Notice bibliographique
Résumé
Mammalian muscles present a wide range of contractile and metabolic properties resulting from the relative proportions of oxidative (type I) and glycolytic (type II) fibres making up a given muscle. Besides these innate properties, muscles are also highly plastic, responding to environmental change. In particular, oxygen availability has a strong influence on muscle metabolism. When oxygen concentration drops (hypoxia), proteins such as the hypoxia inducible factor-1 (HIF-1) are activated to orchestrate a switch to glycolytic (anaerobic) metabolism in an effort to spare oxygen. Over longer periods of hypoxia, HIF-1 also promotes increased vascularisation via angiogenic factors such as the vascular endothelial growth factor (VEGF) to improve oxygen delivery to the hypoxic tissue. The HIF-1 protein is composed of two components; HIF-1α is primarily regulated by oxygen availability, while the other subunit is constitutively expressed. When the oxygen concentration is normal, HIF-1α protein tends to be targeted for degradation, lowering HIF-1 activity. However, under hypoxic conditions HIF-1α is stabilized, allowing the HIF-1 dimer to act on several metabolic pathways to help the cell cope with low oxygen levels. Although the role of HIF-1 under hypoxia has been widely studied, relatively little is known about the function of this protein under normoxic conditions in resting muscle. Furthermore it is unclear whether this factor is differentially regulated in muscles with different metabolic phenotypes.Remi Mounier, Bente Pedersen and Peter Plomgaard from the University of Copenhagen, Denmark, investigated these two questions by looking at different muscle fibre types in humans. Specifically, the team looked at gene and protein expression profiles in resting muscles, and hypothesized that primarily glycolytic muscles would present higher expression levels of HIF-1 and associated factors than oxidative muscles.First, Mounier and colleagues selected three skeletal muscles, the oxidative soleus muscle (mostly type I fibres), the mixed vastus lateralis muscle (type I and type II fibres) and the glycolytic triceps brachii (mostly type II fibres) muscles. Using quantitative real-time PCR, the team established that HIF-1α mRNA expression was higher in glycolytic and mixed muscles than in the oxidative soleus muscle, as predicted by their hypothesis. In contrast, the mRNA expression of VEGF, a gene regulated by HIF-1, did not show any fibre type-specific pattern, confirming that HIF-1α mRNA levels do not necessarily reflect HIF-1 activity. So the team measured HIF-1α protein amounts in the muscles to see whether they correlated with the gene expression patterns. Contrary to their expectations, HIF-1α protein levels were threefold lower in glycolytic muscles than in mixed and oxidative muscles. In addition, VEGF protein levels were lowest in glycolytic muscles, intermediate in mixed muscles and highest in oxidative muscles.The results of this study strongly suggest that different muscle types regulate the HIF pathway at different levels, and further investigation will be necessary to unveil the mechanisms responsible for this tissue-specific regulation. Furthermore, these results also confirm the presence of HIF-1 under normal oxygen conditions, and thus suggest that this factor may also play an important role in regulating skeletal muscle homeostasis even under normoxia.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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.
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 ».