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| Autor principal: | |
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
| Publicado: |
Zenodo
2026
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| Materias: | |
| Acceso en línea: | https://doi.org/10.5281/zenodo.18176996 |
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- <p><span><span>Pancreatic β-cells </span><span>contain</span><span> insulin secretory granules (ISGs), organelles where proinsulin is converted into insulin. As ISGs mature, they undergo extensive biophysical remodeling, producing a spectrum of subpopulations with heterogeneous molecular and spatial characteristics. However, systematic methods to define ISG subpopulations </span><span>remain</span><span> underdeveloped. To address this gap in knowledge, we employed soft x-ray tomography (SXT), which can quantitatively measure the biochemical density of ISGs within whole β-cells. Using unsupervised clustering, we classified subpopulations based on molecular density, size, and spatial positioning. Across different insulin secretory stimuli, we </span><span>observed</span><span> shifts towards mature and releasable subtypes, </span><span>demonstrating</span><span> that exogenous signals can dynamically remodel ISG subpopulation distributions. We extended this </span><span>methodology</span><span> to</span><span> primary</span><span> β-cells characterized using volume electron microscopy</span><span> </span><span>(</span><span>vEM</span><span>). Integrating subpopulations from SXT and </span><span>vEM</span><span> uncovered insights </span><span>inaccessible</span><span> by a single method in isolation. This strategy </span><span>establishes</span><span> a framework for defining therapeutic approaches aimed at enriching physiologically beneficial ISG subpopulations.</span></span><span> </span></p>