Sirolimus and mTORC1: centre stage in the story of what makes muscles bigger?
Notice bibliographique
Résumé
Sirolimus, or rapamycin as it commonly known, is a potent immunosuppressant and possesses both antifungal and antineoplastic properties. As such it has clinically important uses in oncology, cardiology and transplantation medicine. In this issue of The Journal of Physiology, Drummond and co-workers used rapamycin to elucidate in greater detail the signalling pathways that are activated by high force contractions in human skeletal muscle (Drummond et al. 2009). We have known for some time that resistance exercise employing high force contractions stimulates muscle protein synthesis (Chesley et al. 1992; Welle et al. 1993). The critical experiments in humans, following some very elegant work in rodents (Bodine et al. 2001; Kubica et al. 2005), showed that phosphorylation of a critical activation site on the mammalian target of rapamycin complex 1 (mTORC1), namely Ser2448 (Nave et al. 1999), was increased following resistance exercise (Dreyer et al. 2006). With excitement, many exercise physiologists no doubt rushed to see whether mTORC1 activation was as critical in humans as it appeared to be in rats. Sadly, however, many other studies have not reported phosphorylation of mTORC1 following resistance exercise (Eliasson et al. 2006; Glover et al. 2008). Issues of the timing of muscle sampling along with differences in nutritional status have no doubt contributed to the confusion. Nonetheless, the intriguing results of Drummond et al. (2009) show us that somewhere along the way mTORC1 is involved in turning on the process of protein synthesis following resistance exercise. Complicating the picture, however, are the findings that proteins downstream of mTORC1 such as ribosomal S6 kinase 1 (S6K1) and ribosomal protein S6 (rpS6) as well mTORC1 do get phosphorylated, but not until some 2 h after exercise. Why then did protein synthesis not rise at that time? Several other recent papers have shown that other proteins such as mammalian vacuole protein sorting 34 (mVsp34) are also probably playing a role in activating high force contraction-induced muscle protein synthesis (MacKenzie et al. 2009). Thus, what is perhaps now much clearer than before is that there is tremendous redundancy in how signalling processes affect muscle protein synthesis. Indeed, recent data even show that changes in signalling protein phosphorylation can be almost completely divorced from protein synthesis with a stimulus such as insulin (Greenhaff et al. 2008). It appears that we are inching closer to an understanding of how high force contractions, a potent anabolic and anti-catabolic stimulus, may be triggering a rise in muscle protein synthesis. The work from Drummond and colleagues (Drummond et al. 2009) sheds new light on the importance of mTOR in the post-exercise phenotype and these workers are to be congratulated for their efforts. At the same time, the results of this study raise important questions. For example, what is the true role of the extracellular regulated kinase (ERK) pathway? This pathway too appears to be affected by rapamycin. We know that protein synthesis is elevated for some time (at least 24–48 h) after resistance exercise; hence, what mechanisms are active at the later times beyond the initial 1–2 h? No doubt mTORC1 will be playing a role at some point.
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 | 0,006 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,007 |
| Communication savante | 0,008 | 0,018 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,012 | 0,026 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,003 |
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 ».