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The Energy Cost Of Treadmill Running In Normobaric Hypoxia: The Energy Equivalent Of Oxygen Uptake Matters!

2024· article· en· W4402663089 on OpenAlexaffabout
Jared R. Fletcher, Kaylin Hughes, Spencer Skaper, Trevor A. Day, Emma Neupert

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsMount Royal University
Fundersnot available
KeywordsHypoxia (environmental)OxygenTreadmillEnergy costEnergy (signal processing)CardiologyMedicinePhysical therapyChemistryMathematicsEconomicsStatisticsEnvironmental economics

Abstract

fetched live from OpenAlex

The energy cost of running (Erun) is a key determinant of endurance running performance. Erun appears to be lower in hypoxia (HYPO) compared to normoxia (NORM); however, this observation may be a result of expressing Erun as a steady-state V̇O2 at a common speed, which potentially ignores the difference in relative intensity and the energy equivalent of V̇O2 in HYPO. The expression of Erun as an energy cost between normobaric NORM and HYPO has not yet been evaluated. PURPOSE: To compare Erun during submaximal treadmill running in NORM and HYPO expressed as a V̇O2 (L·min-1) and its energy equivalent (J·kg-1·m-1). METHODS: 15 male and female runners (29 ± 8 years, 179 ± 9 cm, 76 ± 16 kg, V̇O2max = 45.5 ± 6.7 ml·kg-1·min-1) ran for 10 minutes at 70, 80 and 90% of lactate threshold speed in two, single-blind and randomized conditions: NORM (Pb = 668 ± 3 mmHg, PO2 = 140 ± 1 mmHg and HYPO (~2300 m, FIO2 = 18.3 ± 0.1%, PO2 = 122 ± 0.5 mmHg), respectively. Erun was calculated from steady-state V̇O2 and V̇CO2 and expressed as V̇O2 (L·min-1) and energy cost (J·kg-1·m-1), respectively. The oxygen cost of ventilation was estimated from V̇E. V̇O2 and Erun were compared across conditions. RESULTS: V̇E (HYPO: 59.4 ± 3.0 L·min-1 vs NORM: 55.8 ± 3.0 L·min-1, p = 0.009, η2 = 0.05) ) and RER (HYPO: 0.89 ± 0.01 vs. NORM: 0.86 ± 0.01, p = 0.02, η2 = 0.14) were significantly higher in HYPO, resulting in a ~ 4% greater energy equivalent of V̇O2 in HYPO. When accounting for the extra cost of ventilation during running in HYPO, V̇O2 was significantly lower in HYPO (2.37 ± 0.13 L·min-1) compared to NORM (2.54 ± 0.13 L·min-1 p = 0.002, η2 = 0.10). No effect of altering FIO2 was observed for Erun across speeds (HYPO: 3.71 ± 0.18 J·kg-1·m-1 vs. NORM: 3.80 ± 0.18 J·kg-1·m-1, p = 0.17, η2 = 0.06). CONCLUSION: These data highlight the importance of assessing Erun as an energy cost per unit distance (e.g., J·kg-1·m-1) rather than a V̇O2 (i.e., in L·min-1 or ml·kg-1·min-1); the energy cost of running may incorrectly be interpreted as lower in HYPO when expressed only as V̇O2 which has important training and performance prescription implications, particularly when relative intensity (and thus the energy equivalent of V̇O2) differs, for example between HYPO and NORM shown here. This study was supported by the Turing Scheme (UK) and NSERC (Canada)

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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 score0.001
Threshold uncertainty score0.004

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 communication0.0010.001
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 head0.012
GPT teacher head0.263
Teacher spread0.250 · 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
Published2024
Admission routes2
Has abstractyes

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