MétaCan
Menu
Retour à la cohorte
Enregistrement W1500150694 · doi:10.1113/jphysiol.2014.284406

Rebuttal from Stuart M. Phillips and Chris McGlory

2014· letter· en· W1500150694 sur OpenAlexafffundabout
Stuart M. Phillips, Chris McGlory

Notice bibliographique

RevueThe Journal of Physiology · 2014
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMuscle Physiology and Disorders
Établissements canadiensMcMaster University
Organismes subventionnairesCanadian Institutes of Health ResearchCanadian Diabetes Association
Mots-clésArgument (complex analysis)RebuttalProteolysisMechanism (biology)BiologyPhilosophyEvolutionary biologyEpistemologyBiochemistryHistory

Résumé

récupéré en direct d'OpenAlex

In our opponents’ view (Reid et al. 2014), the exact answer to the question of what is the dominant mechanism remains unknown and, as they conclude, ‘…proteolysis is an essential component of disuse atrophy.’ Importantly, we agree with both points. However, our position remains that the answer as to which is the dominant mechanism cannot merely be obtained from static protein/gene measurements or from rodent knock out models. As we in our original manuscript, and others (Cunningham, 2002) have highlighted, there are marked interspecies differences between humans and rodents that we propose have a significant bearing on this debate. While important proof of concept mechanistic information can be derived from rodent models they are still methodologically flawed. For example, the continued use of ex vivo muscle preparation is inherently biased towards showing elevated rates of muscle protein breakdown (MPB) and proteolytic markers as the tissue is essentially dying (albeit slowly) during the experiment. Our opponents cite only a single human study that attempted to measure MPB to support their argument (Tesch et al. 2008), which relied on an indirect proteolytic marker, and which did not include concomitant assessments of muscle protein synthesis (MPS). Even in recent papers (Bodine & Baehr, 2014) where large volumes of data were reviewed, in very few cited studies were actual rates of protein synthesis and/or breakdown even reported; instead, the change in muscle mass was estimated, proteolytic ‘markers’ were measured and a ‘conclusion’ reached as to the mechanism. To clarify, we do not dismiss our opponents’ argument that at least in the early phase of muscle disuse (<10 days), increases in MPB contribute to the decline in skeletal muscle size (Wall et al. 2013). There is evidence (with indirect markers) for this assertion, even in humans (Tesch et al. 2008). Nonetheless, the decline in human muscle size with disuse is predominantly driven by a reduction in the rate of MPS, especially in response to contraction and nutrition. Our opponents’ use of a graphic word cloud to support their thesis, while intriguing, is not in our view evidence that they are correct. Instead, we view this graphic ‘evidence’ as a depiction of the number of animal- versus human-based researchers in this area. Since animal-based researchers have generated most of the data in this field, the use of a word cloud in this instance is simply a reflection of the conclusion of the majority of researchers, using the same model, in this field. Thus, the word cloud is analogous to someone shouting the loudest in an argument and believing that approach renders their argument correct. Readers are invited to give their views on this and the accompanying CrossTalk articles in this issue by submitting a brief (250 word) comment. Comments may be submitted up to 6 weeks after publication of the article, at which point the discussion will close and the CrossTalk authors will be invited to submit a ‘Last Word’. Please email your comment to journals@physoc.org. Disclaimer: Supplementary materials have been peer-reviewed but not copyedited. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. The authors report no conflict of interest, financial or otherwise. This work was supported by grants to S.M.P. from the National Science and Engineering Research Council of Canada and the Canadian Institutes of Health Research, as well as the Canadian Diabetes Association.

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)0,010
score de la tête « metaresearch » (Gemma)0,057
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: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,029
Score d'incertitude au seuil0,068

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,057
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,008
Communication savante0,0090,013
Science ouverte0,0050,006
Intégrité de la recherche0,0290,065
Charge utile insuffisante (le modèle a refusé de juger)0,0200,023

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 Opus0,010
Tête enseignante GPT0,226
Écart entre enseignants0,216 · 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

Citations7
Publié2014
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revueThe Journal of PhysiologyMême sujetMuscle Physiology and DisordersTravaux en français237 207