The islet estrogen receptor-alpha is induced by hyperglycemia and protects against oxidative stress-induced insulin-deficient diabetes
Bibliographic record
Abstract
The female steroid, 17beta-estradiol (E2), is important for pancreatic beta-cell function and acts via at least three estrogen receptors (ER), ERalpha, ERbeta, and the G-protein coupled ER (GPER). Using a pancreas-specific ERalpha knockout mouse generated using the Cre-lox-P system and a Pdx1-Cre transgenic line (PERalphaKO (-)/(-)), we previously reported that islet ERalpha suppresses islet glucolipotoxicity and prevents beta-cell dysfunction induced by high fat feeding. We also showed that E2 acts via ERalpha to prevent beta-cell apoptosis in vivo. However, the contribution of the islet ERalpha to beta-cell survival in vivo, without the contribution of ERalpha in other tissues is still unclear. Using the PERalphaKO (-)/(-) mouse, we show that ERalpha mRNA expression is only decreased by 20% in the arcuate nucleus of the hypothalamus, without a parallel decrease in the VMH, making it a reliable model of pancreas-specific ERalpha elimination. Following exposure to alloxan-induced oxidative stress in vivo, female and male PERalphaKO (-)/(-) mice exhibited a predisposition to beta-cell destruction and insulin deficient diabetes. In male PERalphaKO (-)/(-) mice, exposure to E2 partially prevented alloxan-induced beta-cell destruction and diabetes. ERalpha mRNA expression was induced by hyperglycemia in vivo in islets from young mice as well as in cultured rat islets. The induction of ERalpha mRNA by hyperglycemia was retained in insulin receptor-deficient beta-cells, demonstrating independence from direct insulin regulation. These findings suggest that induction of ERalpha expression acts to naturally protect beta-cells against oxidative injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".