Persistent Elevation of Vascular Endothelial Growth Factor and Prostacyclin Following Cardiopulmonary Maladaptation to High Altitude: A Pilot study
Bibliographic record
Abstract
Background: Exposure to hypobaric hypoxemia causes acute mountain sickness (AMS) in 40% of subjects acutely exposed to an altitude of 4,000 m. Vascular endothelial growth factor (VEGF) and cytokines appear to play a role in AMS in model systems. The objective of this pilot study was to explore the change in VEGF, the vasodilatory prostacyclin PGI-2, interleukin-6 and thiobarbituric acid reactive substances (TBARS) levels following prolonged exposure to hypobaric hypoxemia on Bolivian Altiplano. The secondary objective was to investigate the relationship between these markers with good versus poor adaptation to high altitude. Methods: The study population consisted of 7 climbers aged 24-64 yr. One cardiac transplant and one kidney transplant recipients participated in this study. Aerobic capacity was assessed on a treadmill using a RAMP protocol with gas exchange analyses. Blood samples were harvested within 48 hr of departure and within 24 hr returning to sea level. Results: Selected biochemisty parameters are presented in the table: *** Table in Full Text PDF. *** Data are mean ±SD. CP= cardiopulmonary. Both cardiac and Tx recipients did not experience AMS. Maximum altitude achieved: ∗6120-6522; †5680; ‡5300 meters. Conclusions: Pulmonary maladaptation to high altitude results in a 2-fold elevated VEGF and PGI-2 without concomitant increase of markers of inflammation or oxidative stress. VEGF does not appear to increase in cerebral maladaptation to high altitude. Further investigations are needed to better understand the role of VEGF and other biomarkers during the process of adaptation or maladaptation to high altitude.
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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 | 0.001 | 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) | 0.001 | 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".