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An Efficient Deep Learning Model For Single-Cell Segmentation And Tracking In Time-Lapse Microscopy

Time-lapse microscopy allows for direct observation of cell biological processes at the single-cell level with high temporal resolution. Quantitative analysis of single-cell time-lapse microscopy requires automated segmentation and tracking of individual cells over several days. Precise segmentation and tracking remain challenging because cells change their shape, divide, and show unpredictable movements.Researchers at UC Santa Cruz applied recent advances in the application of deep-learning models to the analysis of cellular images. The result was a deep-learning-based model and a user-friendly software, termed DeepSea, that automates both the segmentation and tracking of individual cells in time-lapse microscopy images.

Novel Cytomegalovirus Vaccine

Brief description not available

Antibody-Based Chemically Induced Dimerizers (AbCIDs)

This novel technology enables refined temporal control of protein-protein interactions that can be used to regulate cell therapies, including CAR T-cells and “cell factories”.

Novel Methods For Chemical Synthesis Of Lactosyl Sphingosines, Glucosylsphingosines, Galactosylsphingosines, And 3-O-Sulfogalactosylsphingosines

Researchers at the University of California, Davis, have developed new synthesis methods for the rapid and highly pure production of glycosphingolipids. The prototyped process can produce pure glycosphingolipids that can be used within basic disease research and drug and diagnostic development.

Novel CAR-T Therapy for Glioblastoma

Brief description not available