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Morphokinetic Analyses of Fishing Cat-Domestic Cat Interspecies Somatic Cell Nuclear Transfer Embryos Through A Time-Lapse System.
Animals (Basel)
January 2025
Endangered Species Conservation via Assisted Reproduction (ESCAR) Lab, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Proteos, Singapore 138673, Singapore.
A time-lapse live embryo monitoring system provides a powerful approach to recording dynamic developmental events of cultured embryos in detail. By obtaining continuous short-interval images, blastocyst formation can be predicted and embryos can be selected. The objective of this study was to investigate the morphokinetic parameters of fishing cat-domestic cat interspecies somatic cell nuclear transfer (iSCNT) embryos from one-cell to blastocyst stages, and in particular, the cleavage patterns of the first division in iSCNT and IVF embryos, as these play a central role in euploidy.
View Article and Find Full Text PDFAssessing gut barrier integrity and reproductive performance following pre-mating oral administration of solid-lipid-nanoparticles designed for drug delivery.
Front Toxicol
January 2025
Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
Solid lipid nanoparticles (SLNs) have gained interest as drug delivery carriers due to their efficient cellular internalization and increased therapeutic effect of the loaded drug, with minimal side effects. Although recently several studies have shown the possibility to administer SLNs during pregnancy to vehicle mRNA to the placenta, data about the effect of premating exposure to SLNs on pregnancy outcome are scant. Considering that assumption of drug-delivering nanocarriers in reproductive age may potentially affect women's reproductive health, the aim of the present study was to evaluate whether repeated oral administration of SLNs to female mice prior to mating would influence key pregnancy outcomes.
View Article and Find Full Text PDFRecording Lineage History with Cellular Barcodes in the Mammary Epithelium and in Breast Cancer.
Adv Exp Med Biol
January 2025
Laboratory of Genetics and Developmental Biology, Institut Curie, INSERM U934, CNRS UMR3215, Paris, France.
Lineage tracing methods have extensively advanced our understanding of physiological cell behaviour in vivo and in situ and have vastly contributed to decipher the phylogeny and cellular hierarchies during normal and tumour development. In recent years, increasingly complex systems have been developed to track thousands of cells within a given tissue or even entire organisms. Cellular barcoding comprises all techniques designed to genetically label single cells with unique DNA sequences or with a combination of fluorescent proteins, in order to trace their history and lineage production in space and time.
View Article and Find Full Text PDFWarming associated with climate change is driving poleward shifts in the marine habitat of anadromous Pacific salmon ( spp.). Yet the spawning locations for salmon to establish self-sustaining populations and the consequences for the ecosystem if they should do so are unclear.
View Article and Find Full Text PDFInferring metabolic objectives and trade-offs in single cells during embryogenesis.
Cell Syst
January 2025
Center for Bioinformatics and Computational Medicine, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address:
While proliferating cells optimize their metabolism to produce biomass, the metabolic objectives of cells that perform non-proliferative tasks are unclear. The opposing requirements for optimizing each objective result in a trade-off that forces single cells to prioritize their metabolic needs and optimally allocate limited resources. Here, we present single-cell optimization objective and trade-off inference (SCOOTI), which infers metabolic objectives and trade-offs in biological systems by integrating bulk and single-cell omics data, using metabolic modeling and machine learning.
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