Carotid body responses to <scp>O<sub>2</sub></scp> and <scp>CO<sub>2</sub></scp> in hypoxia‐tolerant naked mole rats
Bibliographic record
Abstract
Abstract Aim Naked mole rats (NMRs) exhibit blunted hypoxic (HVR) and hypercapnic ventilatory responses (HCVR). The mechanism(s) underlying these responses are largely unknown. We hypothesized that attenuated carotid body (CB) sensitivity to hypoxia and hypercapnia contributes to the near absence of ventilatory responses to hypoxia and CO2 in NMRs. Methods We measured ex vivo CB sensory nerve activity, phrenic nerve activity (an estimation of ventilation), and blood gases in urethane‐anesthetized NMRs and C57BL/6 mice breathing normoxic, hypoxic, or hypercapnic gases. CB morphology, carbon monoxide, and H2S levels were also determined. Results Relative to mice, NMRs had blunted CB and HVR. Morphologically, NMRs have larger CBs, which contained more glomus cells than in mice. Furthermore, NMR glomus cells form a dispersed pattern compared to a clustered pattern in mice. Hemeoxygenase (HO)‐1 mRNA was elevated in NMR CBs, and an HO inhibitor increased CB sensitivity to hypoxia in NMRs. This increase was blocked by an H2S synthesis inhibitor, suggesting that interrupted gas messenger signaling contributes to the blunted CB responses and HVR in NMRs. Regarding hypercapnia, CB and ventilatory responses to CO2 in NMRs were larger than in mice. Carbonic anhydrase (CA)‐2 mRNA is elevated in NMR CBs, and a CA inhibitor blocked the augmented CB response to CO2 in NMRs, indicating CA activity regulates augmented CB response to CO2. Conclusions Consistent with our hypothesis, impaired CB responses to hypoxia contribute in part to the blunted HVR in NMRs. Conversely, the HCVR and CB are more sensitive to CO2 in NMRs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".