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BACKGROUND: A traditional view is that stem cells (SCs) divide slowly. Meanwhile, both embryonic and pluripotent SCs display a shorter cell cycle duration (CCD) in comparison to more committed progenitors (CPs). METHODS: We examined the in vitro proliferation and cycling behavior of somatic adult human cells using live cell imaging of passage zero keratinocytes and single-cell RNA sequencing. RESULTS: We found two populations of keratinocytes: those with short CCD and protracted near exponential growth, and those with long CCD and terminal differentiation. Applying the ergodic principle, the comparative numbers of cycling cells in S phase in an enriched population of SCs confirmed a shorter CCD than CPs. Further, analysis of single-cell RNA sequencing of cycling adult human keratinocyte SCs and CPs indicated a shortening of both G1 and G2M phases in the SC. CONCLUSIONS: Contrary to the pervasive paradigm, SCs progress through cell cycle more quickly than more differentiated dividing CPs. Thus, somatic human adult keratinocyte SCs may divide infrequently, but divide rapidly when they divide. Additionally, it was found that SC-like proliferation persisted in vitro.

Abstract 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

Tumours often display invasive behaviours that induce fingering, branching and fragmentation processes. The phenomenon, known as diffusional instability, is driven by differential cell proliferation, migration, and death due to the presence of metabolite and catabolite concentration gradients. An understanding of the intricate dynamics of this spatially heterogeneous process plays a key role in the investigation of tumour growth and invasion. In this study, we developed an in vitro tumour invasion assay to investigate cell invasiveness in tumour spheroids under a chemotactic stimulus. Our method, employing tumour spheroids seeded in a 3D collagen gel within a microfluidic chemotaxis chamber, focuses on the role of diffusive gradients. Using Time-Lapse Microscopy, the dynamic evolution of tumour spheroids was monitored in real-time, providing a comprehensive view of the morphological changes and cell migration patterns under different chemotactic conditions. Specifically, we explored the impact of fetal bovine serum (FBS) gradients on the behaviour of CT26 mouse colon carcinoma cells and compared the effects of varying FBS concentrations to two isotropic control conditions. Furthermore, a finite element in silico model was developed to quantify the diffusive flow of nutrients in the chemotaxis chamber and obtain a detailed understanding of tumour dynamics. Our findings reveal that the presence of a chemotactic gradient significantly influences tumour invasiveness, with higher concentrations of nutrients associated with increased cancer growth and cell migration. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Live-cell imaging of fluorescent biosensors has demonstrated that space-time correlations in signalling of cell collectives play an important organisational role in morphogenesis, wound healing, regeneration, and maintaining epithelial homeostasis. Here, we demonstrate how to quantify one such phenomenon, namely apoptosis-induced ERK activity waves in the MCF10A epithelium. We present a protocol that starts from raw time-lapse fluorescence microscopy images and, through a sequence of image manipulations, ends with ARCOS, our computational method to detect and quantify collective signalling. We also describe the same workflow in the interactive napari image viewer to quantify collective phenomena for users without prior programming experience. Our approach can be applied to space-time correlations in cells, cell collectives, or communities of multicellular organisms, in 2D and 3D geometries. [ABSTRACT FROM AUTHOR]

STUDY QUESTION Is there an association between morphokinetic variables of meiotic maturation and the severity of aneuploidy following in vitro maturation (IVM) in the mouse? SUMMARY ANSWER The severity of meiotic aneuploidy correlates with an extended time to first polar body extrusion (tPB1) and duration of meiosis I (dMI). WHAT IS KNOWN ALREADY Morphokinetic variables measured using time-lapse technology allow for the non-invasive evaluation of preimplantation embryo development within clinical assisted reproductive technology (ART). We recently applied this technology to monitor meiotic progression during IVM of mouse gametes. Whether there is a relationship between morphokinetic variables of meiotic progression and aneuploidy in the resulting egg has not been systematically examined at the resolution of specific chromosomes. Next-generation sequencing (NGS) is a robust clinical tool for determining aneuploidy status and has been reverse-translated in mouse blastocysts and oocytes. Therefore, we harnessed the technologies of time-lapse imaging and NGS to determine the relationship between the morphokinetics of meiotic progression and egg aneuploidy. STUDY DESIGN, SIZE, DURATION Cumulus–oocyte complexes were collected from large antral follicles from hyperstimulated CD-1 mice. Cumulus cells were removed, and spontaneous IVM was performed in the absence or presence of two doses of Nocodazole (25 or 50 nM) to induce a spectrum of spindle abnormalities and chromosome segregation errors during oocyte meiosis. Comprehensive chromosome screening was then performed in the resulting eggs, and morphokinetic variables and ploidy status were compared across experimental groups (control, n = 11; 25 nM Nocodazole, n = 13; 50 nM Nocodazole, n = 23). PARTICIPANTS/MATERIALS, SETTING, METHODS We monitored IVM in mouse oocytes using time-lapse microscopy for 16 h, and time to germinal vesicle breakdown (tGVBD), tPB1, and dMI were analyzed. Following IVM, comprehensive chromosome screening was performed on the eggs and their matched first polar bodies via adaptation of an NGS-based preimplantation genetic testing for aneuploidy (PGT-A) assay. Bioinformatics analysis was performed to align reads to the mouse genome and determine copy number-based predictions of aneuploidy. The concordance of each polar body–egg pair (reciprocal errors) was used to validate the results. Ploidy status was categorized as euploid, 1–3 chromosomal segregation errors, or ≥4 chromosomal segregation errors. Additionally, aneuploidy due to premature separation of sister chromatids (PSSC) versus non-disjunction (NDJ) was distinguished. MAIN RESULTS AND THE ROLE OF CHANCE We applied and validated state-of-the-art NGS technology to screen aneuploidy in individual mouse eggs and matched polar bodies at the chromosome-specific level. By performing IVM in the presence of different doses of Nocodazole, we induced a range of aneuploidy. No aneuploidy was observed in the absence of Nocodazole (0/11), whereas IVM in the presence of 25 and 50 nM Nocodazole resulted in an aneuploidy incidence of 7.69% (1/13) and 82.61% (19/23), respectively. Of the aneuploid eggs, 5% (1/20) was due to PSSC, 65% (13/20) to NDJ, and the remainder to a combination of both. There was no relationship between ploidy status and tGVBD, but tPB1 and the dMI were both significantly prolonged in eggs with reciprocal aneuploidy events compared to the euploid eggs, and this scaled with the severity of aneuploidy. Eggs with ≥4 aneuploid chromosomes had the longest tPB1 and dMI (P  < 0.0001), whereas eggs with one to three aneuploid chromosomes exhibited intermediate lengths of time (P  < 0.0001). LARGE SCALE DATA N/A. LIMITATIONS, REASONS FOR CAUTION We used Nocodazole in this study to disrupt the meiotic spindle and induce aneuploidy in mouse oocytes. Whether the association between morphokinetic variables of meiotic progression and the severity of aneuploidy occurs with other compounds that induce chromosome segregation errors remain to be investigated. In addition, unlike mouse oocytes, human IVM requires the presence of cumulus cells, which precludes visualization of morphokinetic variables of meiotic progression. Thus, our study may have limited direct clinical translatability. WIDER IMPLICATIONS OF THE FINDINGS We validated NGS in mouse eggs to detect aneuploidy at a chromosome-specific resolution which greatly improves the utility of the mouse model. With a tractable and validated model system for characterizing meiotic aneuploidy, investigations into the molecular mechanisms and factors which may influence aneuploidy can be further elaborated. Time-lapse analyses of morphokinetic variables of meiotic progression may be a useful non-invasive predictor of aneuploidy severity. STUDY FUNDING/COMPETING INTERESTS This work was supported by the Bill & Melinda Gates Foundation (INV-003385). Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. The authors have no conflict of interest to disclose. [ABSTRACT FROM AUTHOR]

