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Does Improved Local O2 Distribution Explain Faster VO2 Kinetics During Smaller Compared To Larger Moderate-intensity Transitions?

2011· article· en· W2320969827 on OpenAlexaff
Matthew D. Spencer, Juan M. Murias, Braden M. R. Gravelle, Kaitlin M. McLay, John M. Kowalchuk, Donald H. Paterson

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern University
Fundersnot available
KeywordsKineticsIntensity (physics)DeoxygenationChemistrySteady state (chemistry)MathematicsPhysicsBiochemistry

Abstract

fetched live from OpenAlex

Moderate-intensity exercise (MOD) transitions of different amplitudes yield differing pulmonary O2 uptake profiles (VO2p kinetics) even within an individual; yet, the precise mechanism(s) responsible for regulating VO2p kinetics remain elusive. Insights into the balance between local muscle O2 delivery and O2 utilization (VO2m) can be gleaned from the ratio of NIRS-derived muscle deoxygenation (Δ[HHb])-to-VO2m (represented by phase II VO2p) to determine whether O2 delivery may constrain VO2p kinetics. PURPOSE: To compare the VO2p and Δ[HHb] responses to two discrete MOD step increases in work rate (WR). METHODS: Six healthy, young males each completed 4 repetitions of leg cycling MODs in 2 protocols which included 6min of cycling at 20W followed by 6min at either 90W (MOD90) or 130W (MOD130). VO2p and Δ[HHb] responses were modeled as a mono-exponential using non-linear regression, and later scaled to a relative % of the respective response (0-100%). The transient Δ[HHb]-to-VO2p ratio for each individual was calculated as the average Δ[HHb]/VO2 relative response during the 20s to 120s period of the exercise on-transient. RESULTS: Whereas phase II τVO2p was greater (p<0.05) for MOD130 (32±11s; mean ± SD) than MOD90 (25±7s), the effective Δ[HHb] response time (τ'Δ[HHb] = τΔ[HHb] + TDΔ[HHb]) was similar between conditions (MOD90: 21±2s; MOD130: 20±1s). Despite similar steady-state reliance on O2 extraction for a given VO2p (expressed as Δ[HHb]AMP/VO2pAMP (arbitrary units; a.u.); MOD90: 14±5a.u., MOD130: 13±5a.u.), a greater transient O2 delivery-to-utilization mismatch (i.e., Δ[HHb]-to-VO2 "overshoot") was observed during the on-transient of MOD130 (1.10±0.10) compared to MOD90 (1.03±0.08) where no such mismatch was observed. CONCLUSIONS: Larger amplitude MOD transitions yielded a relatively slower adjustment of VO2p compared to smaller amplitude MOD transitions; yet, the time course of adjustment of Δ[HHb] was unaffected. The modest but significant transient Δ[HHb]/VO2 "overshoot" observed in MOD130 (but not in MOD90) suggests that within an individual, constraints imposed by a progressive attenuation of local muscle O2 delivery/distribution with increases in WR may modulate adjustments of VO2m during the on-transient of exercise. Supported by NSERC

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.250
Teacher spread0.231 · 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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Citations2
Published2011
Admission routes1
Has abstractyes

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