Hypothalamic miR-1983 Targets Insulin Receptor β and the Insulin-mediated miR-1983 Increase Is Blocked by Metformin
Bibliographic record
Abstract
MicroRNAs (miRNAs) expressed in the hypothalamus are capable of regulating energy balance and peripheral metabolism by inhibiting translation of target messenger RNAs (mRNAs). Hypothalamic insulin resistance is known to precede that in the periphery, thus a critical unanswered question is whether central insulin resistance creates a specific hypothalamic miRNA signature that can be identified and targeted. Here we show that miR-1983, a unique miRNA, is upregulated in vitro in 2 insulin-resistant immortalized hypothalamic neuronal neuropeptide Y-expressing models, and in vivo in hyperinsulinemic mice, with a concomitant decrease of insulin receptor β subunit protein, a target of miR-1983. Importantly, we demonstrate that miR-1983 is detectable in human blood serum and that its levels significantly correlate with blood insulin and the homeostatic model assessment of insulin resistance. Levels of miR-1983 are normalized with metformin exposure in mouse hypothalamic neuronal cell culture. Our findings provide evidence for miR-1983 as a unique biomarker of cellular insulin resistance, and a potential therapeutic target for prevention of human metabolic disease.
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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) | 0.002 | 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".