An alarming rise in antimicrobial resistance worldwide has spurred efforts into the search for alternatives to antibiotic treatments. The use of bacteriophages, bacterial viruses harmless to humans, represents a promising approach with potential to treat bacterial infections (phage therapy). Recent advances in microscopy-based single-cell techniques have allowed researchers to develop new quantitative methodologies for assessing the interactions between bacteria and phages, especially the ability of phages to eradicate bacterial pathogen populations and to modulate growth of both commensal and pathogen populations. Here we combine droplet microfluidics with fluorescence time-lapse microscopy to characterize the growth and lysis dynamics of the bacterium Escherichia coli confined in droplets when challenged with phage. We investigated phages that promote lysis of infected E. coli cells, specifically, a phage species with DNA genome, T7 (Escherichia virus T7) and two phage species with RNA genomes, MS2 (Emesvirus zinderi) and Qβ (Qubevirus durum). Our microfluidic trapping device generated and immobilized picoliter-sized droplets, enabling stable imaging of bacterial growth and lysis in a temperature-controlled setup. Temporal information on bacterial population size was recorded for up to 25  h, allowing us to determine growth rates of bacterial populations and helping us uncover the extent and speed of phage infection. In the long-term, the development of novel microfluidic single-cell and population-level approaches will expedite research towards fundamental understanding of the genetic and molecular basis of rapid phage-induced lysis and eco-evolutionary aspects of bacteria-phage dynamics, and ultimately help identify key factors influencing the success of phage therapy [ABSTRACT FROM AUTHOR]

Summary: Our objective was to study whether serum anti-Müllerian hormone (AMH) concentrations were associated with embryo morphokinetic events. This retrospective cohort study was performed in a private university-affiliated in vitro fertilization centre between March 2019 and December 2020 and included 902 oocytes cultured in a time-lapse imaging incubator, obtained from 114 intracytoplasmic sperm injection cycles performed. The relationship between AMH concentrations and morphokinetic events was investigated by considering the clustering of data (multiple embryos/patient). Evaluated kinetic markers were time to pronuclei appearance (tPNa) and fading (tPNf), time to two (t2), three (t3), four (t4), five (t5), six (t6), seven (t7), and eight cells (t8), (tSB) and time to the start of blastulation (tSB) and to blastulation (tB). Significant inverse relationships were observed between serum AMH concentrations and tPNf, t3, t4, t5, t6, t7, t8, and tB. The AMH was positively correlated with the KIDScore and implantation rate. Increased serum AMH concentrations correlated with faster embryo development. The clinical implications of this effect on embryo development warrant further investigation. [ABSTRACT FROM AUTHOR]

The embryological stage of the implementation of ART programs can be considered one of the most important, since the assessment of the competencies or "quality" of oocytes, their fertilization and in vitro cultivation to the stage of preimplantation embryos largely determine its success. An efficient method of embryo selection is currently in high demand in this field, since it is a method of selecting embryos that have the highest potential for implantation. Almost all publications on time-lapse microscopy have focused on timing specific embryonic division events and then using this information to create algorithms to help select an embryo for transfer, but there are insufficient data on obstetric and perinatal outcomes. [ABSTRACT FROM AUTHOR]

Simple Summary: We used the charged-particle microbeam installed at the AIFIRA facility to perform micro-irradiation experiments and measure the recruitment kinetics of DNA signaling and repair proteins. We developed and validated image acquisition and processing methods to enable a systematic study of the recruitment kinetics of two GFP-tagged proteins (GFP-XRCC1 and GFP-RNF8) after irradiation with protons and α-particles. Online measurement of fluorescence intensity and recruitment time as a function of particle type and number allowed us to characterize the differences in behavior between the two proteins. Time-lapse fluorescence imaging coupled to micro-irradiation devices provides information on the kinetics of DNA repair protein accumulation, from a few seconds to several minutes after irradiation. Charged-particle microbeams are valuable tools for such studies since they provide a way to selectively irradiate micrometric areas within a cell nucleus, control the dose and the micro-dosimetric quantities by means of advanced detection systems and Monte Carlo simulations and monitor the early cell response by means of beamline microscopy. We used the charged-particle microbeam installed at the AIFIRA facility to perform micro-irradiation experiments and measure the recruitment kinetics of two proteins involved in DNA signaling and repair pathways following exposure to protons and α-particles. We developed and validated image acquisition and processing methods to enable a systematic study of the recruitment kinetics of GFP-XRCC1 and GFP-RNF8. We show that XRCC1 is recruited to DNA damage sites a few seconds after irradiation as a function of the total deposited energy and quite independently of the particle LET. RNF8 is recruited to DNA damage sites a few minutes after irradiation and its recruitment kinetics depends on the particle LET. [ABSTRACT FROM AUTHOR]

Do morphokinetic profiles and treatment outcomes differ between embryos developed from vitrified or fresh oocytes? Retrospective multicentre analysis using data from eight CARE Fertility clinics across the UK between 2012 and 2019. Patients receiving treatment using embryos developed from vitrified oocytes (n = 118 women, n = 748 oocytes), providing 557 zygotes during this time period, were recruited and matched with patients undergoing treatment with embryos developed from fresh oocytes (n = 123 women, n = 1110 oocytes), providing 539 zygotes in the same time frame. Time-lapse microscopy was used to assess morphokinetic profiles, including early cleavage divisions (2- through to 8-cell), post-cleavage stages including time to start of compaction, time to morula, time to start of blastulation and time to full blastocyst. Duration of key stages such as the compaction stage were also calculated. Treatment outcomes were compared between the two groups (live birth rate, clinical pregnancy rate and implantation rate). A significant delay of 2–3 h across all early cleavage divisions (2- through to 8-cell) and time to start of compaction occurred in the vitrified group versus fresh controls (all P ≤ 0.01). The compaction stage was significantly shorter in vitrified oocytes (19.02 ± 0.5 h) compared with fresh controls (22.45 ± 0.6 h, P < 0.001). There was no difference in the time that fresh and vitrified embryos reached the blastocyst stage (108.03 ± 0.7 versus 107.78 ± 0.6 h). There was no significant difference in treatment outcomes between the two groups. Vitrification is a useful technique for extending female fertility with no effects on IVF treatment outcome. [ABSTRACT FROM AUTHOR]

Cells use molecular circuits to interpret and respond to extracellular cues, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I interferon (IFN)-responsive regulatory network operates in single human cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1/early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback loops, enabling duration-dependent desensitization to repetitive stimulations.

