Skeletal muscle blood flow and vascular conductance are enhanced in humans with high‐affinity hemoglobin during handgrip exercise in severe hypoxia
Bibliographic record
Abstract
Background In humans, exercise tolerance is determined by the balance of diffusive and convective elements of oxygen transport. Mathematical models have suggested that alterations in hemoglobin‐oxygen (Hb‐O 2 ) binding affinity (P 50 ) have minimal effects of on oxygen delivery. However, there is limited experimental data in humans to evaluate these models during exercise in humans. Purpose We sought to investigate skeletal muscle blood flow and vascular conductance (hyperemic response to exercise and hypoxia) during exercise in otherwise healthy participants with chronically high Hb‐O 2 affinity (HAH). We hypothesized that patients with HAH would have a blunted hyperemic response to both handgrip and hypoxia due to the marked polycythemia that is typical in participants with HAH compared to controls. Methods Participants with HAH (n=6, 3 men, age= 37±12 yr, P 50 =15±2 mmHg) and control participants matched for age, sex, and BMI (CTL, n=5, 3 men, age=41±8 yr, and P 50 =26±1 mmHg) completed two intensities (10% and 20% maximal voluntary contraction (MVC)) of rhythmic handgrip exercise with a duty cycle of 1s contraction and 2s relaxation (20 contractions·min −1 ). Each exercise intensity was performed breathing three different gas mixtures: 21%, 15%, and 10% oxygen. Brachial artery mean blood velocity was measured using Doppler ultrasound. Beat‐by‐beat blood pressure was measured via arterial catheterization. Forearm blood flow (FBF) was calculated as the product of mean blood velocity (cm·s −1 ) and brachial artery cross‐sectional area (cm 2 ) and expressed as milliliters per minute (mL·min −1 ), and forearm vascular conductance (FVC) was calculated as (FBF) × (mean arterial pressure) −1 × 100 and expressed as mL·min −1 ·mmHg −1 . Data were analyzed using a three‐way ANOVA (Inspirate [21%, 15%, 10% O 2 ], group [CTL, HAH], handgrip intensity [Rest, 10% and 20% MVC]). Results During normoxia (21% O 2 ), groups were not different in FBF (P>0.05), FVC (P>0.05) or arterial saturation (S a O 2 , P=0.54). Similarly, the moderate hypoxia condition (15% O 2 ), groups were not different in FBF (P>0.05), or FVC (P>0.05) despite a preservation in arterial saturation in HAH (S a O 2 , CTL: 89.0±0.7% vs. HAH: 95.1±1.7%, P<0.001). However, with more severe hypoxic exposure (10% O 2 ), FBF and FVC were higher in HAH than controls during the 20% MVC exercise (P<0.05). HAH also had higher FBF (P<0.05) and trended towards higher FVC in the 10% MVC exercise (P=0.08). Interestingly, arterial saturation was drastically higher for HAH at the end of handgrip exercise (20% MVC) in 10% O 2 (CTL: 69.2±4.5% vs. HAH: 89.1±1.4%, P<0.001). Conclusion As predicted in mathematical models, Hb‐O 2 binding affinity had little effect on skeletal muscle blood flow and forearm vascular conductance during light exercise under normoxic and moderate hypoxic conditions (21% and 15% O 2 ). However, with a greater physiological stress to skeletal muscle O 2 uptake in a more severe hypoxic condition (10% O 2 ), participants with HAH, contrary to our initial hypothesis, had preserved arterial O 2 saturation and a greater hyperemic response than controls. Support or Funding Information This work was supported by the NIH (5T32DK007352‐39 to CCW, R35HL139854 to MJJ) Rest 10% MVC 20% MVC FBF, mL·min − 1 21% O 2 CTL 87 ± 8 327 ± 25 589 ± 26 HAH 142 ± 19 420 ± 29 716 ± 68
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".