwent ICSI with ejaculated sperm because of idiopathic male factor infertility (the male factor infertility [MFI] group, n = 32 cycles) or female infertility (the control group, n = 32 cycles). Embryos were cultured in a time-lapse imaging incubator, and morphokinetic development was recorded and compared among the groups. Significantly slower divisions were observed in embryos derived from epididymal sperm than in those derived from the MFI and control groups. Embryos derived from epididymal sperm had a significantly lower KIDScore (3.1 ± 0.2) than did those derived from ejaculated spermatozoa from the MFI (5.4 ± 0.1) and control (5.6 ± 0.2, p < 0.001) groups. Epididymal sperm-derived embryos showed a significantly greater occurrence of multinucleation (23.2%) than did those derived from ejaculated sperm from the MFI and control groups (2.8% and 3.7%, p < 0.001, respectively). Epididymal sperm-derived embryos were significantly more likely to undergo direct or reverse cleavage (11.1%) than ejaculated sperm-derived embryos in the control group (4.3%, p = 0.001). In conclusion, delayed cell cleavage and increased incidences of blastomere multinucleation and abnormal cleavage patterns are observed when epididymal-derived sperm are used for ICSI.

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying various biological functions and processes, particularly in organs such as the brain and heart. However, cells in living organisms often exhibit extensive and complex movements caused by organ deformation and whole-body motion. These movements pose a challenge in obtaining high-quality time-lapse cell images and tracking the intricate cell movements in the captured images. Recent advances in deep learning techniques provide powerful tools for detecting cells in low-quality images with densely packed cell populations, as well as estimating cell positions for cells undergoing large nonrigid movements. This chapter introduces the challenges of cell tracking in deforming organs and moving animals, outlines the solutions to these challenges, and presents a detailed protocol for data preparation, as well as for performing cell segmentation and tracking using the latest version of 3DeeCellTracker. This protocol is expected to enable researchers to gain deeper insights into organ dynamics and biological processes.

ARTseq-FISH reveals position-dependent differences in gene expression of micropatterned mESCs.

Differences in gene-expression profiles between individual cells can give rise to distinct cell fate decisions. Yet how localisation on a micropattern impacts initial changes in mRNA, protein, and phosphoprotein abundance remains unclear. To identify the effect of cellular position on gene expression, we developed a scalable antibody and mRNA targeting sequential fluorescence in situ hybridisation (ARTseq-FISH) method capable of simultaneously profiling mRNAs, proteins, and phosphoproteins in single cells. We studied 67 (phospho-)protein and mRNA targets in individual mouse embryonic stem cells (mESCs) cultured on circular micropatterns. ARTseq-FISH reveals relative changes in both abundance and localisation of mRNAs and (phospho-)proteins during the first 48 hours of exit from pluripotency. We confirm these changes by conventional immunofluorescence and time-lapse microscopy. Chemical labelling, immunofluorescence, and single-cell time-lapse microscopy further show that cells closer to the edge of the micropattern exhibit increased proliferation compared to cells at the centre. Together these data suggest that while gene expression is still highly heterogeneous position-dependent differences in mRNA and protein levels emerge as early as 12 hours after LIF withdrawal.

Lifecycle of a predatory bacterium vampirizing its prey through the cell envelope and S-layer.

Predatory bacteria feed upon other bacteria in various environments. Bdellovibrio exovorus is an obligate epibiotic predator that attaches on the prey cell surface, where it grows and proliferates. Although the mechanisms allowing feeding through the prey cell envelope are unknown, it has been proposed that the prey's proteinaceous S-layer may act as a defensive structure against predation. Here, we use time-lapse and cryo-electron microscopy to image the lifecycle of B. exovorus feeding on Caulobacter crescentus. We show that B. exovorus proliferates by non-binary division, primarily generating three daughter cells. Moreover, the predator feeds on C. crescentus regardless of the presence of an S-layer, challenging its assumed protective role against predators. Finally, we show that apparently secure junctions are established between prey and predator outer membranes.

Isolated Random Forest Assisted Spatio-Temporal Ant Colony Evolutionary Algorithm for Cell Tracking in Time-Lapse Sequences.

Multi-Object tracking in real world environments is a tough problem, especially for cell morphogenesis with division. Most cell tracking methods are hard to achieve reliable mitosis detection, efficient inter-frame matching, and accurate state estimation simultaneously within a unified tracking framework. In this paper, we propose a novel unified framework that leverages a spatio-temporal ant colony evolutionary algorithm to track cells amidst mitosis under measurement uncertainty. Each Bernoulli ant colony representing a migrating cell is able to capture the occurrence of mitosis through the proposed Isolation Random Forest (IRF)-assisted temporal mitosis detection algorithm with the assumption that mitotic cells exhibit unique spatio-temporal features different from non-mitotic ones. Guided by prediction of a division event, multiple ant colonies evolve between consecutive frames according to an augmented assignment matrix solved by the extended Hungarian method. To handle dense cell populations, an efficient group partition between cells and measurements is exploited, which enables multiple assignment tasks to be executed in parallel with a reduction in matrix dimension. After inter-frame traversing, the ant colony transitions to a foraging stage in which it begins approximating the Bernoulli parameter to estimate cell state by iteratively updating its pheromone field. Experiments on multi-cell tracking in the presence of cell mitosis and morphological changes are conducted, and the results demonstrate that the proposed method outperforms state-of-the-art approaches, striking a balance between accuracy and computational efficiency.