During the last few decades, assisted reproductive technologies (ARTs) have flourished rapidly and accompanied a set of advanced procedures such as intracytoplasmic sperm injection (ICSI), electronic witnessing, digital monitoring through embryoscope time-lapse systems, consistent decision-making algorithms with advanced statistics modes and preimplantation genetic testing (PGT). In usual practice, manual procedures were routinely used in IVF (in vitro fertilization) laboratories worldwide, but automation and artificial intelligence (AI) systems are promising techniques for quality assurance, which reduced the burden on the working staff in the embryology laboratory. In addition, these systems are equipped with powerful mathematical tools that minimize technician variability in the IVF lab and efficiently generate data for impaired gametes and embryos. The principal challenge of single-sperm selection out of 108 gametes can be sorted out by incorporating machine learning algorithms coupled with advanced data processing capabilities. In the same line, the emergence of closed embryo culture systems (CECSs) in human embryology has enabled the accurate morphokinetic evaluation of the more rapid cell division and the identification of normal and abnormal hallmarks of embryo viability. In particular, these CECSs are guided by the latest time-lapse microscopy (TLM) facility to continuously monitor embryo development kinetics without removing them from controlled and stable incubator conditions. In conclusion, AI-driven models can reduce technical variability in sample handling and remove the burden of the most subjective, tedious and/or monotonous aspects of the IVF lab. Furthermore, these systems also highlight environmental stressors that could hamper embryo development competence. In a broader sense, AI-based approaches are more accurate, precise and rapid in predicting embryo quality noninvasively.

Summary: Oocyte-mediated somatic cell haploidization is a process in which a diploid cell halves its chromosomal content by segregating its homologue within the ooplasm. Replacing the donor oocyte nucleus with a patient's female diploid somatic nucleus can generate patient-genotyped oocytes. Insemination of these resulting constructs enables their activation and induces a reductive meiotic division, haploidizing the diploid female donor cell that can subsequently support syngamy with the male genome and create a zygote. So far, experimental data for this method have been limited and have not consistently proven the generation of chromosomally normal embryos. Overall, we achieved reconstruction of murine oocytes with a micromanipulation survival rate of 56.5%, and a correct haploidization and fertilization rate of 31.2%, resulting in a 12.7% blastocyst rate. Time-lapse analysis revealed that reconstructed embryos underwent a timely polar body extrusion and pronuclear appearance followed by a satisfactory embryonic cleavage, comparable with the control. Whole genome sequencing of the analyzed embryos indicated that 27.3% (6/22) were properly diploid. Our findings suggest that diploid cell haploidization may be a feasible technique for creating functional gametes in mammals. [ABSTRACT FROM AUTHOR]

ABSTRACT Clostridioides difficile infections begin when its metabolically dormant spores germinate in response to sensing bile acid germinants alongside amino acid and divalent cation co-germinants in the small intestine. While bile acid germinants are essential for C. difficile spore germination, it is currently unclear whether both co-germinant signals are required. One model proposes that divalent cations, particularly Ca2+, are essential for inducing germination, while another proposes that either co-germinant class can induce germination. The former model is based on the finding that spores defective in releasing large stores of internal Ca2+ in the form of calcium dipicolinic acid (CaDPA) cannot germinate when germination is induced with bile acid germinant and amino acid co-germinant alone. However, since the reduced optical density of CaDPA-less spores makes it difficult to accurately measure their germination, we developed a novel automated, time-lapse microscopy-based germination assay to analyze CaDPA mutant germination at the single-spore level. Using this assay, we found that CaDPA mutant spores germinate in the presence of amino acid co-germinant and bile acid germinant. Higher levels of amino acid co-germinants are nevertheless required to induce CaDPA mutant spores to germinate relative to WT spores because CaDPA released by WT spores during germination can function in a feedforward loop to potentiate the germination of other spores within the population. Collectively, these data indicate that Ca2+ is not essential for inducing C. difficile spore germination because amino acid and Ca2+ co-germinant signals are sensed by parallel signaling pathways. IMPORTANCE Clostridioides difficile spore germination is essential for this major nosocomial pathogen to initiate infection. C. difficile spores germinate in response to sensing bile acid germinant signals alongside co-germinant signals. There are two classes of co-germinant signals: Ca2+ and amino acids. Prior work suggested that Ca2+ is essential for C. difficile spore germination based on bulk population analyses of germinating CaDPA mutant spores. Since these assays rely on optical density to measure spore germination and the optical density of CaDPA mutant spores is reduced relative to WT spores, this bulk assay is limited in its capacity to analyze germination. To overcome this limitation, we developed an automated image analysis pipeline to monitor C. difficile spore germination using time-lapse microscopy. With this analysis pipeline, we demonstrate that, although Ca2+ is dispensable for inducing C. difficile spore germination, CaDPA can function in a feedforward loop to potentiate the germination of neighboring spores.

Brain tissue metabolism is distributed across several cell types and subcellular compartments, which activate at different times and with different temporal patterns. The introduction of genetically-encoded fluorescent indicators that are imaged using time-lapse microscopy has opened the possibility of studying brain metabolism at cellular and sub-cellular levels. There are indicators for sugars, monocarboxylates, Krebs cycle intermediates, amino acids, cofactors, and energy nucleotides, which inform about relative levels, concentrations and fluxes. This review offers a brief survey of the metabolic indicators that have been validated in brain cells, with some illustrative examples from the literature. Whereas only a small fraction of the metabolome is currently accessible to fluorescent probes, there are grounds to be optimistic about coming developments and the application of these tools to the study of brain disease.

Much of biochemical regulation ultimately controls growth rate, particularly in microbes. Although time-lapse microscopy visualises cells, determining their growth rates is challenging, particularly for those that divide asymmetrically, like Saccharomyces cerevisiae, because cells often overlap in images. Here, we present the Birth Annotator for Budding Yeast (BABY), an algorithm to determine single-cell growth rates from label-free images. Using a convolutional neural network, BABY resolves overlaps through separating cells by size and assigns buds to mothers by identifying bud necks. BABY uses machine learning to track cells and determine lineages and estimates growth rates as the rates of change of volumes. Using BABY and a microfluidic device, we show that bud growth is likely first sizer- then timer-controlled, that the nuclear concentration of Sfp1, a regulator of ribosome biogenesis, varies before the growth rate does, and that growth rate can be used for real-time control. By estimating single-cell growth rates and so fitness, BABY should generate much biological insight.

Although genetic mutations that alter organisms' average lifespans have been identified in aging research, our understanding of the dynamic changes during aging remains limited. Here, we integrate single-cell imaging, microfluidics, and computational modeling to investigate phenotypic divergence and cellular heterogeneity during replicative aging of single S. cerevisiae cells. Specifically, we find that isogenic cells diverge early in life toward one of two aging paths, which are characterized by distinct age-associated phenotypes. We captured the dynamics of single cells along the paths with a stochastic discrete-state model, which accurately predicts both the measured heterogeneity and the lifespan of cells on each path within a cell population. Our analysis suggests that genetic and environmental factors influence both a cell's choice of paths and the kinetics of paths themselves. Given that these factors are highly conserved throughout eukaryotes, divergent aging might represent a general scheme in cellular aging of other organisms.

