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Record W4408190958 · doi:10.1249/mss.0000000000003697

Changes in VO2max after 6 wk of Intensity Domain-Specific Training: Role of Central and Peripheral Adaptations

2025· article· en· W4408190958 on OpenAlexaff
Erin Calaine Inglis, Letizia Rasica, Danilo Iannetta, Mary Z. Mackie, Felipe Mattioni Maturana, Daniel A. Keir, Martin J. MacInnis, Juan M. Murias

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern UniversityUniversity of CalgaryNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsPeripheralHigh-intensity interval trainingIntensity (physics)Domain (mathematical analysis)Training (meteorology)MedicineInternal medicineGeographyMathematicsPhysicsMeteorology

Abstract

fetched live from OpenAlex

PURPOSE: This study characterized central and peripheral adaptations to domain-specific endurance exercise training. METHODS: Eighty-four young healthy participants were randomly assigned to age- and sex-matched groups of: continuous cycling in the 1) moderate-intensity (MOD), 2) lower heavy-intensity (HVY1), and 3) upper heavy-intensity (HVY2) domain; interval cycling in the 4) severe-intensity domain (i.e., high-intensity interval training (HIIT), and 5) extreme-intensity domain (i.e., sprint-interval training (SIT)); or 6) control (CON). Two 3-wk phases of training (three sessions per week) were performed. All training protocols, except SIT, were work matched. RESULTS: Maximal oxygen uptake (V̇O 2max ), maximal cardiac output (Q˙ max ), derived maximal arterial-venous oxygen difference (a-vO 2diff ), blood volume (BV), plasma volume (PV), and near-infrared spectroscopy (NIRS)-derived muscle oxidative capacity (τOxCap) were measured and compared at PRE and POST. The largest change in V̇O 2max occurred in HIIT (0.43 ± 0.20 L·min -1 ), which was greater than CON (0.02 ± 0.08 L·min -1 ), MOD (0.11 ± 0.19 L·min -1 ), HVY1 (0.24 ± 0.18 L·min -1 ), and SIT (0.28 ± 0.21 L·min -1 ) ( P < 0.05) but not HVY2 (0.36 ± 0.14 L·min -1 ) ( P > 0.05). Changes in Q˙ max were observed in HVY1 (1.6 ± 0.5 L·min -1 ), HVY2 (3.0 ± 0.6 L·min -1 ), HIIT (2.9 ± 1.2 L·min -1 ), and SIT (1.8 ± 1.4 L·min -1 ) ( P < 0.05) but not in MOD (1.2 ± 0.3 L·min -1 ) and CON (0.1 ± -0.5 L·min -1 ) ( P > 0.05). HVY2 and HIIT produced significant changes in BV (438 ± 101 and 302 ± 38 mL) and PV (198 ± 92 and 158 ± 51 mL), respectively ( P < 0.05), whereas other groups did not. CONCLUSIONS: No significant peripheral adaptations (i.e., τOxCap and a-vO 2diff ) were observed in any group ( P > 0.05). The results indicate that higher training intensities (i.e., HVY2 and HIIT) produce larger changes in V̇O 2max , which is supported predominantly by central adaptations. In addition, results suggest that, despite nonsignificant changes, the contribution of peripheral components to changes in V̇O 2max should not be dismissed.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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