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Record W2031248936 · doi:10.1113/jphysiol.2011.211292

Integrated human physiology: breathing, blood pressure and blood flow to the brain

2011· article· en· W2031248936 on OpenAlexaff
Philip N. Ainslie, Kurt J. Smith

Bibliographic record

VenueThe Journal of Physiology · 2011
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsCerebral blood flowHypercapniaHypocapniaCerebral perfusion pressureCerebral autoregulationBlood pressureMedicineAnesthesiaHypoxia (environmental)VasoconstrictionCardiologyInternal medicineAutoregulationChemistryAcidosisOxygen

Abstract

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The cerebral vasculature rapidly adapts to changes in perfusion pressure (cerebral autoregulation), regional metabolic requirements of the brain (neurovascular coupling), autonomic neural activity, and humoral factors (cerebrovascular reactivity). Regulation of cerebral blood flow (CBF) is therefore highly controlled and involves a wide spectrum of regulatory mechanisms that together work to maintain optimum oxygen and nutrient supply. It is well-established that the cerebral vasculature is highly sensitive to changes in arterial blood gases, in particular the partial pressure of arterial carbon dioxide (). The teleological relevance of this unique feature of the brain is likely to lie in the need to tightly control brain pH and its related impact on ventilatory control at the level of the central chemoreceptors. Changes in arterial blood gases, in particular those that cause hypoxaemia and hypercapnia, also lead to widespread effects on the systemic vasculature often leading to sympathoexcitation and related blood pressure (BP) elevations via vasoconstriction (Ainslie et al. 2005). In this issue of The Journal of Physiology an elegant study by Battisti-Charbonney and co-workers provide a relevant example of integrative human physiology (Battisti-Charbonney et al. 2011). Using continuous bilateral measurements of blood flow velocity in the middle cerebral arteries (as a surrogate index of CBF) and BP, the authors gauged the CBF responses to CO2 changes under the background condition of either hyperoxia or hypoxia. The key findings indicate that the relationship between CBF velocity over a wide range of end-tidal () values during hypocapnia (: ∼25 mmHg) and hyperoxic or hypoxic rebreathing (: 55–60 mmHg and 45–50 mmHg, respectively) are optimally fitted using a sigmoid (logistic) curve rather than a linear curve. Above the upper limits of CO2 reactivity (i.e. near the threshold (∼55 to 60 mmHg) where CBF velocity has plateaued despite further elevations in ) linear elevations in BP then progressed, presumably via chemoreflex-induced elevations in sympathetic nerve activity (SNA). Notably, the authors are the first to integrate this logistic and linear fitting approach to document the influence of and related changes in mean arterial pressure (MAP) on CBF. Collectively, these experiments demonstrate that rebreathing tests – when analysed as described – may provide an estimate of the cerebrovascular response to CO2 (and O2) at a constant BP, as well as an estimate of the cerebrovascular passive response to both BP and CO2. In the broader context of integrative physiology, these findings are noteworthy on many levels. For example, impairment in cerebrovascular reactivity to CO2 and failure to effectively counter-regulate (or autoregulate) against systemic BP fluctuations could lead to a predisposition to adverse cerebrovascular events such as stroke, infarct extension and haemorrhagic transformation of existing strokes (Aries et al. 2010). However, the critical physiological and methodological consideration is that traditional tests to assess cerebrovascular reactivity to CO2 or cerebrovascular autoregulation treat these factors as separate identities. Clearly they are not: elevations in will lead to sympathoexcitation and increases in BP via vasoconstriction (Ainslie et al. 2005). The latter, as exampled by Battisti-Charbonney and co-workers, will have independent effects on CBF from those of (Lucas et al. 2010). Conversely, emerging evidence indicates that acute changes in BP may then impact on alveolar ventilation and thus , in part via the aptly named ‘ventilatory baroreflex’ (Stewart et al. 2011). Moreover, because the brain is relatively pressure-passive (Lucas et al. 2010) and since elevations in also ‘impair’ the brain's capability to defend against BP changes (Panerai et al. 1999), considerations of BP as a critical determinant of CBF is warranted in these conditions. An example of these integrated changes in and BP occur in a myriad everyday activities: postural change, coughing, laughing, defecation, exercise, sexual activity, to name but a few. The merit of the newly proposed method as a useful clinical tool to explore the separate and combined quantification of the cerebrovascular reactivity to CO2 and BP needs to be established. However, consideration of the combined influence of both and BP on the brain would seem meritorious from a systems physiology viewpoint. In summary, in view of the article by Battisti-Charbonney et al., we have attempted to highlight some of the common factors that independently, synergistically and often antagonistically participate in the regulation of CBF. Research exploring these complex interactions is currently lacking. Future studies with particular focus on these integrative physiological mechanisms are clearly warranted in both health and disease states.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0130.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.261
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations7
Published2011
Admission routes1
Has abstractyes

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