Notice bibliographique
Résumé
As the global population ages and life expectancy continues to rise, osteoporosis continues to be a growing worldwide health concern. The International Osteoporosis Foundation reports 1 in 3 women over the age of 50 years and 1 in 5 men worldwide will experience osteoporotic fractures in their lifetime, costing between 5 and 6.5 trillion USD annually in Canada, Europe, and the United States alone. The need for preventative measures to reduce age-related bone loss is clear, not only to improve quality of life for countless individuals but also to relieve the economic burden this condition imposes. Exercise is a proven preventative method as it increases and maintains bone density, and reduces the risk of osteoporotic fracture with age. The benefits of exercise are not only mediated by physiological changes, but also by mechanically challenging the tissue. The work presented here seeks to elucidate how attenuating cellular mechanotransduction from embryogenesis through adolescence and into adulthood affects bone quality before and after exercise, as well as how exposure to whole-body low-intensity vibration from adulthood into old age affects bone quality before and after exercise. Linker of Nucleoskeleton and Cytoskeleton (LINC) protein complexes play an important role in cellular structure by connecting cytoskeletal elements to the nuclear envelope, as well as being critical regulator of force transmission from the cytoskeleton to the nucleus in vitro. We hypothesized disrupting these complexes in vivo would lead to decreased bone quality outcomes. To investigate LINC function in vivo, we generated two Cre/lox murine models that disrupt the LINC complex in bone progenitor cells – one under the Prrx1 promoter and the other under the osterix (Osx) marker. Bone microarchitecture and mechanical properties were measured at an 8-week baseline old mice and mice subjected to a 6-week exercise intervention. We found decreased osteogenic and adipogenic differentiation potential of bone marrow aspirates in our Osx model as well as diminished trabecular architecture an 8-week baseline; however, there were no remarkable changes in bone microarchitecture or mechanical properties after our six-week running intervention. Similarly, our Prrx1 model did not show any bone microarchitecture or mechanical property changes after our six- week running intervention, but this model also did not show an cellular phenotype differences or 8-week baseline differences either. Finally, to investigate how exposure to whole-body low-intensity vibration from adulthood into old age affects bone quality before and after exercise, we subjected 20-week old female C57Bl/6J mice to a low-intensity vibration (LIV) intervention (0.7g, 90Hz) for 15 minutes/2 times a day/5 days a week until they reach 48 weeks of age. A sub-cohort was placed in a six-week running intervention. We did not see any remarkable changes in bone microarchitecture or bone mechanical properties with long-term LIV treatment or exercise. Understanding the mechanical regulation of bone progenitor cells and how bone tissue responds to long-term physical stimulation in an aging population may lead to improved physiotherapy interventions, reducing the prevalence of osteoporotic fractures. The study findings included in this text, while not groundbreaking, shed light into the complex environment of bone mechanobiology. Whole bone tissue appears to be mostly unaffected by perturbations in mechanical signaling, whether that be through LINC complex disruption or addition of vibrational signals throughout the lifespan; however, there is evidence for changes in the cellular environment which could potentially lead to bone mineral makeup differences. Future investigation into mechanical regulation of bone tissue may benefit from focusing on cell-specific adaptations or utilizing more robust mechanical challenge model for induction of whole bone tissue changes.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».