Modulation of micro<scp>RNA</scp>‐375 expression alters voltage‐gated Na<sup>+</sup> channel properties and exocytosis in insulin‐secreting cells
Bibliographic record
Abstract
AIM: MiR-375 has been implicated in insulin secretion and exocytosis through incompletely understood mechanisms. Here we aimed to investigate the role of miR-375 in the regulation of voltage-gated Na(+) channel properties and glucose-stimulated insulin secretion in insulin-secreting cells. METHODS: MiR-375 was overexpressed using double-stranded mature miR-375 in INS-1 832/13 cells (OE375) or downregulated using locked nucleic acid (LNA)-based anti-miR against miR-375 (LNA375). Insulin secretion was determined using RIA. Exocytosis and ion channel properties were measured using the patch-clamp technique in INS-1 832/13 cells and beta-cells from miR-375KO mice. Gene expression was analysed by RT-qPCR, and protein levels were determined by Western blot. RESULTS: Voltage-gated Na(+) channels were found to be regulated by miR-375. In INS-1 832/13 cells, steady-state inactivation of the voltage-gated Na(+) channels was shifted by approx. 6 mV to a more negative membrane potential upon down-regulation of miR-375. In the miR-375 KO mouse, voltage-gated Na(+) channel inactivation was instead shifted by approx. 14 mV to a more positive membrane potential. Potential targets differed among species and expression of suggested targets Scn3a and Scn3b in INS-1 832/13 cells was only slightly moderated by miR-375. Modulation of miR-375 levels in INS-1-832/13 cells did not significantly affect insulin release. However, Ca(2+) dependent exocytosis was significantly reduced in OE375 cells. CONCLUSION: We conclude that voltage-gated Na(+) channels are regulated by miR-375 in insulin-secreting cells, and validate that the exocytotic machinery is controlled by miR-375 also in INS-1 832/13 cells. Altogether we suggest miR-375 to be involved in a complex multifaceted network controlling insulin secretion and its different components.
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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".