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.

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.

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.

Time-Lapse Imaging of Migrating Neurons and Glial Progenitors in Embryonic Mouse Brain Slices.

During the development of the cerebral cortex, neurons and glial cells originate in the ventricular zone lining the ventricle and migrate toward the brain surface. This process is crucial for proper brain function, and its dysregulation can result in neurodevelopmental and psychiatric disorders after birth. In fact, many genes responsible for these diseases have been found to be involved in this process, and therefore, revealing how these mutations affect cellular dynamics is important for understanding the pathogenesis of these diseases. This protocol introduces a technique for time-lapse imaging of migrating neurons and glial progenitors in brain slices obtained from mouse embryos. Cells are labeled with fluorescent proteins using in utero electroporation, which visualizes individual cells migrating from the ventricular zone with a high signal-to-noise ratio. Moreover, this in vivo gene transfer system enables us to easily perform gain-of-function or loss-of-function experiments on the given genes by co-electroporation of their expression or knockdown/knockout vectors. Using this protocol, the migratory behavior and migration speed of individual cells, information that is never obtained from fixed brains, can be analyzed.

Multiscale transport and 4D time-lapse imaging in precision-cut liver slices (PCLS).

Background: Monitoring cellular processes across different levels of complexity, from the cellular to the tissue scale, is important for understanding tissue structure and function. However, it is challenging to monitor and estimate these structural and dynamic interactions within three-dimensional (3D) tissue models. Objective: The aim of this study was to design a method for imaging, tracking, and quantifying 3D changes in cell morphology (shape and size) within liver tissue, specifically a precision-cut liver slice (PCLS). A PCLS is a 3D model of the liver that allows the study of the structure and function of liver cells in their native microenvironment. Methods: Here, we present a method for imaging liver tissue during anisosmotic exposure in a multispectral four-dimensional manner. Three metrics of tissue morphology were measured to quantify the effects of osmotic stress on liver tissue. We estimated the changes in the volume of whole precision cut liver slices, quantified the changes in nuclei position, and calculated the changes in volumetric responses of tissue-embedded cells. Results: During equilibration with cell-membrane-permeating and non-permeating solutes, the whole tissue experiences shrinkage and expansion. As nuclei showed a change in position and directional displacement under osmotic stress, we demonstrate that nuclei could be used as a probe to measure local osmotic and mechanical stress. Moreover, we demonstrate that cells change their volume within tissue slices as a result of osmotic perturbation and that this change in volume is dependent on the position of the cell within the tissue and the duration of the exposure. Conclusion: The results of this study have implications for a better understanding of multiscale transport, mechanobiology, and triggered biological responses within complex biological structures.

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development.

BACKGROUND: Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to assist embryologists with automatized and objective predictive models able to standardize human embryo assessment. In this study, we aimed at developing a novel ML-based strategy to identify relevant patterns associated with the prediction of blastocyst development stage on day 5. METHODS: We retrospectively analysed the morphokinetics of 575 embryos obtained from 80 women who underwent IVF at our Unit. Embryo morphokinetics was registered using the Geri plus® time-lapse system. Overall, 30 clinical, morphological and morphokinetic variables related to women and embryos were recorded and combined. Some embryos reached the expanded blastocyst stage on day 5 (BL Group, n = 210), some others did not (nBL Group, n = 365). RESULTS: The novel EmbryoMLSelection framework was developed following four-steps: Feature Selection, Rules Extraction, Rules Selection and Rules Evaluation. Six rules composed by a combination of 8 variables were finally selected, and provided a predictive power described by an AUC of 0.84 and an accuracy of 81%. CONCLUSIONS: We provided herein a new feature-signature able to identify with an high performance embryos with the best developmental competence to reach the expanded blastocyst stage on day 5. Clear and clinically relevant cut-offs were identified for each considered variable, providing an objective tool for early embryo developmental assessment.

WISE: whole-scenario embryo identification using self-supervised learning encoder in IVF.

