Hibernation-Induced microRNA Expression Promotes Signaling Pathways and Cell Cycle Dysregulation in Ictidomys tridecemlineatus Cardiac Tissue
Bibliographic record
Abstract
The thirteen-lined ground squirrel Ictidomys tridecemlineatus is a rodent that lives throughout the United States and Canada and uses metabolic rate depression to facilitate circannual hibernation which helps it survive the winter. Metabolic rate depression is the reorganization of cellular physiology and molecular biology to facilitate a global downregulation of nonessential genes and processes, which conserves endogenous fuel resources and prevents the buildup of waste byproducts. Facilitating metabolic rate depression requires a complex interplay of regulatory approaches, including post-transcriptional modes such as microRNA. MicroRNA are short, single-stranded RNA species that bind to mRNA transcripts and target them for degradation or translational suppression. Using next-generation sequencing, we analyzed euthermic vs. hibernating cardiac tissue in I. tridecemlineatus to predict seven miRNAs (let-7e-5p, miR-122-5p, miR-2355-3p, miR-6715b-3p, miR-378i, miR-9851-3p, and miR-454-3p) that may be differentially regulated during hibernation. Gene ontology and KEGG pathway analysis suggested that these miRNAs cause a strong activation of ErbB2 signaling which causes downstream effects, including the activation of MAPK and PI3K/Akt signaling and concurrent decreases in p53 signaling and cell cycle-related processes. Taken together, these results predict critical miRNAs that may change during hibernation in the hearts of I. tridecemlineatus and identify key signaling pathways that warrant further study in this species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".