Pancreas-specific miR-216a regulates proliferation and endocrine and exocrine cell function <i>in vivo</i>
Bibliographic record
Abstract
Abstract Pancreas is a vital organ composed of exocrine and endocrine cells that aid digestion of food and regulate blood glucose levels. Perturbations in the function of pancreatic cells leads to the development of life-burdening and/or threatening diseases such as diabetes and pancreatic cancer. Thus, it is critical to understand the molecular check-points that maintain normal pancreas physiology. MicroRNAs (miRNAs) are small non-coding RNAs involved in regulating gene expression in normal and diseased tissues. Several miRNAs have tissue-specific patterns consistent with crucial functions in many biological processes. Yet, there is limited knowledge about the role of pancreas-specific miRNAs in pancreatic pathologies. Here, we report that miR-216a is a conserved, pancreas-specific miRNA that is expressed in both endocrine and exocrine cells. Deletion of miR-216a in mice leads to reduced β-cell mass and a reduction in islet size under both chow and high-fat diet feeding conditions. We show that inhibition of miR-216a increases apoptosis and decreases cell proliferation in β- and exocrine cells. Smad7 is upregulated in miR-216a deficient islets and cell cycle and proliferation are among the most significantly regulated biological processes in miR-216 knockout pancreata. Re-introduction of miR-216a in the pancreatic cancer line, PANC-1, increases cell migration more than 2-fold. In vivo , deletion of miR-216a in the pancreatic cancer prone mouse line Kras G12D ; Ptf1a CreER inhibits the propensity of pancreatic cancer precursor lesions. Our study identifies miR-216a as an important pancreas-specific miRNA which may have implications for both diabetes and pancreatic cancer.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".