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Enregistrement W2110761892 · doi:10.1113/jphysiol.2012.250548

Your ageing brain: the lows and highs of cerebral metabolism

2013· letter· en· W2110761892 sur OpenAlexaff
Philip N. Ainslie, Damian M. Bailey

Notice bibliographique

RevueThe Journal of Physiology · 2013
Typeletter
Langueen
DomaineMedicine
ThématiqueTraumatic Brain Injury and Neurovascular Disturbances
Établissements canadiensOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésCerebral blood flowMedicineCerebral perfusion pressureMiddle cerebral arteryInternal medicineHyperventilationCerebral autoregulationAnesthesiaOxygenationHypocapniaVasoconstrictionBlood pressureCardiologyHypercapniaCardiorespiratory fitnessIschemiaAutoregulation

Résumé

récupéré en direct d'OpenAlex

The regulation of cerebral blood flow (CBF) is critical for the maintenance of oxygen and nutrient supply to the metabolically active brain. The control of CBF is multifactorial, influenced largely by the partial pressure of arterial carbon dioxide (), mean arterial pressure (MAP) and cerebral metabolism. Exercise-induced elevations in cerebral neuronal activity and metabolism increase CBF by approximately 10–30%. Increases in exercise intensity up to approximately 60–70% of maximal oxygen uptake () increase CBF whereas a reduction towards baseline values due to hyperventilation-induced hypocapnia and subsequent cerebral vasoconstriction are observed at higher exercise intensities. With healthy ageing, CBF is reduced at rest and during exercise by 28–50% from the age of 30 to 70 years likely mediated via brain atrophy and/or reduction in neuronal activity (reviewed in: Ogoh & Ainslie, 2009). In this issue, Fisher and co-workers examined changes in blood flow velocity in the middle cerebral artery, cerebral oxygenation and metabolism in young (∼22 years) and old (∼66 years) participants at rest and during cycling exercise to exhaustion (Fisher et al. 2013). At each workload, MAP and were monitored and arterial–jugular venous differences assessed to determine the transcerebral metabolic exchange of oxygen, glucose and lactate. Their findings confirm that the middle cerebral artery was indeed reduced at rest and during exercise in older participants. However, in spite of the clear reduction in cerebral perfusion, exercise-induced changes in (estimated) the cerebral metabolic rate of oxygen, mitochondrial oxygen tension, and the cerebral uptake of oxygen, glucose and lactate were remarkably similar in both groups. Why are such findings noteworthy? This study is the first to employ a transcerebral exchange approach to determine if older participants are indeed characterized by a more pronounced reduction in CBF compared to their younger counterparts during exercise. This hypothesis is eminently justified based on previous reports of a lower CBF at rest and during exercise. The similarities between age groups emphasize two important points: (1) substrate delivery (i.e. the net arterial inflow) of oxygen, glucose and lactate is a key determinate of cerebral metabolism. However, despite arterial inflow of oxygen, lactate and glucose being lower in the aged, the net cerebral uptake was preserved. Thus, normal reductions in CBF with healthy ageing do not adversely influence the brain's capacity to use essential nutrients, even at maximal exercise. (2) The age-induced reductions in mitochondrial PO2 were similar at exhaustion despite lower absolute workloads in the older group. It would seem unlikely that maximal exercise is limited 'centrally' in the aged, given lower workloads in the face of preserved mitochondrial oxygenation. As reflected in the study, with ageing, is lower. Normally this would be reflected by small elevations in blood [H+] levels and reductions in bicarbonate (i.e. mild metabolic acidosis) resulting in a slight increase in ventilation. In addition, at maximal exercise, the older group were comparatively less acidotic. Despite these clear differences, temporal changes in the middle cerebral artery were similar, suggesting that other factors (e.g. neuronal activity) are important in provoking elevations in CBF, at least until moderate intensity exercise. After this point hypocapnia seems to dominate the relative decline in CBF. Nevertheless, given the powerful influence of , it is likely that the lower in the elderly individuals contributed to the blunted cerebrovascular conductance response observed in this group. Additionally, an inverse relationship exists between CBF and haemoglobin (Hb) to offset the reduction in (e.g. Ibaraki et al. 2010). Therefore, the lower perfusion in the aged group is likely 'underestimated' given their lower Hb and, conversely, 'overestimated' due to hypocapnia. Thus, as illustrated in Fig. 1, the age-related changes in and Hb, respectively, account for approximately 13% of the reduction in CBF and 6% of the elevation in CBF. Influence of ageing on MCAV responses during exercise (Modified from Fisher et al. 2013.) Dashed lines indicate the 'theoretical' changes in MCAV that would have occurred in the absence of age-related changes in and haemoglobin. See text for details. MCAV, middle cerebral artery. It is clear that many aspects of CBF measurement in ageing warrant further investigation. For example, what are the underlying mechanisms driving an increase in CBF during exercise, and how are these altered with age-related disease processes? Are there age, training status and/or sex differences in 'regional' (as opposed to global) CBF during exercise? This is particularly important given recent findings that demonstrate – using positron emission tomography – an age-related decline in CBF and the cerebral metabolic rate of oxygen in the cerebral cortex whereas the CBF to the primary motor and sensory areas appear to be maintained (Aanerud et al. 2012). Such findings indicate that 'regional' reductions in oxygen and nutrient supply colocalize with those (i.e. cortex) that are the most vulnerable to neurodegeneration. Addressing some of these intriguing questions will not only provide new information concerning the mechanisms by which CBF is regulated during healthy ageing, but will also provide insight into the pathophysiology of many age-related diseases.

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)0,001
score de la tête « metaresearch » (Gemma)0,006
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: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,006
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,003
Communication savante0,0040,005
Science ouverte0,0010,002
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,003

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.

Tête enseignante Opus0,027
Tête enseignante GPT0,261
Écart entre enseignants0,235 · 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

Citations10
Publié2013
Routes d'admission1
Résumé présentoui

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