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Enregistrement W2520134363 · doi:10.1113/jp272370

Exercise and the lungs: nature or nurture?

2016· letter· en· W2520134363 sur OpenAlexaff
I. Mark Olfert

Notice bibliographique

RevueThe Journal of Physiology · 2016
Typeletter
Langueen
DomaineMedicine
ThématiqueChronic Obstructive Pulmonary Disease (COPD) Research
Établissements canadiensCanadian Society for Exercise Physiology
Organismes subventionnairesnon disponible
Mots-clésRespirationVentilation (architecture)Respiratory systemLungCardiologyMedicineAerobic exerciseCardiorespiratory fitnessLung volumesRespiratory physiologyInternal medicinePhysiologyAnatomy

Résumé

récupéré en direct d'OpenAlex

The lungs are a component of the respiratory system, which also includes the oral/nasal passages, trachea and muscles of respiration. With the exception of the diaphragm and the other muscles supporting respiration, the respiratory system has long been viewed as untrainable in response to exercise. Indeed, unlike the cardiac and skeletal muscle, which can undergo structural and morphological changes to improve their function with exercise training, lung structure is not found to change with training, resulting in minimal (if any) changes in lung volume or function. This lack of plasticity is generally not a problem, as most healthy individuals performing exercise (at or near sea level) are able to maintain normal arterial oxygen levels, even during maximal exercise. Moreover the lung, and more generally the respiratory system, is often found to provide unfailing support for gas exchange under peak demand (e.g. during maximal exercise) in healthy mammals, and therefore it has widely been accepted that the lungs are ‘overbuilt’ for their primary gas exchange function. A notable exception applies to highly fit or elite-level athletes, who can experience gas exchange impairment particularly as exercise intensity approaches peak aerobic capacity, resulting in a phenomenon known as exercise-induced arterial hypoxaemia (EIAH). This is not unique to humans, as other mammals with high aerobic capacity (horses, dogs, etc.) are also found to exhibit EIAH (Dempsey & Wagner 1999). The physiological mechanisms that underpin hypoxaemia can be narrowed to one or more of the following: inadequate ventilation, mismatching of ventilation and perfusion in the lung, shunting of venous blood to the arterial side (i.e. bypassing gas exchange), and diffusion limitation. While these are well established, the relative contribution from any of these specific mechanism(s) in the aetiology of EIAH is still the focus of investigation. This is, in part, because EIAH is not a universal finding among athletes, and is even found in individuals (typically women) with much lower than the frequently reported threshold of 60 ml kg−1 min−1 that is often associated with EIAH (Harms et al. 1998). Clinicians and scientists are left wondering why, and whether some component of lung structure (if not changing) may respond differently to exercise training, between athletes, between aerobically fit versus unfit individuals, or between the sexes. In a recent study, Lalande et al. (2012) reported that individuals with high were found to have greater pulmonary capillary blood volume at rest, questioning if aerobically fit individuals have a more distensible pulmonary circulation. In a recent issue of The Journal of Physiology, Tedjasaputra et al. (2016) have further explored this finding and ask the next logical question, does greater fitness level alter lung diffusing capacity (DLCO) at or near maximal exercise? And if so, do these changes occur via pulmonary capillary blood volume (Vc) and/or with changes in diffusion across the alveolar membrane (Dm)? While this is not the first study to attempt to measure DLCO during exercise, the ability to measure DLCO near maximal exercise is extremely challenging since the subject is required to perform a breath-hold. It is notable that the investigators were able to obtain high-quality data on DLCO at exercise workloads of 90% of , when the lungs and gas exchange are close to the greatest stress and demands. Their study reveals that DLCO was greater in subjects with high aerobic capacity (HI-Fit group with > 60 ml kg−1 min−1) compared with individuals with lower aerobic capacity (LO-Fit group with ∼45 ml kg−1 min−1), and this was due to an increase in the Dm component and not Vc. These data suggest that endurance trained athletes have a larger alveolar–capillary interface, which is advantageous for the transfer of O2 during intense exercise. Although the current study does not directly address the issue of EIAH, and it is not stated in the report whether EIAH even existed in any of the subjects, these data establish that there are differences in the lung diffusing capacity between highly fit vs. less aerobically fit individuals. This raises a number of interesting questions: (1) have the lungs in these high-level endurance athletes changed with training to allow for this advantage? Or (2) is the ability of individuals to achieve high levels of lung and aerobic performance genetically pre-selected (i.e. nature vs. nurture)? And, (3) do the lungs in some people respond differently from in others, perhaps contributing to the variability between those who experience vs. those that don't experience EIAH? Based on the evidence currently available in the literature, it seems unlikely that DLCO changes significantly with training (Flaherty et al. 2014). It is also notable, however, that lung size of the HI-Fit group was greater than the LO-Fit group in Tedjasaputra et al.’s paper, suggesting the answer for diffusion may rely on ‘nature’ rather than ‘nurture’. This conforms to the notion that lung size (which is genetically determined) is likely to be an important factor determining whether an athlete will experience EIAH. Conceptually, it seems logical to expect that individuals with a small stature (and therefore small lungs) and who also achieve/develop a high aerobic capacity (via training) may be predisposed to EIAH. This is consistent with the observations found in exercising women (who on average have smaller lungs compared with similar stature males) are found to be more susceptible to EIAH (Harms et al. 1998). Interestingly, when highly fit women are matched to males based on lung size, they do not appear to be more susceptible to EIAH (Olfert et al. 2004). Therefore, although EIAH is most commonly observed in athletes with high , it should be the combination of lung size and how strongly the aerobic/metabolic engine is developed by training in any individual (i.e. establishing the demand on the lung) that determines whether gas exchange impairment and EIAH occur. Practically speaking, EIAH is unlikely to occur in individuals with low aerobic fitness, because even the smallest of healthy lungs appear to be more than adequate to meet the peak aerobic demands with this phenotype. However, as aerobic fitness and demand increase, lung size (and therefore Dm) becomes increasing important, such that individuals with smaller lungs and high aerobic demand are likely to be the most susceptible to EIAH. Thus, in principle, any person may experience EIAH if he or she develops an aerobic demand that exceeds supply for the supply and demand relationship that exists for total transfer of oxygen across the alveolar membrane at or near peak aerobic demand. So it seems the combined effect of ‘nature’ and ‘nurture’ must both be considered in determining the effect of the lung during exercise.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,019

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,007
Communication savante0,0040,004
Science ouverte0,0010,002
Intégrité de la recherche0,0040,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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.

Tête enseignante Opus0,011
Tête enseignante GPT0,291
Écart entre enseignants0,281 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2016
Routes d'admission1
Résumé présentoui

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