Acute Hypoxia Alters Extracellular Vesicle Signatures and the Brain Citrullinome of Naked Mole-Rats (Heterocephalus glaber)
Bibliographic record
Abstract
Peptidylarginine deiminases (PADs) and extracellular vesicles (EVs) may be indicative biomarkers of physiological and pathological status and adaptive responses, including to diseases and disorders of the central nervous system (CNS) and related to hypoxia. While these markers have been studied in hypoxia-intolerant mammals, in vivo investigations in hypoxia-tolerant species are lacking. Naked mole-rats (NMR) are among the most hypoxia-tolerant mammals and are thus a good model organism for understanding natural and beneficial adaptations to hypoxia. Thus, we aimed to reveal CNS related roles for PADs in hypoxia tolerance and identify whether circulating EV signatures may reveal a fingerprint for adaptive whole-body hypoxia responses in this species. We found that following in vivo acute hypoxia, NMR: (1) plasma-EVs were remodelled, (2) whole proteome EV cargo contained more protein hits (including citrullinated proteins) and a higher number of associated KEGG pathways relating to the total proteome of plasma-EVs Also, (3) brains had a trend for elevation in PAD1, PAD3 and PAD6 protein expression, while PAD2 and PAD4 were reduced, while (4) the brain citrullinome had a considerable increase in deiminated protein hits with hypoxia (1222 vs. 852 hits in normoxia). Our findings indicate that circulating EV signatures are modified and proteomic content is reduced in hypoxic conditions in naked mole-rats, including the circulating EV citrullinome, while the brain citrullinome is elevated and modulated in response to hypoxia. This was further reflected in elevation of some PADs in the brain tissue following acute hypoxia treatment. These findings indicate a possible selective role for PAD-isozymes in hypoxia response and tolerance.
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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".