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Enregistrement W2514038579 · doi:10.1113/jp272366

Cerebrovascular reactivity in the developing brain: influence of sex and maturation

2016· letter· en· W2514038579 sur OpenAlexaff
Lindsay Ellis, Daniela Flück

Notice bibliographique

RevueThe Journal of Physiology · 2016
Typeletter
Langueen
DomaineMedicine
ThématiqueNeonatal and fetal brain pathology
Établissements canadiensOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésReactivity (psychology)NeurosciencePsychologyInternal medicineMedicinePathology

Résumé

récupéré en direct d'OpenAlex

The brain is energetically expensive and maintenance of normal cerebral metabolism is critically dependent on the regulation of cerebral blood flow (CBF). In addition to buffering changes in blood pressure and meeting local metabolic needs, the cerebrovasculature has an exquisite sensitivity to even small changes in the partial pressure of arterial CO2 (). This response is termed cerebrovascular reactivity (CVR) and reflects the functional capacity of the cerebrovasculature to dilate and constrict, for example in response to flucations in (Ainslie & Duffin, 2009). When used in clinical settings, CVR has been used to evaluate cerebrovascular function in at-risk populations, such as in stroke and hypertensive patients (Ainslie & Duffin, 2009). A multitude of studies have investigated CVR in adults; however, studies investigating CBF and CVR in children are scarce. Maturation, unique developmental trajectories for males and females, and high cerebral metabolic demands greatly affect the regulation of CBF in children. As such, data on CBF and CVR are crucial in the pediatric population for the understanding of overall brain development and function throughout the formative years. A recent Journal of Physiology article by Leung et al. (2016) utilized powerful and quantitative techniques – arterial spin labelling (ASL) and blood-oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) – to characterize the developmental trajectories of CBF and CVR in grey (GM) and white matter (WM) in healthy children and young adults. Accordingly, this investigation highlighted the importance of accounting for age-related cerebrovascular changes when assessing developmental changes in CBF and CVR. A cohort of 17 males and 17 females (aged 9–30 years) underwent a CVR challenge using a novel prospective end-tidal forcing system capable of targeting specific end-tidal O2 and CO2 levels ( and , respectively) on a breath-by-breath basis. This challenge consisted of four blocks of alternating 60 s of normoxic ( = 100 mHg) isocapnia ( = 40 mmHg) and 45 s of normoxic ( = 100 mHg) hypercapnia ( = 45 mmHg); the protocol was terminated by a 60 s period of normoxic isocapnia resulting in a total time of 8 min. Together with the CVR challenge, imaging data were collected for 8 min with a single-shot T2*-weighted echo-planar imaging sequence. T1-weighted anatomical images with isotropic 1.0 mm voxel size were collected for co-registration and segmentation of GM and WM regions. Moreover, a pulsed ASL sequence was utilized to obtain baseline CBF data. The CVR values were created by temporally aligning waveform and the corresponding BOLD MRI datasets, followed by a resampling of the data. A linear regression between the two resulted in CVR values for each voxel on the CVR map represented as %ΔMR signal mmHg–1 (CO2). The CVR and CBF maps were then coregistered in order to calculate the global mean reactivity and mean CBF in the GM and WM for each subject. Primary results from this investigation indicate that CVR in GM and WM increases (∼55 % in GM, ∼51 % in WM) in children aged 9–14.7 years and decreases (∼27 % in GM, ∼26 % in WM) thereafter. However, the data revealed that mean CBF in GM and WM declines approximately 50% from participants aged 9–30 years in signmoidal fashion. These novel findings provide a basis for further discussion related to (1) age-related changes in CVR and CBF, (2) sex hormones as potential modulators of CVR and CBF, and (3) methodological considerations and future directions. The developmental trajectory of the paediatric brain may underscore the mechanisms of CBF regulation and the cerebrovasculature's unique response to . In particular, it is possible that the large demand of CBF during development and maturation (see Fig. 1) may limit the capacity of the cerebrovasculature to respond to changes in , thus resulting in the blunted CVR presented by Leung et al. A blunted CVR is typically interpreted as a reduced vasoactive capacity in response to steady-state elevation in ; however, whether this intrepratation is the same during the brain development in children warrants further investigation. Importantly, there are a variety of other developmental factors that have the potential to explain the disparity in CBF between children and young adults. For example, the proportion of brain to body size may account for greater CBF in children in relation to adults (Lenroot & Giedd, 2006). Moreover, the greater CBF in pre-pubertal children may be associated with the increased metabolic demands within the brain as a result of increased neuronal development (Biagi et al. 2007). Sex hormones are known modulators of cerebral endothelial function. However CBF is independent of sex hormones in pre-pubertal children (Krause, 2006). Oestrogen and the metabolites of testosterone enhance sensitivity to vasodilatory factors, such as CO2; this indicates that the onset of puberty and associated sex hormones may be important modulators in CVR and CBF (Krause, 2006). The time point of cerebrovascular measurements in females, and the associated oestrogen present as a result of the menstrual cycle, may also affect cerebral vasculature. That said, the amount of oestrogen in the blood is not consistent throughout the female menstrual cycle and is lowest during the beginning of the follicular phase and peaks prior to the ovulatory phase. Thus, it would seem ideal to assess CBF and CVR in post-pubertal females at the beginning of the follicular phase. While the data presented by Leung et al. do not show a significant difference between post-pubertal males and females, this may be a result of artifact and non-standardization of data collection during the menstrual cycle in the female participants. The data presented by Leung et al. have important implications for future investigations as they highlight the developmental changes present in CBF and CVR from childhood to young adulthood. Along with the consideration of sex and maturation in future studies on CBF and CVR, the inclusion of a higher number of post-pubertal study participants will help clarify and delineate the related classifications based on age. Moreover, it is prudent to consider the time course needed for the cerebrovasculature to reach a steady state response to changes in and subsequent central chemoreceptor signals. While an acute change in vessel diameter may occur within 6–10 s of a vasoactive stimulus, such as hypercapnia, more time (i.e. > 45 s) may be necessary to observe a steady-state change (Ainslie & Duffin, 2009). Additionally, it is possible that 60 s of normocapnia was not long enough in duration to allow the cerebrovasculature to return to baseline (Ainslie & Duffin, 2009). In total, the aforementioned factors could falsely indicate a ‘blunted’ CVR response in children on the potential basis of an increased time to reach steady state. Lastly, studies investigating the effects of age and maturation on CVR in children during wakefulness, sleep and exercise are rare. Future investigations could include the aforementioned considerations and also investigate integrative cerebral physiology in children as it relates to sex, maturation and cerebral function. This will lead to a deeper understanding of the complex, and likely non-linear and non-stationary, interactions in cerebrovascular physiology throughout the lifespan. None declared. Both authors have approved the final version of the manuscript and agree to be accountable for all aspects of the work. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed. The authors are grateful to Dr Philip N. Ainslie for his suggestions and critical review of this manuscript.

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)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut 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: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
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 savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,014
Tête enseignante GPT0,256
Écart entre enseignants0,241 · 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'étudeObservationnel
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

Citations6
Publié2016
Routes d'admission1
Résumé présentoui

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Même revueThe Journal of PhysiologyMême sujetNeonatal and fetal brain pathologyTravaux en français237 207