The integration of Machine Learning (ML) with super-resolution microscopy represents a transformative advancement in biomedical research. Recent advances in ML, particularly deep learning (DL), have significantly enhanced image processing tasks, such as denoising and reconstruction. This review explores the growing potential of automation in super-resolution microscopy, focusing on how DL can enable autonomous imaging tasks.
View Article and Find Full Text PDFThe Antarctic seabed harbors significant biodiversity, and almost 90% of oceanic environments are permanently below 5 °C (i.e., deep sea and polar regions).
View Article and Find Full Text PDFBackground: Whole blood (WB) resuscitation has been shown to provide mortality benefit. However, the impact of whole blood transfusions on the risk of venous thromboembolism (VTE) remains unclear. We sought to compare the VTE risk in patients resuscitated with WB vs component therapy (COMP).
View Article and Find Full Text PDFMembrane-less compartments and organelles are widely acknowledged for their role in regulating cellular processes, and there is an urgent need to harness their full potential as both structural and functional elements of synthetic cells. Despite rapid progress, synthetically recapitulating the nonequilibrium, spatially distributed responses of natural membrane-less organelles remains elusive. Here, we demonstrate that the activity of nucleic-acid cleaving enzymes can be localized within DNA-based membrane-less compartments by sequestering the respective DNA or RNA substrates.
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