Small RNA and Freeze Survival: The Cryoprotective Functions of MicroRNA in the Frozen Muscle Tissue of the Grey Tree Frog
Bibliographic record
Abstract
The grey tree frog, Dryophytes versicolor, survives whole-body freezing for weeks during cold winter months. Survival in a state devoid of available food, water, or oxygen forces a reliance on metabolic rate depression (MRD) and the reprioritization of bodily functions. This study utilizes next-generation sequencing (NGS) and bioinformatic analyses to characterize changes in the microRNAome of D. versicolor. When comparing control to frozen groups, five microRNAs (miRNA) were found to be differentially regulated (miR-143-3p, miR-30e-3p, miR-10a-5p, miR-140-3p, and miR-148a-3p), suggesting that they play key roles in freeze survival. The KEGG and GO analyses of these changes predicted a significant negative enrichment of terms associated with cell proliferation and active metabolism while simultaneously predicting the upregulation of cell signalling terms. These results suggest a fast-acting regulatory role for miRNA in contributing to the reorganization of gene expression and the limitation of energy-expensive processes during MRD in the hind leg skeletal muscle of the frog.
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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) | 0.001 | 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".