PURPOSE: To study the effectiveness of whole-scenario embryo identification using a self-supervised learning encoder (WISE) in in vitro fertilization (IVF) on time-lapse, cross-device, and cryo-thawed scenarios. METHODS: WISE was based on the vision transformer (ViT) architecture and masked autoencoders (MAE), a self-supervised learning (SSL) method. To train WISE, we prepared three datasets including the SSL pre-training dataset, the time-lapse identification dataset, and the cross-device identification dataset. To identify whether pairs of images were from the same embryos in different scenarios in the downstream identification tasks, embryo images including time-lapse and microscope images were first pre-processed through object detection, cropping, padding, and resizing, and then fed into WISE to get predictions. RESULTS: WISE could accurately identify embryos in the three scenarios. The accuracy was 99.89% on the time-lapse identification dataset, and 83.55% on the cross-device identification dataset. Besides, we subdivided a cryo-thawed evaluation set from the cross-device test set to have a better estimation of how WISE performs in the real-world, and it reached an accuracy of 82.22%. There were approximately 10% improvements in cross-device and cryo-thawed identification tasks after the SSL method was applied. Besides, WISE demonstrated improvements in the accuracy of 9.5%, 12%, and 18% over embryologists in the three scenarios. CONCLUSION: SSL methods can improve embryo identification accuracy even when dealing with cross-device and cryo-thawed paired images. The study is the first to apply SSL in embryo identification, and the results show the promise of WISE for future application in embryo witnessing.

Rapid time-lapse 3D oxygen tension measurements within hydrogels using widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) and image segmentation.

Understanding the influence of oxygen tension on cellular functions and behaviors is crucial for investigating various physiological and pathological conditions. In vitro cell culture models, particularly those based on hydrogel extracellular matrices, have been developed to study cellular responses in specific oxygen microenvironments. However, accurately characterizing oxygen tension variations with great spatiotemporal resolutions, especially in three dimensions, remains challenging. This paper presents an approach for rapid time-lapse 3D oxygen tension measurements in hydrogels using a widely available inverted fluorescence microscope. Oxygen-sensitive fluorescent microbeads and widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) are utilized for oxygen tension estimation. To incorporate the third dimension, a motorized sample stage is implanted that enables automated image acquisition in the vertical direction. A machine learning algorithm based on K-means clustering is employed for microbead position identification. Using an upside-down microfluidic device, 3D oxygen gradients are generated within a hydrogel sample, and z-stack images are acquired using the FD-FLIM system. Analyses of the acquired images, involving microbead position identification, lifetime calculation, and oxygen tension conversion, are then performed offline. The results demonstrate the functionality of the developed approach for rapid time-lapse 3D oxygen tension measurements in hydrogels. Furthermore, the 3D oxygen tension adjacent to a tumor spheroid within a hydrogel during media exchange is characterized. The results further confirm that the 3D spatiotemporal oxygen tension profiles can be successfully measured quantitatively using the established setup and analysis process and that the approach may have great potential for investigating cellular activities within oxygen microenvironments.

A novel tracking and analysis system for time-lapse cellular imaging of Schizosaccharomyces pombe.

The importance of the parent-progeny relationship tracking technique in single-cell analysis has grown with the passage of time. In this study, fundamental image-processing techniques were combined to develop software capable of inferring cell cycle alterations in fission yeast cells, which exhibit equipartition during division. These methods, exclusively relying on bright-field images as input, could track parent-progeny relationships after cell division by assessing the temporal morphological transformation of these cells. In the application of this technique, the software was employed for calculating intracellular fluorescent dots during every stage of the cell cycle, using a yeast strain expressing EGFP-fused Swi6, which binds to chromatin. The results obtained with this software were consistent with those of previous studies. This software facilitated single-cell-level tracking of parent-progeny relationships in cells exhibiting equipartition during division and enabled the monitoring of spatial fluctuations in a cell cycle-dependent protein. This method, expediting the analysis of extensive datasets, may also empower large-scale screening experiments that cannot be conducted manually.

Facilitating long-term cell examinations and time-lapse recordings in cell biology research with CO2 mini-incubators.

In recent years, microscopy has revolutionized the study of dynamic living cells. However, performing long-term live cell imaging requires stable environmental conditions such as temperature, pH, and humidity. While standard incubators have traditionally provided these conditions, other solutions, like stagetop incubators are available. To further enhance the accessibility of stable cell culture environments for live cell imaging, we developed a portable CO2 cell culture mini-incubator that can be easily adapted to any x-y inverted microscope stage, enabling long-term live cell imaging. This mini-incubator provides and maintains stable environmental conditions and supports cell viability comparable to standard incubators. Moreover, it allows for parallel experiments in the same environment, saving both time and resources. To demonstrate its functionality, different cell lines (VERO and MDA-MB-231) were cultured and evaluated using various assays, including crystal violet staining, MTT, and flow cytometry tests to assess cell adhesion, viability, and apoptosis, respectively. Time-lapse imaging was performed over an 85-h period with MDA-MB-231 cells cultured in the mini-incubator. The results indicate that this device is a viable solution for long-term imaging and can be applied in developmental biology, cell biology, and cancer biology research where long-term time-lapse recording is required.