Hypoxia induction in cultured pancreatic islets enhances endothelial cell morphology and survival while maintaining beta-cell function
Bibliographic record
Abstract
BACKGROUND: Pancreatic islets are heavily vascularized in vivo yet lose this vasculature after only a few days in culture. Determining how to maintain islet vascularity in culture could lead to better outcomes in transplanting this tissue for the treatment of type 1 diabetes as well as provide insight into the complex communication between beta-cells and endothelial cells (ECs). We previously showed that islet ECs die in part due to limited diffusion of serum albumin into the tissue. We now aim to determine the impact of hypoxia on islet vascularization. METHODS: We induced hypoxia in cultured mouse islets using the hypoxia mimetic cobalt chloride (100 μM CoCl2). We measured the impact on islet metabolism (two-photon NAD(P)H and Rh123 imaging) and function (insulin secretion and survival). We also measured the impact on hypoxia related transcripts (HIF-1α, VEGF-A, PDK-1, LDHA, COX4) and confirmed increased VEGF-A expression and secretion. Finally, we measured the vascularization of islets in static and flowing culture using PECAM-1 immunofluorescence. RESULTS: CoCl2 did not induce significant changes in beta cell metabolism (NAD(P)H and Rh123), insulin secretion, and survival. Consistent with hypoxia induction, CoCl2 stimulated HIF-1α, PDK-1, and LDHA transcripts and also stimulated VEGF expression and secretion. We observed a modest switch to the less oxidative isoform of COX4 (isoform 1 to 2) and this switch was noted in the glucose-stimulated cytoplasmic NAD(P)H responses. EC morphology and survival were greater in CoCl2 treated islets compared to exogenous VEGF-A in both static (dish) and microfluidic flow culture. CONCLUSIONS: Hypoxia induction using CoCl2 had a positive effect on islet EC morphology and survival with limited impact on beta-cell metabolism, function, and survival. The EC response appears to be due to endogenous production and secretion of angiogenic factors (e.g. VEGF-A), and mechanistically independent from survival induced by serum albumin.
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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 | 0.000 | 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".