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Delineating the Role of Cerebral Blood Flow and Hypocapnia on Neuromuscular Function

2015· article· en· W2463809516 on OpenAlexaff
Geoffrey L. Hartley, Cody L. Watson, Matthew Greenway, Philip N. Ainslie, Stephen S. Cheung

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2015
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of British Columbia, Okanagan CampusBrock University
Fundersnot available
KeywordsHypocapniaHyperventilationCerebral blood flowIsometric exerciseAnesthesiaMedicineTranscranial DopplerMiddle cerebral arteryCardiologyInternal medicineIschemiaAcidosisHypercapnia

Abstract

fetched live from OpenAlex

Neuromuscular fatigue, defined as the inability of a muscle to maintain a given level of force regardless of whether or not a task can be sustained, has been attributed, in part, to central mechanisms. Although reductions in cerebral blood flow (CBF) may be implicated in the development of central fatigue, the contribution from hypocapnic-reductions (i.e., PETCO2) in CBF versus reductions in CBF per se has yet to be isolated. PURPOSE: To examine the hypothesis that hypocapnia, independent of concomitant reductions in CBF, cause impairments in neuromuscular function. METHODS: Neuromuscular function, as indicated by motor evoked potentials (MEP), M-waves and cortical voluntary activation (cVA) of the flexor carpal radialis muscle during isometric wrist flexion, was assessed in 8 males (31±12 y) during 3 separate conditions: 1) cyclooxygenase inhibition using Indomethacin (Indo) to selectively reduce CBF; 2) controlled hyperventilation-induced hypocapnia (Hypocapnia); and 3) isocapnic hyperventilation (Isocapnia). CBF was estimated using transcranial Doppler ultrasound velocity measurements of the middle cerebral artery. Change from baseline and comparison of the 3 conditions was assessed using two-way repeated measures ANOVA. Relationships between variables were assessed using Pearson‘s correlations. RESULTS: The experimental conditions successfully isolated CBF and PETCO2. MEP amplitude (% M-wave amplitude) increased in hypocapnia (14.6±9.5%, p < 0.01) in comparison to Indo (-2.0±2.8%) and Isocapnia (0.6±1.8%); however, no significant changes were observed in M wave (p = 0.666) or cVA (p = 0.117). Correlation analysis revealed that MEP amplitude was inversely associated with PETCO2 (r = -0.54, p < 0.01) and cVA was weakly associated with CBF (r = 0.30, p < 0.05). CONCLUSIONS: Increased motor cortex excitability appears to be exclusive to hypocapnia but not reductions in CBF per se. However, a weak relationship between reductions in CBF and cVA exists, such that further research is required to confirm this finding and explore the potential implications. Supported by NSERC Discovery 227912-2012.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.254
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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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