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Circadian Rhythm Affects Oxygen Uptake Kinetics In Moderate Not Heavy Exercise

2008· article· en· W1980418755 on OpenAlexaffabout
Azmy Faisal, Andrew D. Robertson, Keith R. Beavers, Richard L. Hughson

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2008
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMorningCircadian rhythmAnimal scienceKineticsVentilatory thresholdCyclingAthletesVO2 maxRhythmMedicineOxygenChemistryInternal medicinePhysical therapyHeart rateBiologyPhysics

Abstract

fetched live from OpenAlex

Understanding the effect of circadian rhythm on oxygen uptake (VO2) kinetics might be of practical importance to athletes looking to optimize their competitive performance when event scheduling and time zone changes become factors, such as the Olympic Games in Beijing, 2008. PURPOSE: In addition to investigating the presence of circadian rhythm within oxygen uptake kinetics, we examined the effect of prior moderate and heavy exercise on subsequent heavy exercise. METHODS: Following ethics approval, 8 male athletes (23.2 ± 1.1 years, 176.2 ± 2.5 cm, 70.3 ± 1.8 kg, 59.7 ± 0.8 ml/kg/min; mean ± SE) consented to participate in this study. To minimize the inter-variability among participants, an inclusion criterion of VO2 peak > 55 ml/kg/min was used. Each participant performed multiple rides of two different 24-minute cycling protocols involving 6-minute bouts at moderate and heavy intensities (80% ventilatory threshold and 85% VO2peak, respectively) interspersed with 6-minute bouts at 20 W [Protocol A: moderate (M1) followed by heavy (H2); Protocol B: heavy (H1) followed by heavy (H3)]. To increase the signal to noise ratio each protocol was repeated at least 4 times at both 7 AM and 5 PM. RESULTS: VO2 on-kinetics of the moderate bout were faster, as indicated by a smaller phase two time constant (Tau2), in the afternoon compared to the morning (22.4 ± 1.5 vs. 24.0 ± 1.5 s; p<0.01). No effect was observed on heavy rides (p =0.54). During both morning and afternoon rides, prior moderate or heavy exercise showed a similar effect by reducing Tau2 of the subsequent heavy bout [AM (H2: 23.8 ± 1.2, H3: 22.3 ± 0.8 vs. H1: 26.5 ± 0.7 s; p<0.01); PM (H2: 23.1 ± 0.7, H3: 22.7 ± 0.9 vs. H1: 26.7 ± 0.8 s; p<0.01)]. Also, the amplitude of the VO2 slow component was reduced following a heavy warm-up bout in both the morning (H3: 394 ± 22 vs. H1: 638 ± 33 ml/min; p<0.01) and afternoon (H3: 373 ± 21 vs. H1: 608 ± 38 ml/min; p<0.01); although only a trend was present following the moderate warm-up (AM: p = 0.06; PM: p = 0.20). CONCLUSION: Circadian rhythm might be present in VO2 kinetics for moderate exercise, such that kinetics are faster in the afternoon. This may be a result of enhanced oxygen extraction. However, there was no interaction between the effect of warm-up exercise and time of day. Supported by Egyptian Culture and Educational Bureau in Canada, NSERC, CHIR

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.021
GPT teacher head0.265
Teacher spread0.245 · 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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Citations0
Published2008
Admission routes2
Has abstractyes

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