Metabolomic Analysis of Carbohydrate and Amino Acid Changes Induced by Hypoxia in Naked Mole-Rat Brain and Liver
Bibliographic record
Abstract
Hypoxia poses a major physiological challenge for mammals and has significant impacts on cellular and systemic metabolism. As with many other small rodents, naked mole-rats (NMRs; Heterocephalus glaber), who are among the most hypoxia-tolerant mammals, respond to hypoxia by supressing energy demand (i.e., through a reduction in metabolic rate mediated by a variety of cell- and tissue-level strategies), and altering metabolic fuel use to rely primarily on carbohydrates. However, little is known regarding specific metabolite changes that underlie these responses. We hypothesized that NMR tissues utilize multiple strategies in responding to acute hypoxia, including the modulation of signalling pathways to reduce anabolism and reprogram carbohydrate metabolism. To address this question, we evaluated changes of 64 metabolites in NMR brain and liver following in vivo hypoxia exposure (7% O2, 4 h). We also examined changes in matched tissues from similarly treated hypoxia-intolerant mice. We report that, following exposure to in vivo hypoxia: (1) phenylalanine, tyrosine and tryptophan anabolism are supressed both in NMR brain and liver; (2) carbohydrate metabolism is reprogramed in NMR brain and liver, but in a divergent manner; (3) redox state is significantly altered in NMR brain; and (4) the AMP/ATP ratio is elevated in liver. Overall, our results suggest that hypoxia induces significant metabolic remodelling in NMR brain and liver via alterations of multiple metabolic pathways.
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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".