Adipocyte-derived extracellular vesicles regulate survival and function of pancreatic β cells
Bibliographic record
Abstract
Extracellular vesicles (EVs) are implicated in the crosstalk between adipocytes and other metabolic organs, and an altered biological cargo has been observed in EVs from human obese adipose tissue (AT). Yet, the role of adipocyte-derived EVs in pancreatic β cells remains to be determined. Here, we explored the effects of EVs released from adipocytes isolated from both rodents and humans and human AT explants on survival and function of pancreatic β cells and human pancreatic islets. EVs from healthy 3T3-L1 adipocytes increased survival and proliferation and promoted insulin secretion in INS-1E β cells and human pancreatic islets, both those untreated or exposed to cytokines or glucolipotoxicity, whereas EVs from inflamed adipocytes caused β cell death and dysfunction. Human lean adipocyte-derived EVs produced similar beneficial effects, whereas EVs from obese AT explants were harmful for human EndoC-βH3 β cells. We observed differential expression of miRNAs in EVs from healthy and inflamed adipocytes, as well as alteration in signaling pathways and expression of β cell genes, adipokines, and cytokines in recipient β cells. These in vitro results suggest that, depending on the physiopathological state of AT, adipocyte-derived EVs may influence β cell fate and function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".