Pancreatic MicroRNAs in Ictidomys tridecemlineatus Associated with Metabolic Diseases: Nature’s Insights into Important Biomarkers
Bibliographic record
Abstract
Hibernation involves a profound metabolic rate depression (MRD) that enables certain species to survive prolonged periods of low energy availability. The thirteen-lined ground squirrel uses MRD to arrange cellular and biochemical pathways which suppress nonvital genetic and cellular pathways to conserve internal energy while preserving all essential processes. This study investigates the role of microRNAs (miRNAs) in controlling key signaling pathways and cellular processes in pancreatic tissue during hibernation. Using next-generation sequencing and broad genomic analysis, we analyzed and identified seven differentially expressed miRNAs (miR-29a-3p, miR-22-3p, miR-125-5p, miR-200a-3p, miR-328-3p, miR-21-5p, and miR-148-3p) in the pancreas of hibernating 13-lined ground squirrels (Ictidomys tridecemlineatus). Our findings reveal that these miRNAs regulate pathways involved in glucose homeostasis, including insulin secretion and metabolic regulation, contributing to the unique adaptations of hibernation. These insights advance our understanding of the molecular adaptations underlying hibernation and may have implications for therapeutic strategies targeting metabolic disorders such as diabetes.
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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) | 0.000 | 0.000 |
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".