The heme oxygenase system potentiates insulin‐signalling and enhance glucose metabolism in Zucker Diabetic Fatty rats
Bibliographic record
Abstract
Aldosterone causes oxidative insults by stimulating NF‐¿B, activating‐protein (AP‐1), and c‐Jun‐N‐terminal‐kinase (JNK). In type‐2 diabetes (T2D), aldosterone‐ and hyperglycaemia‐induced oxidative events constitute a potent destructive force. We investigated the role of heme oxygenase (HO) on aldosterone/oxidative stress and insulin‐signaling in Zucker diabetic fatty rat (ZDF). HO was induced with hemin or inhibited with chromium mesoporphyrin (CrMP). Hemin reduced fasting/postprandial hyperglycaemia, while CrMP exacerbated hyperglycaemia in ZDF. The anti‐diabetic effect was accompanied by enhanced HO activity, catalase, bilirubin, ferritin and total anti‐oxidant capacity, whereas reduced aldosterone, 8‐isoprostane, JNK, NF‐¿B, AP‐1 and AP‐2 were observed. Interestingly, hemin increased insulin levels alongside cAMP and cGMP, two secondary‐messengers that also regulate insulin release. Furthermore, agents that promote insulin‐signaling including adiponectin, AMPK, aldolase‐B and GLUT4, were robustly increased. Correspondingly, hemin reduced glucose/insulin tolerance, lowered insulin resistance (HOMA‐IR), and reversed the inability of insulin to enhance GLUT4. The suppression of hyperglycaemia‐ and aldosterone‐induced oxidative stress alongside the potentiation of insulin‐sensitizing pathways may account anti‐diabetic effect.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".