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Substrate Oxidation During Prolonged Upper and Lower-Body Exercise with Glucose Ingestion

2006· article· en· W2057700303 on OpenAlexaff
Jonathan Tremblay, Fran ois P ronnet, Denis Massicotte, Carole Lavoie

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsCyclingIngestionRespiratory exchange ratioAnimal scienceInternal medicineChemistryMedicineEndocrinologyHeart rateBiology

Abstract

fetched live from OpenAlex

Substrate oxidation during 120-min upper and lower-body exercise (UBE and LBE: arm cranking vs cycling) was compared in recreational cyclists (n = 6, 67 ± 6 kg, VO2max = 45 ± 5 and 69 ± 7 mL·kg−1·min−1 for UBE and LBE respectively) and kayakers (n = 6, 75 ± 8 kg, VO2max = 51 ± 9 and 55 ± 4 mL·kg−1·min−1 for UBE and LBE respectively) at ∼50% of their maximal power output on each ergometer (cyclists: 69 ± 13 and 182 ± 22 W vs kayakers: 89 ± 10 and 159 ± 6 W, UBE and LBE respectively), with water (22 mL·kg−1) or 13C-labelled glucose ingestion (2 g·kg−1), using indirect respiratory calorimetry corrected for urea excretion in urine and sweat combined with tracer techniques. Protein oxidation was not different between cyclists and kayakers but its contribution to the energy yield was higher in UBE than in LBE in both cyclists (7.4 ± 0.2 vs 3.8 ± 0.1 %, in UBE and LBE, respectively) and kayakers (6.0 ± 0.2 vs 4.8 ± 0.1 %, in UBE and LBE, respectively) because of the lower energy expenditure during UBE than LBE. When only water was ingested, total carbohydrate (CHO) oxidation was higher during LBE than UBE in both cyclists and kayakers, also because of the higher workload sustained. The contribution of CHO oxidation to the energy yield was similar during UBE and LBE in kayakers (66.6 ± 6.6 and 68.0 ± 6.4 %, respectively) but was higher in cyclists during UBE than LBE (70.6 ± 6.7 vs 65.2 ± 5.7 %). Glucose ingestion increased total CHO oxidation during UBE and LBE especially in cyclists during UBE (cyclists: 79.6 ± 6.4 and 73.0 ± 2.1 %; kayakers: 78.4 ± 1.1 and 76.8 ± 2.1 %, in UBE and LBE, respectively). This was due to a large oxidation rate of exogenous glucose which was significantly higher in kayakers than cyclists and during LBE than UBE (0.64 ± 0.16 vs 0.71 ± 0.15 g/min in UBE and LBE, respectively, in kayakers, vs 0.51 ± 0.15 and 0.62 ± 0.14 g/min in cyclists). The contribution of exogenous glucose oxidation was also slightly higher in kayakers than in cyclists especially during LBE (kayakers: 25.7 ± 6.1 and 21.2 ± 4.6 %; cyclists: 24.3 ± 6.7 and 18.6 ± 4.0 %, in UBE and LBE respectively). Exogenous glucose ingestion significantly spared endogenous CHO: the contribution of endogenous glucose oxidation was significantly reduced to 52-55, vs 65-71 % with water ingestion. These results show that substrate selection and exogenous glucose oxidation are different during prolonged exercise at ∼50 % of the maximal workload during arm cranking and cycling, and favours CHO oxidation during arm cranking. This phenomenon is more pronounced in subjects who regularly perform LBE than in those accustomed to UBE. 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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 designBench or experimental
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
Published2006
Admission routes1
Has abstractyes

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