Saved in:
| Main Author: | |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
|
| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.18176996 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866902256558800896 |
|---|---|
| author | Chang, Kevin |
| author_facet | Chang, Kevin |
| contents | <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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18176996 |
| institution | Zenodo |
| language | eng |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Classifying Biophysical Subpopulations of Insulin Secretory Granules using Quantitative Whole Cell Structure Analysis Chang, Kevin soft X-ray tomography insulin secretory granule whole-cell imaging dense-core granules pancreatic beta cell <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> |
| title | Classifying Biophysical Subpopulations of Insulin Secretory Granules using Quantitative Whole Cell Structure Analysis |
| topic | soft X-ray tomography insulin secretory granule whole-cell imaging dense-core granules pancreatic beta cell |
| url | https://doi.org/10.5281/zenodo.18176996 |