Changes in microRNA expression related to ischemia-reperfusion injury in the kidney of the thirteen-lined ground squirrel during torpor
Bibliographic record
Abstract
During the hibernation season, the thirteen-lined ground squirrel undergoes cyclical torpor and arousal periods. The decrease and restoration of metabolic rate and oxygen delivery during torpor and arousal, respectively, may cause reperfusion-ischemia injury in the kidneys. In order to maintain the structural integrity of the kidneys necessary for renal function resumption during arousal, the thirteen-lined ground squirrel has developed adaptive methods to prevent and repair kidney injury. In this present study, computational methods were used to clean and analyze sequenced kidney RNA samples. Significantly differentially expressed microRNAs and enriched gene sets were also determined. From the gene set analysis, the results showed an increase in ubiquitin-related processes and p53 signaling pathways which suggested the occurrence of kidney damage during torpor. There was also an observed increase in cell cycle processes and the anchoring junction cellular compartment which may lend to the prevention of kidney injury. From the differentially expressed microRNAs, miR-27a (log2FC= 1.639; p-value= 0.023), miR-129 (log2FC= 2.516; p-value= 0.023), miR-let-7b (log2FC= 2.360; p-value= 0.025), miR-let-7c (log2FC= 2.291; p-value= 0.037) and miR-let-7i (log2FC= 1.564; p-value= 0.039) were found to be significantly upregulated. These biochemical adaptations may allow the thirteen-lined ground squirrel to maintain kidney structure and function during hibernation.
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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".