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Enregistrement W2201272619 · doi:10.1139/apnm-2015-0057

Discussion: “The kinetics of blood lactate in boys during and following a single and repeated all-out sprints of cycling are different than in men” — Do children indeed release and remove lactate faster than adults?

2015· letter· en· W2201272619 sur OpenAlexaffvenue
Raffy Dotan, Bareket Falk

Notice bibliographique

RevueApplied Physiology Nutrition and Metabolism · 2015
Typeletter
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePharmacological Effects and Assays
Établissements canadiensBrock University
Organismes subventionnairesnon disponible
Mots-clésBlood lactateKineticsRealmPsychologyMedicineInternal medicineHeart ratePhysicsHistory

Résumé

récupéré en direct d'OpenAlex

In their just-published paper, Engel et al. (2015) re-establish 2 very important facts in the realm of pediatric exercise physiology: First, that pre-pubertal boys, even when trained, do not reach the levels of blood lactate (La) concentrations attained by men. Second, that in repeated short-term high-intensity exercise, boys fatigue considerably less than do their adult counterparts. The authors, however, go beyond comparing La concentrations and performance capacities and venture into the more complex topic of child–adult differences in La kinetics. The boys’ La kinetics is clearly different than that of the men (Fig. 2; Engel et al. 2015), with the boys’ La concentration peaking earlier, but at considerably lower levels than themen’s. Less obvious are the reasons for these differences and this is where, we believe, the authors went astray. As the first of their study’smain findings, the authors claim that boys demonstrated “...a faster release of lactate into the blood and more rapid subsequent removal from the blood...” As will be explained below, we consider this claim and its reasoning to be largely unacceptable. The root problem appears to be the authors’ stated reliance on a model previously employed by Beneke et al. for the very same purpose (Beneke et al. 2005). That model, in turn, was one earlier used by Dost to assess pharmacokinetics (Dost 1968). While the 2 may appear similar, there is an important distinction between drug and La kinetics. While drug kinetics is typically measured in hours and days, La responses are timed in minutes and seconds. Therefore, in typical pharmacokinetics, a factor that affects the kinetics by a few seconds or minutes would be imperceptible and thus inconsequential for how a drug would be administered. On the other hand, a comparable effect on La kinetics does make a considerable difference. Such a factor does indeed exist. It has been termed “circulation time” or “transit time”. It has long been shown that circulation (out and back transit) time increases with body mass and blood volume from infancy to adulthood (Seckel 1936), and Cumming, for example, showed it to be shorter in children versus adults during exercise (Cumming 1978). In this respect, children’s faster La response to exercise is not much different than their corresponding fasteroxygenuptakekinetics (Carter et al. 2005). The Dost/Beneke model has 2 components (i.e., release into the blood and elimination from the blood) and it may be suitable when comparing drug or La kinetics in individuals of similar body dimensions. Indeed, Engel et al. confirm that the model they used (i.e., the Dost/Beneke model) has been validated for men, but not for boys. Thus, in view of the known differences in transit times between children and adults, both Engel et al. and Beneke et al. should have taken these differences into account and employed at least a 3rather than a 2-component model when comparing boys to men. In looking at the descending (elimination) slopes in Engel et al.’s Figs. 2 and 3, there is no obvious boys–men rate difference. In 2003we showed thatwhen postexercise La concentrationswere similar, no difference in the rate of La elimination could be demonstrated (Dotan et al. 2003). This means that children do not possess any “secret weaponry” when it comes to metabolizing La and thus, this cannot be used to explain children’s faster recovery, in general, and fromhigh-intensity exercise, inparticular (Falk andDotan2006). The only detected boys–men difference in La-kinetics was a phase shift that saw the boys reach their peak La concentration some 2.6 min ahead of the men (very similar to the difference found by Engel et al.).Weattributed thisphase shift to theboys’ shorter transit times, although this might very well not be the only reason. We agree with Engel et al. that children likely possess higher type-I muscle-fibre composition. As we have previously suggested, we also believe that children recruit their type-II motor units to a lesser degree compared with men (e.g., Dotan et al. 2012). Certainly, these attributes could both be true. Whatever the exact reason, it is very likely that children’s functional muscle composition is skewed towards higher percentage of type-I motor units. This can clearly explain why children produce less La and lower power and hence have less to recover from (Falk and Dotan 2006). This, in turn, also explains children’s lower fatigability, as Engel et al. nicely demonstrated. The authors, however, failed to support their claim that type-I fibres release La to the blood faster than their type-II counterparts. We believe this is mainly a function of intra-muscular La concentration rather thanmuscle-fibre type. Jorfeldt et al. counter-intuitively concluded that “lactate formed in the muscle during exercise is released at low and moderate work loads but [is] partly accumulated in the tissue at heavy work loads when the rate of lactate formation is high” (Jorfeldt et al. 1978). That is, unlike the case with simple diffusion models, the relative rate of La release is, in essence, slowed down the more La is accumulated in the muscle (i.e., despite the increasing gradient). It is the fact that more La is produced and accumulated in type-II fibres that indirectly relates the differential release rate to fibre type. This, in addition to longer transit times, nicely explains why La concentration peaked 7.6 min postexercise in our men, while the corresponding delay for the boys was only 5.0 min (Dotan et al. 2003). It is noteworthy that although the boys–men difference in the time to peak La

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,974
Score d'incertitude au seuil0,469

Scores Codex et Gemma par catégorie

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

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,222
Écart entre enseignants0,208 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

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

En bref

Citations7
Publié2015
Routes d'admission2
Résumé présentoui

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