Preimplantation genetic testing for aneuploidies (PGT-A) is arguably the most effective embryo selection strategy. Nevertheless, it requires greater workload, costs, and expertise. Therefore, a quest towards user-friendly, non-invasive strategies is ongoing. Although insufficient to replace PGT-A, embryo morphological evaluation is significantly associated with embryonic competence, but scarcely reproducible. Recently, artificial intelligence-powered analyses have been proposed to objectify and automate image evaluations. iDAScore v1.0 is a deep-learning model based on a 3D convolutional neural network trained on time-lapse videos from implanted and non-implanted blastocysts. It is a decision support system for ranking blastocysts without manual input. This retrospective, pre-clinical, external validation included 3604 blastocysts and 808 euploid transfers from 1232 cycles. All blastocysts were retrospectively assessed through the iDAScore v1.0; therefore, it did not influence embryologists' decision-making process. iDAScore v1.0 was significantly associated with embryo morphology and competence, although AUCs for euploidy and live-birth prediction were 0.60 and 0.66, respectively, which is rather comparable to embryologists' performance. Nevertheless, iDAScore v1.0 is objective and reproducible, while embryologists' evaluations are not. In a retrospective simulation, iDAScore v1.0 would have ranked euploid blastocysts as top quality in 63% of cases with one or more euploid and aneuploid blastocysts, and it would have questioned embryologists' ranking in 48% of cases with two or more euploid blastocysts and one or more live birth. Therefore, iDAScore v1.0 may objectify embryologists' evaluations, but randomized controlled trials are required to assess its clinical value. [ABSTRACT FROM AUTHOR]

In an in vitro fertilization program, approximately 10–15% of oocytes obtained after controlled ovarian stimulation are immature, with germinal vesicles (GVs). These oocytes are usually discarded in clinical practice; however, an in vitro maturation (IVM) procedure can be applied to mature them. There are scarce data in the literature on the effect of IVM on the expression of important development- and zona pellucida (ZP)–related genes in human oocytes; therefore, we wanted to determine this. One hundred nine human oocytes were collected from patients enrolled in an intracytoplasmic sperm injection program. The expression of the BMP4, GDF9, ZP1, ZP2, ZP3, and ZP4 genes was analyzed using RT–qPCR in oocytes matured in vitro with different reproductive hormones in the IVM medium (AMH, FSH + hCG, FSH + hCG + AMH), in in vivo matured oocytes and in immature oocytes with GVs. No statistically significant differences in the expression of selected genes in oocytes were observed among groups with different reproductive hormones in IVM medium. However, several interesting significant correlations were found between BMP4 and GDF9, and ZP1 and ZP4; between GDF9 and ZP1, and ZP2 and ZP4; and between ZP1 and ZP3 and ZP4 in the in vitro matured oocytes, while no such correlations were present in other groups of oocytes. The type of reproductive hormone in the maturation medium does not affect the expression of the analyzed genes in oocytes during the maturation process. However, the in vitro maturation procedure itself generated correlations among analyzed genes that were otherwise not present in in vivo matured and immature oocytes. [ABSTRACT FROM AUTHOR]

Abstract While CRISPR‐Cas defence mechanisms have been studied on a population level, their temporal dynamics and variability in individual cells have remained unknown. Using a microfluidic device, time‐lapse microscopy and mathematical modelling, we studied invader clearance in Escherichia coli across multiple generations. We observed that CRISPR interference is fast with a narrow distribution of clearance times. In contrast, for invaders with escaping PAM mutations we found large cell‐to‐cell variability, which originates from primed CRISPR adaptation. Faster growth and cell division and higher levels of Cascade increase the chance of clearance by interference, while slower growth is associated with increased chances of clearance by priming. Our findings suggest that Cascade binding to the mutated invader DNA, rather than spacer integration, is the main source of priming heterogeneity. The highly stochastic nature of primed CRISPR adaptation implies that only subpopulations of bacteria are able to respond quickly to invading threats. We conjecture that CRISPR‐Cas dynamics and heterogeneity at the cellular level are crucial to understanding the strategy of bacteria in their competition with other species and phages.

The shrinkage of bamboo can be traced to the cellular scale; however, research on the shrinkage of bamboo cells' scale is rare. This gap primarily arises from the intrinsic heterogeneity of biomass materials, leading to significant differences in the shrinkage behaviors of bamboo cells. Consequently, conventional measurement and analysis techniques struggle to obtain comprehensive and accurate results. To fill in this gap, this study investigated the dynamic shrinking behavior of individual bamboo cells, including fiber cells and parenchyma cells, using time-lapse microscopy and machine-learning techniques. Time-lapse observations revealed that the shrinkage rate of fiber cells across the cross-section surpassed that of parenchyma cells, accompanied by a greater shrinkage deformation. Specifically, fiber cells exhibited a shrinkage rate of 2.53 %/min, whereas parenchyma cells showed a rate of 0.58 %/min. This resulted in corresponding diameter reductions of approximately −30 % and −7 %, respectively. Additionally, machine-learning results demonstrated the efficacy of the trained long short-term memory (LSTM) model in accurately predicting morphological changes in individual parenchyma cells during the shrinkage process. This study advances understanding of bamboo-moisture interaction mechanisms and offers crucial theoretical data for improving bamboo drying and minimizing crack formation. • The shrinkage behavior of bamboo cells was studied using time-lapse microscopy and machine learning. • Fiber cells shrink faster and deform greater than those of parenchyma cells. • LSTM model accurately predicts the morphological changes of parenchyma cells during the shrinkage process. [ABSTRACT FROM AUTHOR]

Abstract Background Recently, the combination of deep learning and time-lapse imaging provides an objective, standard and scientific solution for embryo selection. However, the reported studies were based on blastocyst formation or clinical pregnancy as the end point. To the best of our knowledge, there is no predictive model that uses the outcome of live birth as the predictive end point. Can a deep learning model predict the probability of live birth from time-lapse system? Methods This study retrospectively analyzed the time-lapse data and live birth outcomes of embryos samples from January 2018 to November 2019. We used the SGD optimizer with an initial learning rate of 0.025 and cosine learning rate reduction strategy. The network is randomly initialized and trained for 200 epochs from scratch. The model is quantitively evaluated over a hold-out test and a 5-fold cross-validation by the average area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Results The deep learning model was able to predict live birth outcomes from time-lapse images with an AUC of 0.968 in 5-fold stratified cross-validation. Conclusions This research reported a deep learning model that predicts the live birth outcome of a single blastocyst transfer. This efficient model for predicting the outcome of live births can automatically analyze the time-lapse images of the patient’s embryos without the need for manual embryo annotation and evaluation, and then give a live birth prediction score for each embryo, and sort the embryos by the predicted value.

