Skeletal muscle blood flow and vascular conductance are enhanced in humans with high‐affinity hemoglobin during handgrip exercise in severe hypoxia
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».