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| Zdroj: |
Medical Imaging Week; 6/10/2024, p814-814, 1p |
| Abstrakt: |
A new study conducted by researchers at the University of Southern California explores the dysfunction of a and b cells in pancreatic islets, which can lead to diabetes. The researchers developed a subcellular feature-based classification approach using soft X-ray tomography (SXT) to identify and quantify the structural characteristics of these cells. They observed significant differences in morphology and organelle statistics between the two cell types and were able to predict cell types using supervised machine learning. The study also utilized Uniform Manifold Approximation and Projection (UMAP) embeddings to visualize distinct vesicle and cell subtypes, providing a new approach to exploring structural heterogeneity in islet cells. This research presents an innovative method for tracking heterogeneity in cells that can be applied to any cellular system. [Extracted from the article] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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