Hypoxic naked mole–rat brains use microRNA to coordinate hypometabolic fuels and neuroprotective defenses
Bibliographic record
Abstract
Naked mole-rats are among the mammalian champions of hypoxia tolerance. They evolved adaptations centered around reducing metabolic rate to overcome the challenges experienced in their underground burrows. In this study, we used next-generation sequencing to investigate one of the factors likely supporting hypoxia tolerance in naked mole-rat brains, posttranscriptional microRNAs (miRNAs). Of the 212 conserved miRNAs identified using small RNA sequencing, 18 displayed significant differential expression during hypoxia. Bioinformatic enrichment revealed that hypoxia-mediated miRNAs were suppressing energy expensive processes including de novo protein translation and cellular proliferation. This suppression occurred alongside the activation of neuroprotective and neuroinflammatory pathways, and the induction of central signal transduction pathways including HIF-1α and NFκB via miR-335, miR-101, and miR-155. MiRNAs also coordinated anaerobic glycolytic fuel sources, where hypoxia-upregulated miR-365 likely suppressed protein levels of ketohexokinase, the enzyme responsible for catalyzing the first committed step of fructose catabolism. This was further supported by a hypoxia-mediated reduction in glucose transporter 5 proteins that import fructose into the cell. Yet, messenger RNA and protein levels of lactate dehydrogenase, which converts pyruvate to lactate in the absence of oxygen, were elevated during hypoxia. Together, this demonstrated the induction of anaerobic glycolysis despite a lack of reliance on fructose as the primary fuel source, suggesting that hypoxic brains are metabolically different than anoxic naked mole-rat brains that were previously found to shift to fructose-based glycolysis. Our findings contribute to the growing body of oxygen-responsive miRNAs "OxymiRs" that facilitate natural miRNA-mediated mechanisms for successful hypoxic exposures.
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) | 0.001 | 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".