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Record W3215705954 · doi:10.3389/fphys.2021.723951

The Effect of Breathing Patterns Common to Competitive Swimming on Gas Exchange and Muscle Deoxygenation During Heavy-Intensity Fartlek Exercise

2021· article· en· W3215705954 on OpenAlexafffund
Kevin J. Grossman, David Lim, Juan M. Murias, Glen R. Belfry

Bibliographic record

VenueFrontiers in Physiology · 2021
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of CalgaryWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeoxygenationIntensity (physics)BreathingMedicineChemistryAnesthesiaBiochemistryPhysics

Abstract

fetched live from OpenAlex

During competitive freestyle swimming, the change of direction requires a turn followed by ∼15 m of underwater kicking at various intensities that require a ∼5 s breath-hold (BH). Upon surfacing, breathing must be regulated, as head rotation is necessary to facilitate the breath while completing the length of the pool (∼25 s). This study compared the respiratory and muscle deoxygenation responses of regulated breathing vs. free breathing, during these 25–5 s cycles. It was hypothesized that with the addition of a BH and sprint during heavy-intensity (HVY) exercise, oxygen uptake (VO2) and oxygen saturation (SatO2) would decrease, and muscle deoxygenation ([HHb]) and total hemoglobin ([Hbtot]) would increase. Ten healthy male participants (24 ± 3 years) performed 4–6 min trials of HVY cycling in the following conditions: (1) continuous free breathing (CONLD); (2) continuous with 5 s BH every 25 s (CONLD-BH); (3) Fartlek (FLK), a 5 s sprint followed by 25 s of HVY; and (4) a combined Fartlek and BH (FLK-BH). Continuous collection of VO2 and SatO2, [Hbtot], and [HHb] via breath-by-breath gas analysis and near-infrared spectroscopy (normalized to baseline) was performed. Breathing frequency and tidal volumes were matched between CONLD and CONLD-BH and between FLK and FLK-BH. As a result, VO2 was unchanged between CONLD (2.12 ± 0.35 L/min) and CONLD-BH (2.15 ± 0.42 L/min; p = 0.116) and between FLK (2.24 ± 0.40 L/min) and FLK-BH (2.20 ± 0.45 L/min; p = 0.861). SatO2 was higher in CONLD (63 ± 1.9%) than CONLD-BH (59 ± 3.3%; p < 0.001), but was unchanged between FLK (61 ± 2.2%) and FLK-BH (62 ± 3.1%; p = 0.462). Δ[Hbtot] is higher in CONLD (3.3 ± 1.6 μM) than CONLD-BH (-2.5 ± 1.2 μM; Δ177%; p < 0.001), but was unchanged between FLK (2.0 ± 1.6 μM) and FLK-BH (0.82 ± 1.4 μM; p = 0.979). Δ[HHb] was higher in CONLD (7.3 ± 1.8μM) than CONLD-BH (7.0 ± 2.0μM; Δ4%; p = 0.011) and lower in FLK (6.7 ± 1.8μM) compared to FLK-BH (8.7 ± 2.4 μM; p < 0.001). It is suggested that the unchanged VO2 between CONLD and CONLD-BH was supported by increased deoxygenation as reflected by decreased Δ[Hbtot] and blunted Δ[HHb], via apneic-driven redistribution of blood flow away from working muscles, which was reflected by the decreased SatO2. However, the preserved VO2 during FLK-BH vs. FLK has been underpinned by an increase in [HHb].

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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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