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Record W1975122193 · doi:10.1152/ajpregu.00516.2013

Cardiovascular responses to water immersion in humans: impact on cerebral perfusion

2014· article· en· W1975122193 on OpenAlexaff
Howard H. Carter, Angela L. Spence, Christopher J. A. Pugh, Philip N. Ainslie, Louise H. Naylor, Daniel J. Green

Bibliographic record

VenueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Disease Prevention
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsMedicineCerebral blood flowCerebral perfusion pressureHemodynamicsMiddle cerebral arteryCardiologyPerfusionInternal medicineBlood pressureAnesthesiaCerebral arteriesImmersion (mathematics)Ischemia

Abstract

fetched live from OpenAlex

Episodic increases in cerebrovascular perfusion and shear stress may have beneficial impacts on endothelial function that improve brain health. We hypothesized that water immersion to the level of the right atrium in humans would increase cerebral perfusion. We continuously measured, in 9 young (means ± SD, 24.6 ± 2.0 yr) healthy men, systemic hemodynamic variables along with blood flows in the common carotid and middle and posterior cerebral arteries during controlled filling and emptying of a water tank to the level of the right atrium. Mean arterial pressure (80 ± 9 vs. 91 ± 12 mmHg, P < 0.05), cardiac output (4.8 ± 0.7 vs. 5.1 ± 0.6 l/min, P < 0.05) and end-tidal carbon dioxide (PetCO2, 39.5 ± 2.0 vs. 44.4 ± 3.5 mmHg, P < 0.05) increased with water immersion, along with middle (59 ± 6 vs. 64 ± 6 cm/s, P < 0.05) and posterior cerebral artery blood flow velocities (41 ± 9 vs. 44 ± 10 cm/s, P < 0.05). These changes were reversed when the tank was emptied. Water immersion is associated with hemodynamic and PetCO2 changes, which increase cerebral blood velocities in humans. This study provides an evidence base for future studies to examine the potential additive effect of exercise in water on improving cerebrovascular health.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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 teacher head, 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".

Quick stats

Citations78
Published2014
Admission routes1
Has abstractyes

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