Publications by authors named "S M Shvartsman"
A lack of tools for detecting receptor activity has limited our ability to fully explore receptor-level control of developmental patterning. Here, we extend a new class of biosensors for receptor tyrosine kinase (RTK) activity, the pYtag system, to visualize endogenous RTK activity in . We build biosensors for three RTKs that function across developmental stages and tissues.
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- Researchers studied how gametes (reproductive cells) develop in clusters called cysts, which are formed from germ cells connected by intercellular bridges that allow them to share materials.
- They used advanced live imaging techniques to observe the movement and behavior of these germ cells in their natural environment, revealing how their motility contributes to the formation and breaking of these cysts during embryonic development.
- The study suggests a balance between cell movement and the stability of intercellular connections determines the size of cysts, with implications for understanding how oocytes (egg cells) are selected and the overall female reproductive system development.
Article Synopsis
- Gastrulation is a vital embryonic development process that changes a simple blastula into a complex embryo with various germ layers that form tissues and organs.
- Research has revealed key mechanisms behind the movements involved in gastrulation, focusing on how cells change shape and position during this transformation.
- The study introduces a method for measuring strain tensors to analyze these cell movements, successfully applying it to identify specific morphological domains in Drosophila (fruit flies) relevant to gastrulation.
For investigations into fate specification and morphogenesis in time-lapse images of preimplantation embryos, automated 3D instance segmentation and tracking of nuclei are invaluable. Low signal-to-noise ratio, high voxel anisotropy, high nuclear density, and variable nuclear shapes can limit the performance of segmentation methods, while tracking is complicated by cell divisions, low frame rates, and sample movements. Supervised machine learning approaches can radically improve segmentation accuracy and enable easier tracking, but they often require large amounts of annotated 3D data.
View Article and Find Full Text PDFHabituation-a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld-is universally observed in living systems from animals to unicellular organisms. Despite its prevalence, generic mechanisms for this fundamental form of learning remain poorly defined. Drawing inspiration from prior work on systems that respond adaptively to step inputs, we study habituation from a nonlinear dynamics perspective.
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