Adrenal chromaffin cell function in high‐altitude deer mice ( <i>Peromyscus maniculatus</i> )
Bibliographic record
Abstract
Hypoxia at high altitudes can activate the sympathetic nervous system, which could become maladaptive in high‐altitude natives if it is maintained over chronic periods. The deer mouse ( Peromyscus maniculatus ) has the largest altitudinal range of all North American mammals, with populations living above 4300m elevation. We hypothesized that high‐altitude deer mice might have altered the physiology of chromaffin cells in the adrenal gland to avoid chronic activation of the sympathetic response. We used captive breeding colonies derived from wild populations at high and low altitudes, and compared them in normoxia and after 6–8 weeks of acclimation to hypoxia (12kPa O 2 , simulating the PO 2 at ~4300m). High‐altitude mice show lower rates of catecholamine secretion from adrenal slices (measured via carbon fibre amperometry) in response to stimulation by a nicotinic acetylcholine receptor agonist (nicotine). Here, we used ratiometric Ca 2+ imaging of cultured chromaffin cells to assess whether the variation in catecholamine secretion resulted from variation in the Ca 2+ signal for vesicular catecholamine release. The rise of intracellular Ca 2+ in response to nicotine (1, 5, 25, 125μM) did not vary between populations and was not affected by hypoxia acclimation, suggesting that events downstream of Ca 2+ influx likely contribute to population differences in catecholamine secretion. This appeared to include differences in catecholamine stores, which were lower in highlanders compared to lowlanders in cultured cells from normoxia‐acclimated mice. Our data therefore suggest that chronic sympathetic activation may be avoided in deer mice at high altitudes by a reduction in catecholamine storage and release from the adrenal gland.
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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 | 0.001 |
| 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".