Background: Recently, the combination of deep learning and time-lapse imaging provides an objective, standard and scientific solution for embryo selection. However, the reported studies were based on blastocyst formation or clinical pregnancy as the end point. To the best of our knowledge, there is no predictive model that uses the outcome of live birth as the predictive end point. Can a deep learning model predict the probability of live birth from time-lapse system?Methods: This study retrospectively analyzed the time-lapse data and live birth outcomes of embryos samples from January 2018 to November 2019. We used the SGD optimizer with an initial learning rate of 0.025 and cosine learning rate reduction strategy. The network is randomly initialized and trained for 200 epochs from scratch. The model is quantitively evaluated over a hold-out test and a 5-fold cross-validation by the average area under the curve (AUC) of the receiver operating characteristic (ROC) curve.Results: The deep learning model was able to predict live birth outcomes from time-lapse images with an AUC of 0.968 in 5-fold stratified cross-validation.Conclusions: This research reported a deep learning model that predicts the live birth outcome of a single blastocyst transfer. This efficient model for predicting the outcome of live births can automatically analyze the time-lapse images of the patient's embryos without the need for manual embryo annotation and evaluation, and then give a live birth prediction score for each embryo, and sort the embryos by the predicted value. [ABSTRACT FROM AUTHOR]

The enhancement of photodynamic therapy (PDT) effectiveness by combining it with other treatment modalities and improved drug delivery has become an interesting field in cancer research. We have prepared and characterized nanoliposomes containing the chemotherapeutic drug irinotecan (CPT11lip), the photodynamic agent protoporphyrin IX (PpIXlip), or their combination (CPT11-PpIXlip). The effects of individual and bimodal (chemo-phototherapeutic) treatments on HeLa cells have been studied by a combination of biological and photophysical studies. Bimodal treatments show synergistic cytotoxic effects on HeLa cells at relatively low doses of PpIX/PDT and CPT11. Mechanistic cell inactivation studies revealed mitotic catastrophe, apoptosis, and senescence contributions. The enhanced anticancer activity is due to a sustained generation of reactive oxygen species, which increases the number of double-strand DNA breaks. Bimodal chemo-phototherapeutic liposomes may have a very promising future in oncological therapy, potentially allowing a reduction in the CPT11 concentration required to achieve a therapeutic effect and overcoming resistance to individual cancer treatments. [ABSTRACT FROM AUTHOR]

Does oocyte immaturity rate affect morphokinetic events in a time-lapse imaging (TLI) system? Historical cohort study carried out in a private university-affiliated IVF centre. Injected oocytes (n = 3368) cultured in a TLI incubator, from intracytoplasmic sperm injection (ICSI) cycles (n = 474) carried out between March 2019 and December 2020, were analysed. The effects of immature oocyte rates (the number of germinal-vesicle and metaphase I oocytes by the number of retrieved oocytes in each cycle, on morphokinetic events) were investigated considering clustering of data using mixed models. Evaluated kinetic markers were pronuclei appearance (tPNa), timing to pronuclei fading (tPNf), timing to two (t2), three (t3), four (t4), five (t5), six (t6), seven (t7), and eight cells (t8), timing to morulae (tM) and timing to start of blastulation (tSB) and to blastulation (tB). Durations of the second (t3-t2) and third (t5-t3) cell cycles (cc2 and cc3, respectively) and timing to complete synchronous divisions s1 (t2-tPNf), s2 (t4-t3) and s3 (t8-t5) were also evaluated. Positive relationships were observed between oocyte immaturity rates and slower tPNa, tPNf, t2, t3, t4, t5, t6, t7, t8, tSB, tB and cc3. Multinucleation at two- and four-cell stages were positively correlated with oocyte immaturity rate. The KIDScore ranking was negatively correlated with oocyte immaturity rate. No associations were found between oocyte immaturity rate and clinical outcomes. Increasing oocyte immaturity rate correlates with delayed cell cleavage and blastulation. These findings highlight the importance of TLI for the identification and de-selection of slow-growing embryos for transfer, in cycles with high oocyte immaturity rate. [ABSTRACT FROM AUTHOR]

