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Enregistrement W4415975110 · doi:10.33607/bjshs.v4i137.1699

Resistance Training and Muscle-Brain Crosstalk: Implications for Cognitive Decline in Aging and Spinal Cord Injury

2025· article· en· W4415975110 sur OpenAlexaboutno aff
Wouter A. J. Vints

Notice bibliographique

RevueBaltic Journal of Sport and Health Sciences · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSpinal Cord Injury Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSpinal cord injuryCognitionCognitive declineEndurance trainingCognitive trainingAerobic exerciseNeuroplasticityPopulationResistance training

Résumé

récupéré en direct d'OpenAlex

Background and objectives: Exerkines are signalling factors that are released from organs throughout the body during physical exercise (El-Sayes et al., 2019). Some of these exerkines are thought to contribute to the well-documented benefits of exercise on brain health and cognitive function, potentially delaying age-related cognitive decline (Erickson et al., 2011). However, research is still far from establishing a mechanism-based, evidence-driven exercise programme to prevent such decline. To date, most studies have focused on endurance training, leaving other training modalities underexplored. Moreover, few studies have simultaneously examined exercise-induced effects on blood, brain, and cognitive domains, limiting more holistic understanding of the underlying mechanisms. Research has also primarily involved healthy adults, whereas older adults at risk of Mild Cognitive Impairment (MCI) are less frequently studied. Importantly, the effects of exercise on cognition have never been investigated in persons with Spinal Cord Injury (SCI), a population with an elevated risk of age-related cognitive decline and dementia. The primary objective of the dissertation was therefore to gain a more comprehensive understanding of the mechanisms underlying the beneficial effects of exercise training, specifically resistance exercise in older adults and Neuromuscular Electrical Stimulation (NMES) in individuals with SCI, on brain health and cognitive function, with a particular focus on the role of exerkines in (exercise-induced) neuroplasticity. Methods: Eleven studies were conducted. Study 1 was a literature review describing exerkine release following acute and chronic endurance or resistance exercise and their effects on neuroplasticity via long-term synaptic potentiation. Study 2 summarised the findings from transcriptome and secretome studies identifying muscle-derived exerkines (myokines). Studies 3 and 4 were cross-sectional studies in older adults (n = 74) investigating the relationships between participant characteristics, blood (inflammatory and neurotrophic) and brain biomarkers (neurometabolites, regional grey matter volumes), and cognitive function. Studies 5–8 evaluated the effect of a single bout (n = 37) and a 12-week resistance exercise programme (n = 74) on blood and brain biomarkers and cognitive function in older adults. Studies 6 and 7 further compared outcomes between cognitively healthy older adults and those at elevated risk of MCI (based on the Montreal Cognitive Assessment). Study 9 systematically reviewed evidence on the effects of exercise interventions on cognitive performance in individuals with SCI and highlighted factors underlying their elevated risk of cognitive decline. Study 10 tested the effect of a single bout of NMES on exerkines and cognitive performance in persons with SCI. Study 11 described the protocol of a 12-week NMES intervention in individuals with SCI to examine the effect on exerkines and cognitive outcomes. Results: Study 1 identified 16 exerkines with known (in)direct effects on long-term synaptic potentiation. Study 2 reported 1,126 putative myokines, most with still unknown effects on the brain and body. Study 3 found associations between the circulating inflammatory marker kynurenine and signs of neuroinflammation and neurodegeneration in older adults. Study 4 showed that older adults with normal-to-slightly-elevated body weight and greater handgrip strength maintained larger brain volumes. Study 5 demonstrated improved working memory performance in older adults immediately after a single session of resistance exercise training compared to control group. Study 6 suggested hippocampal volume preservation over time in the resistance exercise group, and Study 7 revealed executive function improvements in older adults at elevated risk of MCI after 12 weeks of resistance training compared with control group. Study 8 demonstrated neurometabolic changes in older adults who contracted COVID-19 during participation. Study 9 confirmed that no prior studies have investigated exercise effects on cognitive function in individuals with SCI. Study 10 found increases in lactate levels, but no changes in cognitive performance after a single NMES session in persons with SCI. Study 11 described the design for a future 12-week NMES intervention study for individuals with SCI. Conclusions: The dissertation advances the understanding of exercise effects on brain health and cognition in older adults and individuals with SCI, providing a neurobiological basis for future research. Kynurenine levels, handgrip strength, and a healthy body weight emerged as potential biomarkers of brain health for older adults. The findings underscore the importance of monitoring cognitive functioning in persons with SCI. Although further research is needed to clarify the effect of different exercise modalities across populations with varying cognitive risk profiles, the present evidence reinforces the notion that physical exercise benefits brain function. A multimodal, enjoyable, and sustainable exercise programme maintained throughout life is likely to be the most effective strategy to mitigate or delay age-related cognitive decline. Keywords: aging, cognition, myokines, exercise, spinal cord injury

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)0,003
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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,179
Score d'incertitude au seuil0,255

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,140
Tête enseignante GPT0,512
Écart entre enseignants0,372 · 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'étudeObservationnel
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

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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