Insulin Inhibits Nrf2 Gene Expression via Heterogeneous Nuclear Ribonucleoprotein F/K in Diabetic Mice
Bibliographic record
Abstract
Oxidative stress induces endogenous antioxidants via nuclear factor erythroid 2-related factor 2 (Nrf2), potentially preventing tissue injury. We investigated whether insulin affects renal Nrf2 expression in type 1 diabetes (T1D) and studied its underlying mechanism. Insulin normalized hyperglycemia, hypertension, oxidative stress, and renal injury; inhibited renal Nrf2 and angiotensinogen (Agt) gene expression; and upregulated heterogeneous nuclear ribonucleoprotein F and K (hnRNP F and hnRNP K) expression in Akita mice with T1D. In immortalized rat renal proximal tubular cells, insulin suppressed Nrf2 and Agt but stimulated hnRNP F and hnRNP K gene transcription in high glucose via p44/42 mitogen-activated protein kinase signaling. Transfection with small interfering RNAs of p44/42 MAPK, hnRNP F, or hnRNP K blocked insulin inhibition of Nrf2 gene transcription. Insulin curbed Nrf2 promoter activity via a specific DNA-responsive element that binds hnRNP F/K, and hnRNP F/K overexpression curtailed Nrf2 promoter activity. In hyperinsulinemic-euglycemic mice, renal Nrf2 and Agt expression was downregulated, whereas hnRNP F/K expression was upregulated. Thus, the beneficial actions of insulin in diabetic nephropathy appear to be mediated, in part, by suppressing renal Nrf2 and Agt gene transcription and preventing Nrf2 stimulation of Agt expression via hnRNP F/K. These findings identify hnRNP F/K and Nrf2 as potential therapeutic targets in diabetes.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".