Study Question: Can more reliable time cut-offs of embryo developmental incompetence be generated by combining time-lapse technology (TLT), artificial intelligence, and preimplantation genetics screening for aneuploidy (PGT-A)?, Summary Answer: Embryo developmental incompetence can be better predicted by time cut-offs at multiple developmental stages and for different ranges of maternal age., What Is Known Already: TLT is instrumental for the continual and undisturbed observation of embryo development. It has produced morphokinetic algorithms aimed at selecting embryos able to generate a viable pregnancy, however, such efforts have had limited success. Regardless, the potential of this technology for improving multiple aspects of the IVF process remains considerable. Specifically, TLT could be harnessed to discriminate developmentally incompetent embryos: i.e. those unable to develop to the blastocyst stage or affected by full-chromosome meiotic aneuploidies. If proven valuable, this application would prevent the non-productive use of such embryos, thereby improving laboratory and clinical efficiency and reducing patient stress and costs due to unnecessary embryo transfer and cryopreservation., Study Design, Size, Duration: The training dataset involved embryos of PGT-A cycles cultured in Embryoscope with a single media (836 euploid and 1179 aneuploid blastocysts and 1874 arrested embryos; 2013-2020). Selection criteria were ejaculated sperm, own (not donated) fresh oocytes, trophectoderm biopsy and comprehensive-chromosome-testing to diagnose uniform aneuploidies. Out-of-sample (30% of training), internal (299 euploid and 490 aneuploid blastocysts and 680 arrested embryos; 2021-2022) and external (97 euploid, 110 aneuploid and 603 untested blastocysts and 514 arrested embryos, 2018 to early 2022) validations were conducted., Participants/materials, Setting, Methods: A training dataset (70%) was used to define thresholds. Several models were generated by fitting outcomes to each timing (tPNa-t8) and maternal age. ROC curves pinpointed in-sample classification values associated with 95%, 99% and 99.99% true-positive rate for predicting incompetence. These values were integrated with upper limits of maternal age ranges (<35, 35-37, 38-40, 41-42, and >42 years) in logit functions to identify time cut-offs, whose accuracy was tested on the validation datasets through confusion matrices., Main Results and the Role of Chance: For developmental (in)competence, the best performing (i) tPNa cut-offs were 27.8 hpi (error-rate: 0/743), 32.6 hpi (error rate: 0/934), 26.8 hpi (error rate: 0/1178), 22.9 hpi (error-rate: 1/654, 0.1%) and 17.2 hpi (error rate: 4/423, 0.9%) in the <35, 35-37, 38-40, 41-42, and >42 years groups, respectively; (ii) tPNf cut-offs were 36.7 hpi (error rate: 0/738), 47.9 hpi (error rate: 0/921), 45.6 hpi (error rate: 1/1156, 0.1%), 44.1 hpi (error rate: 0/647) and 41.8 hpi (error rate: 0/417); (iii) t2 cut-offs were 50.9 hpi (error rate: 0/724), 49 hpi (error rate: 0/915), 47.1 hpi (error rate: 0/1146), 45.8 hpi (error rate: 0/636) and 43.9 hpi (error rate: 0/416); (iv) t4 cut-offs were 66.9 hpi (error rate: 0/683), 80.7 hpi (error rate: 0/836), 77.1 hpi (error rate: 0/1063), 74.7 hpi (error rate: 0/590) and 71.2 hpi (error rate: 0/389); and (v) t8 cut-offs were 118.1 hpi (error rate: 0/619), 110.6 hpi (error rate: 0/772), 140 hpi (error rate: 0/969), 135 hpi (error rate: 0/533) and 127.5 hpi (error rate: 0/355). tPNf and t2 showed a significant association with chromosomal (in)competence, also when adjusted for maternal age. Nevertheless, the relevant cut-offs were found to perform less well and were redundant compared with the blastocyst development cut-offs., Limitations, Reasons for Caution: Study limits are its retrospective design and the datasets being unbalanced towards advanced maternal age cases. The potential effects of abnormal cleavage patterns were not assessed. Larger sample sizes and external validations in other clinical settings are warranted., Wider Implications of the Findings: If confirmed by independent studies, this approach could significantly improve the efficiency of ART, by reducing the workload and patient impacts (extended culture and cleavage stage cryopreservation or transfer) associated with embryos that ultimately are developmentally incompetent and should not be considered for treatment. Pending validation, these data might be applied also in static embryo observation settings., Study Funding/competing Interest(s): This study was supported by the participating institutions. The authors have no conflicts of interest to declare., Trial Registration Number: N/A., (© The Author(s) 2024. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Abstract Background Time-lapse microscopy live-cell imaging is essential for studying the evolution of bacterial communities at single-cell resolution. It allows capturing detailed information about the morphology, gene expression, and spatial characteristics of individual cells at every time instance of the imaging experiment. The image analysis of bacterial "single-cell movies" (videos) generates big data in the form of multidimensional time series of measured bacterial attributes. If properly analyzed, these datasets can help us decipher the bacterial communities' growth dynamics and identify the sources and potential functional role of intra- and inter-subpopulation heterogeneity. Recent research has highlighted the importance of investigating the role of biological "noise" in gene regulation, cell growth, cell division, etc. Single-cell analytics of complex single-cell movie datasets, capturing the interaction of multiple micro-colonies with thousands of cells, can shed light on essential phenomena for human health, such as the competition of pathogens and benign microbiome cells, the emergence of dormant cells (“persisters”), the formation of biofilms under different stress conditions, etc. However, highly accurate and automated bacterial bioimage analysis and single-cell analytics methods remain elusive, even though they are required before we can routinely exploit the plethora of data that single-cell movies generate. Results We present visualization and single-cell analytics using R (ViSCAR), a set of methods and corresponding functions, to visually explore and correlate single-cell attributes generated from the image processing of complex bacterial single-cell movies. They can be used to model and visualize the spatiotemporal evolution of attributes at different levels of the microbial community organization (i.e., cell population, colony, generation, etc.), to discover possible epigenetic information transfer across cell generations, infer mathematical and statistical models describing various stochastic phenomena (e.g., cell growth, cell division), and even identify and auto-correct errors introduced unavoidably during the bioimage analysis of a dense movie with thousands of overcrowded cells in the microscope's field of view. Conclusions ViSCAR empowers researchers to capture and characterize the stochasticity, uncover the mechanisms leading to cellular phenotypes of interest, and decipher a large heterogeneous microbial communities' dynamic behavior. ViSCAR source code is available from GitLab at https://gitlab.com/ManolakosLab/viscar .

During renewal of the intestine, cells are continuously generated by proliferation. Proliferation and differentiation must be tightly balanced, as any bias toward proliferation results in uncontrolled exponential growth. Yet, the inherently stochastic nature of cells raises the question how such fluctuations are limited. We used time-lapse microscopy to track all cells in crypts of growing mouse intestinal organoids for multiple generations, allowing full reconstruction of the underlying lineage dynamics in space and time. Proliferative behavior was highly symmetric between sister cells, with both sisters either jointly ceasing or continuing proliferation. Simulations revealed that such symmetric proliferative behavior minimizes cell number fluctuations, explaining our observation that proliferating cell number remained constant even as crypts increased in size considerably. Proliferative symmetry did not reflect positional symmetry but rather lineage control through the mother cell. Our results indicate a concrete mechanism to balance proliferation and differentiation with minimal fluctuations that may be broadly relevant for other tissues.

Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.

Mitochondria form highly dynamic populations in the cells of plants (and almost all eukaryotes). The characteristics and benefits of this collective behaviour, and how it is influenced by nuclear features, remain to be fully elucidated. Here, we use a recently developed quantitative approach to reveal and analyse the physical and collective 'social' dynamics of mitochondria in an Arabidopsis msh1 mutant where the organelle DNA maintenance machinery is compromised. We use a newly created line combining the msh1 mutant with mitochondrially targeted green fluorescent protein (GFP), and characterize mitochondrial dynamics with a combination of single-cell time-lapse microscopy, computational tracking, and network analysis. The collective physical behaviour of msh1 mitochondria is altered from that of the wild type in several ways: mitochondria become less evenly spread, and networks of inter-mitochondrial encounters become more connected, with greater potential efficiency for inter-organelle exchange—reflecting a potential compensatory mechanism for the genetic challenge to the mitochondrial DNA population, supporting more inter-organelle exchange. We find that these changes are similar to those observed in friendly , where mitochondrial dynamics are altered by a physical perturbation, suggesting that this shift to higher connectivity may reflect a general response to mitochondrial challenges, where physical dynamics of mitochondria may be altered to control the genetic structure of the mtDNA population. [ABSTRACT FROM AUTHOR]

The effects of electric fields (EFs) on various cell types have been thoroughly studied, and exhibit a well-known regulatory effect on cell processes, implicating their usage in several medical applications. While the specific effect exerted on cells is highly parameter-dependent, the majority of past research has focused primarily on low-frequency alternating fields (<1 kHz) and high-frequency fields (in the order of MHz). However, in recent years, low-intensity (1–3 V/cm) alternating EFs with intermediate frequencies (100–500 kHz) have been of topical interest as clinical treatments for cancerous tumours through their disruption of cell division and the mitotic spindle, which can lead to cell death. These aptly named tumour-treating fields (TTFields) have been approved by the FDA as a treatment modality for several cancers, such as malignant pleural mesothelioma and glioblastoma multiforme, demonstrating remarkable efficacy and a high safety profile. In this work, we report the results of in vitro experiments with HeLa and MCF-10A cells exposed to TTFields for 18 h, imaged in real time using live-cell imaging. Both studied cell lines were exposed to 100 kHz TTFields with a 1-1 duty cycle, which resulted in significant mitotic and cytokinetic arrest. In the experiments with HeLa cells, the effects of the TTFields' frequency (100 kHz vs. 200 kHz) and duty cycle (1-1 vs. 1-0) were also investigated. Notably, the anti-mitotic effect was stronger in the HeLa cells treated with 100 kHz TTFields. Additionally, it was found that single and two-directional TTFields (oriented orthogonally) exhibit a similar inhibitory effect on HeLa cell division. These results provide real-time evidence of the profound ability of TTFields to hinder the process of cell division by significantly delaying both the mitosis and cytokinesis phases of the cell cycle. [ABSTRACT FROM AUTHOR]

