Molecular Regulation of the Hypothalamo-Pituitary-Adrenal Axis in Streptozotocin-Induced Diabetes: Effects of Insulin Treatment
Bibliographic record
Abstract
Increased hypothalamo-pituitary-adrenocortical (HPA) activity in diabetes is likely important in the development of some pathologies associated with the disorder. We hypothesized that central regulation of HPA activity differs among normal, streptozotocin (STZ)-diabetic, and insulin-treated diabetic rats. Blood glucose, ACTH, and corticosterone were elevated, 8 d after inducing diabetes. Insulin treatment normalized these parameters. Plasma norepinephrine was similar in all groups, but epinephrine was lower in STZ-diabetic and higher in insulin-treated rats vs. normals. Increased ACTH with diabetes corresponded with increased hypothalamic CRH mRNA, but no change in pituitary POMC mRNA. With insulin-treatment, CRH mRNA remained elevated, and POMC mRNA was unaltered. Hippocampal MR mRNA expression was dramatically increased with diabetes and, moreover, was not normalized by insulin. No differences in GR mRNA were detected between normal and STZ-diabetic rats. However, insulin treatment increased GR mRNA levels in the paraventricular nucleus and pituitary. We postulate that, in STZ-diabetes: 1) increased HPA activity is caused by increased central drive at and/or above the level of the paraventricular nucleus and is associated with decreased epinephrine; and 2) normalized pituitary-adrenal activity with insulin may be caused by the compensatory increase in GR mRNA allowing glucocorticoid-mediated suppression of ACTH secretion despite the residual increase in central HPA activity. Thus, insulin apparently restored HPA activity at and below the pituitary but, surprisingly, not above it.
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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 | 0.001 |
| 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".