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Faster pulmonary oxygen uptake kinetics in children vs adults due to enhancements in oxygen delivery and extraction

2012· article· en· W2132406694 on OpenAlexaff
Erwan Leclair, Serge Berthoin, Benoît Borel, David Thévenet, H. Carter, Georges Baquet, Patrick Mucci

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsYork University
Fundersnot available
KeywordsKineticsOxygenOxygen deliveryCyclingExtraction (chemistry)ChemistryInternal medicineCardiologyAnalytical Chemistry (journal)MedicineChromatographyPhysics

Abstract

fetched live from OpenAlex

This study aimed to examine if the faster pulmonary oxygen uptake (VO2p) phase 2 in children could be explained by increased O2 availability or extraction at the muscle level. For that purpose, O2 availability and extraction were assessed using deoxyhemoglobin (HHb) estimated by near-infrared spectroscopy during moderate-intensity constant load cycling exercise in children and young adults. Eleven prepubertal boys and 12 men volunteered to participate in the study. They performed one maximal graded exercise to determine the power associated with the gas exchange threshold (GET) and four constant load exercises at 90% of GET. VO2p and HHb were continuously monitored. VO2p , HHb, and estimated capillary blood flow (Qcap) kinetics were modelled after a time delay and characterized by the time to achieve 63% of the amplitude (τ) and by mean response time (MRT: time delay + τ), respectively. Mean values of τ for VO2p (P < 0.001), of MRT for HHb (P < 0.01) and of MRT for Qcap (P < 0.001) were significantly shorter in children. Faster VO2p kinetics have been shown in children; these appear due to both faster O2 extraction and delivery kinetics as indicated by faster HHb and Qcap kinetics, respectively.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.012
GPT teacher head0.272
Teacher spread0.261 · 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

Citations27
Published2012
Admission routes1
Has abstractyes

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