The phase separation and aggregation of proteins are hallmarks of many neurodegenerative diseases. These processes can be studied in living cells using fluorescent protein constructs and quantitative live-cell imaging techniques, such as fluorescence recovery after photobleaching (FRAP) or the related fluorescence loss in photobleaching (FLIP). While the acquisition of FLIP images is straightforward on most commercial confocal microscope systems, the analysis and computational modeling of such data is challenging. Here, a novel model-free method is presented, which resolves complex spatiotemporal fluorescence-loss kinetics based on dynamic-mode decomposition (DMD) of FLIP live-cell image sequences. It is shown that the DMD of synthetic and experimental FLIP image series (DMD-FLIP) allows for the unequivocal discrimination of subcellular compartments, such as nuclei, cytoplasm, and protein condensates based on their differing transport and therefore fluorescence loss kinetics. By decomposing fluorescence-loss kinetics into distinct dynamic modes, DMD-FLIP will enable researchers to study protein dynamics at each time scale individually. Furthermore, it is shown that DMD-FLIP is very efficient in denoising confocal time series data. Thus, DMD-FLIP is an easy-to-use method for the model-free detection of barriers to protein diffusion, of phase-separated protein assemblies, and of insoluble protein aggregates. It should, therefore, find wide application in the analysis of protein transport and aggregation, in particular in relation to neurodegenerative diseases and the formation of protein condensates in living cells. [ABSTRACT FROM AUTHOR]

Tumor invasion is strongly influenced by microenvironment and, among other parameters, chemical stimuli play an important role. An innovative methodology for the quantitative investigation of chemotaxis in vitro by live imaging of morphology of cell spheroids, in 3D collagen gel, is presented here. The assay was performed by using a chemotactic chamber to impose a controlled gradients of nutrients (glucose) on spheroids, mimicking the chemotactic stimuli naturally occurring in the proximity of blood vessels. Different tumoral cell lines (PANC‐1 and HT‐1080) are compared to non‐tumoral ones (NIH/3T3). Morphology response is observed by means a Time‐lapse workstation equipped with an incubating system and quantified by image analysis techniques. Description of invasion phenomena was based on an engineering approach, based on transport phenomena concepts. As expected, NIH/3T3 spheroids are characterized by a limited tendency of cells to invade the surrounding tissue, unlike PANC‐1 and HT‐1080 that show relatively stronger response to gradients. [ABSTRACT FROM AUTHOR]

Time-lapse fluorescence imaging coupled to micro-irradiation devices provides information on the kinetics of DNA repair protein accumulation, from a few seconds to several minutes after irradiation. Charged-particle microbeams are valuable tools for such studies since they provide a way to selectively irradiate micrometric areas within a cell nucleus, control the dose and the micro-dosimetric quantities by means of advanced detection systems and Monte Carlo simulations and monitor the early cell response by means of beamline microscopy. We used the charged-particle microbeam installed at the AIFIRA facility to perform micro-irradiation experiments and measure the recruitment kinetics of two proteins involved in DNA signaling and repair pathways following exposure to protons and α-particles. We developed and validated image acquisition and processing methods to enable a systematic study of the recruitment kinetics of GFP-XRCC1 and GFP-RNF8. We show that XRCC1 is recruited to DNA damage sites a few seconds after irradiation as a function of the total deposited energy and quite independently of the particle LET. RNF8 is recruited to DNA damage sites a few minutes after irradiation and its recruitment kinetics depends on the particle LET.

[Display omitted] • Heterogeneity in growth is increased when cells recover from sublethal stresses. • After exposure to 30 ppm PAA and AA pH 2.5 phenotypic variance is induced. • The stochastic model for PAA treated cells showed increased population heterogeneity after 24 h. Studies of classical microbiology rely on the average behaviour of large cell populations without considering that clonal bacterial populations may bifurcate into phenotypic distinct sub-populations by random switching mechanisms. Listeria monocytogenes exposure to sublethal stresses may induce different physiological states that co-exist (i.e., sublethal injury or dormancy) and present variable resuscitation capacity. Exposures to peracetic acid (PAA; 10–30 ppm; for 3 h), acetic acid and hydrochloric acid (AA and HCl; pH 3.0–2.5; for 5 h) at 20 °C were used to induce different physiological states in L. monocytogenes , Scott A strain. After stress exposure, colony growth of single cells was monitored, on Tryptic Soy Agar supplemented with 0.6 % Yeast Extract, using time-lapse microscopy, at 37 °C. Images were acquired every 5 min and were analyzed using BaSCA framework. Most of the obtained growth curves of the colonies were fitted to the model of Baranyi and Roberts for the estimation of lag time (λ) and maximum specific growth rate (μ max), except the ones obtained after exposure to AA pH 2.7 and 2.5 that were fitted to the Trilinear model. The data of λ and μ max that followed a multivariate normal distribution were used to predict growth variability using Monte Carlo simulations. Outgrowth kinetics after treatment with AA (pH 2.7 and 2.5; for 5 h at 20 °C), PAA (30 ppm; for 3 h at 20 °C) revealed that these stress conditions increase the skewness of the variability distributions to the right, meaning that the variability in lag times increases in favour of longer outgrowth. Exposures to AA pH 2.5 and 30 ppm PAA resulted in two distinct subpopulations per generation with different growth dynamics. This switching mechanism may have evolved as a survival strategy for L. monocytogenes cells, maximizing the chances of survival. Simulation of microbial growth showed that heterogeneity in growth dynamics is increased when cells are recovering from exposure to sublethal stresses (i.e. PAA and acidic conditions) that may induce injury or dormancy. [ABSTRACT FROM AUTHOR]

While phototoxicity can be a useful therapeutic modality not only for eliminating malignant cells but also in treating fungal infections, mycologists aiming to observe morphological changes or molecular events in fungi, especially when long observation periods or high light fluxes are warranted, encounter problems owed to altered regulatory pathways or even cell death caused by various photosensing mechanisms. Consequently, the ever expanding repertoire of visible fluorescent protein toolboxes and high-resolution microscopy methods designed to investigate fungi in vitro and in vivo need to comply with an additional requirement: to decrease the unwanted side effects of illumination. In addition to optimizing exposure, an obvious solution is red-shifted illumination, which, however, does not come without compromises. This review summarizes the interactions of fungi with light and the various molecular biology and technology approaches developed for exploring their functions on the molecular, cellular, and in vivo microscopic levels, and outlines the progress towards reducing phototoxicity through applying far-red and near-infrared light. Key points: • Fungal biological processes alter upon illumination, also under the microscope • Red shifted fluorescent protein toolboxes decrease interference by illumination • Innovations like two-photon, lightsheet, and near IR microscopy reduce phototoxicity [ABSTRACT FROM AUTHOR]

