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Record W3020104289 · doi:10.14814/phy2.14430

Comparable blood velocity changes in middle and posterior cerebral arteries during and following acute high‐intensity exercise in young fit women

2020· article· en· W3020104289 on OpenAlexaff
Lawrence Labrecque, Audrey Drapeau, Kevan Rahimaly, Sarah Imhoff, François Billaut, Patrice Brassard

Bibliographic record

VenuePhysiological Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsKinesiologyMedicineGerontologyLibrary scienceMedical education

Abstract

fetched live from OpenAlex

The cerebral blood flow response to high-intensity interval training (HIIT) remains unclear. HIIT induces surges in mean arterial pressure (MAP), which could be transmitted to the brain, especially early after exercise onset. The aim of this study was to describe regional cerebral blood velocity changes during and following 30 s of high-intensity exercise. Ten women (age: 27 ± 6 years; VO2max: 48.6 ± 3.8 ml·kg·min−1) cycled for 30 s at the workload reached at O2max followed by 3min of passive recovery. Middle (MCAvmean) and posterior cerebral artery mean blood velocities (PCAvmean; transcranial Doppler ultrasound), MAP (finger photoplethysmography), and end-tidal carbon dioxide partial pressure (PETCO2; gaz analyzer) were measured. MCAvmean (+19 ± 10%) and PCAvmean (+21 ± 14%) increased early after exercise onset, returning toward baseline values afterward. MAP increased throughout exercise (p < .0001). PETCO2 initially decreased by 3 ± 2 mmHg (p < .0001) before returning to baseline values at end-exercise. During recovery, MCAvmean (+43 ± 15%), PCAvmean (+42 ± 15%), and PETCO2 (+11 ± 3 mmHg; p < .0001) increased. In young fit women, cerebral blood velocity quickly increases at the onset of a 30-s exercise performed at maximal workload, before returning to baseline values through the end of the exercise. During recovery, cerebral blood velocity augments in both arteries, along with PETCO2.

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)0.000
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 score0.724
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.242
Teacher spread0.214 · 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

Citations34
Published2020
Admission routes1
Has abstractyes

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