MiR‐184 expression is regulated by AMPK in pancreatic islets
Bibliographic record
Abstract
AMPK is a critical energy sensor and target for widely used antidiabetic drugs. In β cells, elevated glucose concentrations lower AMPK activity, and the ablation of both catalytic subunits [β-cell-specific AMPK double-knockout (βAMPKdKO) mice] impairs insulin secretion in vivo and β-cell identity. MicroRNAs (miRNAs) are small RNAs that silence gene expression that are essential for pancreatic β-cell function and identity and altered in diabetes. Here, we have explored the miRNAs acting downstream of AMPK in mouse and human β cells. We identified 14 down-regulated and 9 up-regulated miRNAs in βAMPKdKO vs. control islets. Gene ontology analysis of targeted transcripts revealed enrichment in pathways important for β-cell function and identity. The most down-regulated miRNA was miR-184 (miR-184-3p), an important regulator of β-cell function and compensatory expansion that is controlled by glucose and reduced in diabetes. We demonstrate that AMPK is a potent regulator and an important mediator of the negative effects of glucose on miR-184 expression. Additionally, we reveal sexual dimorphism in miR-184 expression in mouse and human islets. Collectively, these data demonstrate that glucose-mediated changes in AMPK activity are central for the regulation of miR-184 and other miRNAs in islets and provide a link between energy status and gene expression in β cells.-Martinez-Sanchez, A., Nguyen-Tu, M.-S., Cebola, I., Yavari, A., Marchetti, P., Piemonti, L., de Koning, E., Shapiro, A. M. J., Johnson, P., Sakamoto, K., Smith, D. M., Leclerc, I., Ashrafian, H., Ferrer, J., Rutter, G. A. MiR-184 expression is regulated by AMPK in pancreatic islets.
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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 | 0.000 |
| 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".