While CRISPR‐Cas defence mechanisms have been studied on a population level, their temporal dynamics and variability in individual cells have remained unknown. Using a microfluidic device, time‐lapse microscopy and mathematical modelling, we studied invader clearance in Escherichia coli across multiple generations. We observed that CRISPR interference is fast with a narrow distribution of clearance times. In contrast, for invaders with escaping PAM mutations we found large cell‐to‐cell variability, which originates from primed CRISPR adaptation. Faster growth and cell division and higher levels of Cascade increase the chance of clearance by interference, while slower growth is associated with increased chances of clearance by priming. Our findings suggest that Cascade binding to the mutated invader DNA, rather than spacer integration, is the main source of priming heterogeneity. The highly stochastic nature of primed CRISPR adaptation implies that only subpopulations of bacteria are able to respond quickly to invading threats. We conjecture that CRISPR‐Cas dynamics and heterogeneity at the cellular level are crucial to understanding the strategy of bacteria in their competition with other species and phages. Synopsis: Time‐lapse microscopy combined with computational modeling reveals new insights into the single‐cell biology of CRISPR‐Cas defense during invader DNA clearance in E. coli. CRISPR adaptation and interference over multiple generations can be tracked using time‐lapse microscopy.Direct interference is fast and efficient, while priming shows large variations between cells.Slower cell growth leads to earlier spacer acquisition within a population.Mathematical modeling shows reduced Cascade binding affinity for the target drives variation between cells during priming. [ABSTRACT FROM AUTHOR]

FOXO transcription factors respond to a number of different stresses by shuttling from the cytoplasm to the nucleus where they upregulate hundreds of target genes with diverse cellular functions. The cellular consequences of FOXO activation are both stress and cell-type specific. Recent evidence suggests that one way in which FOXO dictates stress-specific outcomes is through distinct nuclear/cytoplasmic shuttling dynamics. Here we outline methods for measuring FOXO nuclear shuttling dynamics using fluorescence-based reporters., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

As they proliferate, living cells undergo transitions between specific molecularly and developmentally distinct states. Despite the functional centrality of these transitions in multicellular organisms, it has remained challenging to determine which transitions occur and at what rates without perturbations and cell engineering. Here, we introduce kin correlation analysis (KCA) and show that quantitative cell-state transition dynamics can be inferred, without direct observation, from the clustering of cell states on pedigrees (lineage trees). Combining KCA with pedigrees obtained from time-lapse imaging and endpoint single-molecule RNA-fluorescence in situ hybridization (RNA-FISH) measurements of gene expression, we determined the cell-state transition network of mouse embryonic stem (ES) cells. This analysis revealed that mouse ES cells exhibit stochastic and reversible transitions along a linear chain of states ranging from 2C-like to epiblast-like. Our approach is broadly applicable and may be applied to systems with irreversible transitions and non-stationary dynamics, such as in cancer and development.

Autophagosome maturation comprises fusion with lysosomes and acidification. It is a critical step in the degradation of cytosolic protein aggregates that characterize many neurodegenerative diseases. In order to better understand this process, we studied intracellular trafficking of autophagosomes and aggregates of α-synuclein, which characterize Parkinson's disease and other synucleinopathies. The autophagosomal marker LC3 and the aggregation prone A53T mutant of α-synuclein were tagged by fluorescent proteins and expressed in HEK293T cells and primary astrocytes. The subcellular distribution and movement of these vesicle populations were analyzed by (time-lapse) microscopy. Fusion with lysosomes was assayed using the lysosomal marker LAMP1; vesicles with neutral and acidic luminal pH were discriminated using the RFP-GFP "tandem-fluorescence" tag. With respect to vesicle pH, we observed that neutral autophagosomes, marked by LC3 or synuclein, were located more frequently in the cell center, and acidic autophagosomes were observed more frequently in the cell periphery. Acidic autophagosomes were transported towards the cell periphery more often, indicating that acidification occurs in the cell center before transport to the periphery. With respect to autolysosomal fusion, we found that lysosomes preferentially moved towards the cell center, whereas autolysosomes moved towards the cell periphery, suggesting a cycle where lysosomes are generated in the periphery and fuse to autophagosomes in the cell center. Unexpectedly, many acidic autophagosomes were negative for LAMP1, indicating that acidification does not require fusion to lysosomes. Moreover, we found both neutral and acidic vesicles positive for LAMP1, consistent with delayed acidification of the autolysosome lumen. Individual steps of aggregate clearance thus occur in dedicated cellular regions. During aggregate clearance, autophagosomes and autolysosomes form in the center and are transported towards the periphery during maturation. In this process, luminal pH could regulate the direction of vesicle transport. (1) Transport and location of autophagosomes depend on luminal pH: Acidic autophagosomes are preferentially transported to the cell periphery, causing more acidic autophagosomes in the cell periphery and more neutral autophagosomes at the microtubule organizing center (MTOC). (2) Autolysosomes are transported to the cell periphery and lysosomes to the MTOC, suggesting spatial segregation of lysosome reformation and autolysosome fusion. (3) Synuclein aggregates are preferentially located at the MTOC and synuclein-containing vesicles in the cell periphery, consistent with transport of aggregates to the MTOC for autophagy. [ABSTRACT FROM AUTHOR]

Cellular longevity is regulated by both genetic and environmental factors. However, the interactions of these factors in the context of aging remain largely unclear. Here, we formulate a mathematical model for dynamic glucose modulation of a core gene circuit in yeast aging, which not only guided the design of pro-longevity interventions but also revealed the theoretical principles underlying these interventions. We introduce the dynamical systems theory to capture two general means for promoting longevity-the creation of a stable fixed point in the "healthy" state of the cell and the "dynamic stabilization" of the system around this healthy state through environmental oscillations. Guided by the model, we investigate how both of these can be experimentally realized by dynamically modulating environmental glucose levels. The results establish a paradigm for theoretically analyzing the trajectories and perturbations of aging that can be generalized to aging processes in diverse cell types and organisms., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Given the importance of embryo developmental competence assessment in reproductive medicine and biology, the aim of this study was to compare the performance of fertilization and cleavage morphokinetics with embryo morphology to predict post-ICSI live birth. Data from embryos cultured in a time-lapse microscopy (TLM) incubator and with known live birth outcomes (LB: embryos achieving live birth, n = 168; NLB: embryos not achieving live birth, n = 1633) were used to generate receiver operating characteristic (ROC) curves based on morphokinetic or morphological scores, and the respective areas under the curve (AUC) were compared. The association between live birth and 12 combinations of four morphokinetic quality degrees (A–D) with three morphological quality degrees (A–C) was assessed using multivariate analysis. Morphokinetic parameters from tPNa to t8 were reached earlier in LB compared with NLB embryos. The ROC curve analysis indicated that morphokinetic information is more accurate than conventional morphology to predict live birth [AUC = 0.64 (95% CI 0.58–0.70) versus AUC = 0.58 (95% CI 0.51–0.65)]. The multivariate analysis was in line with AUCs, revealing that embryos with poor morphokinetics, independently of their morphology, provide lower live birth rates (P < 0.001). A considerable percentage of embryos with top morphology presented poor morphokinetics (20.10%), accompanied by a severely reduced live birth rate in comparison with embryos with top morphology and morphokinetics (P < 0.001). In conclusion, TLM-derived early morphokinetic parameters were more predictive of live-birth achievement following ICSI than conventional morphology. [ABSTRACT FROM AUTHOR]