miR1908-5p regulates energy homeostasis in hepatocyte models
Bibliographic record
Abstract
We previously identified genomic variants that are quantitative trait loci for circulating miR-1908-5p and then showed this microRNA to causally associate with plasma levels of LDL-C, fasting blood glucose and HbA1c. The link to LDL-C was subsequently validated and clarified by the identification of a miR1908-5p-TGFB-LDLR regulatory axis. Here, we continue our investigations on miR1908-5p function by leveraging human primary hepatocytes and HuH-7 hepatoma models. Expression of miR1908-5p was shown to be sensitive to glucose and agents affecting glucose metabolism. Transcriptome-wide changes in primary hepatocytes and HuH-7 cells treated with a miR1908-5p mimic were investigated by enrichment approaches to identify targeted transcripts and cognate pathways. Significant pathways included autophagy and increased mitochondrial function. Reduced activation and/or levels of several key energy and metabolic regulators (AKT, mTOR, ME1, G6PD, AMPK and LKB) were subsequently confirmed in mimic treated HuH-7 cells. These effects were associated with reduced NADPH to NADP+ ratio in HuH-7 cells. LKB1 was validated as a direct target of miR1908-5p, the reintroduction of which was however insufficient to compensate for the impact of the miR1908-5p mimic on AMPK and ACC1. These findings implicate miR1908-5p in metabolic and energy regulation in hepatocyte models via multiple, independent, pathways.
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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".