Larger spleens and greater splenic contraction during exercise may be an adaptive characteristic of Nepali Sherpa at high‐altitude
Bibliographic record
Abstract
Abstract Objectives The Sherpa ethnic group living at altitude in Nepal may have experienced natural selection in response to chronic hypoxia. We have previously shown that Sherpa in Kathmandu (1400 m) possess larger spleens and a greater apnea‐induced splenic contraction compared to lowland Nepalis. This may be significant for exercise capacity at altitude as the human spleen responds to stress‐induced catecholamine secretion by an immediate contraction, which results in transiently elevated hemoglobin concentration ([Hb]). Methods To investigate splenic contraction in response to exercise at high‐altitude (4300 m; Pb = ~450 Torr), we recruited 63 acclimatized Sherpa (29F) and 14 Nepali non‐Sherpa (7F). Spleen volume was measured before and after maximal exercise on a cycle ergometer by ultrasonography, along with [Hb] and oxygen saturation (SpO2). Results Resting spleen volume was larger in the Sherpa compared with Nepali non‐Sherpa (237 ± 62 vs. 165 ± 34 mL, p < .001), as was the exercise‐induced splenic contraction (Δspleen volume, 91 ± 40 vs. 38 ± 32 mL, p < .001). From rest to exercise, [Hb] increased (1.2 to 1.4 g.dl−1), SpO2 decreased (~9%) and calculated arterial oxygen content (CaO2) remained stable, but there were no significant differences between groups. In Sherpa, both resting spleen volume and the Δspleen volume were modest positive predictors of the change (Δ) in [Hb] and CaO2 with exercise (p‐values from .026 to .037 and R2 values from 0.059 to 0.067 for the predictor variable). Conclusions Larger spleens and greater splenic contraction may be an adaptive characteristic of Nepali Sherpa to increase CaO2 during exercise at altitude, but the direct link between spleen size/function and hypoxia tolerance remains unclear.
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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) | 0.002 | 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".