Developmental and genetic components explain enhanced pulmonary volumes of female peruvian quechua
Bibliographic record
Abstract
High altitude natives have enlarged vital capacities and residual volumes (RV). Because pulmonary volumes are an indication of functionally relevant traits, such as diffusion capacity, the understanding of the factors (genetic/developmental) that influence lung volumes provides insight into the adaptive responses of highlanders. In order to test for the effect of growth and development at high altitude on lung volumes, we obtained forced vital capacities (FVC), RV, and total lung capacities (TLC) for a sample of 65 Peruvian females of mostly Quechua origins (18-34 years) who were sub-divided into two well-matched groups: 1) sea-level born and raised females (BSL, n = 34) from Lima, Peru (150 m), and 2) high-altitude born and raised females (BHA, n = 31) from Cerro de Pasco, Peru (4,338 m). To determine Quechua origins, Native American ancestry proportion (NAAP) for each individual was assessed using a panel of 70 ancestry informative markers. NAAP was similar between groups (BSL = 91.71%; BHA = 89.93%; P = 0.240), and the analysis confirmed predominantly Quechua origins. After adjusting for body size and NAAP, BHA females had significantly higher FVC (3.79 ± 0.06 l; P < 0.001), RV (0.98 ± 0.03 l; P < 0.001) and TLC (4.80 ± 0.07 l; P < 0.001) compared to BSL females (FVC = 3.33 ± 0.05 l; RV = 0.69 ± 0.03 l; TLC = 4.02 ± 0.06 l). NAAP was not associated with FVC (P = 0.352) or TLC (P = 0.506). However, NAAP was positively associated with RV (P = 0.004). In summary, results indicate that developmental exposure to high altitude in females constitutes an important factor for all lung volumes, whereas both genetic and developmental factors seem to be important for RV.
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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) | 0.003 | 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".