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Record W1499992233 · doi:10.1113/jphysiol.2005.089524

No effect of growth hormone administration on substrate oxidation during exercise in young, lean men

2005· article· en· W1499992233 on OpenAlexfundno aff
Mette Hansen, Rikke Morthorst, Benny Larsson, Rolf Dall, Allan Flyvbjerg, Michael Højby Rasmussen, Hans Ørskov, Michael Kjær, Kai Henrik Wiborg Lange

Bibliographic record

VenueThe Journal of Physiology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
FundersIMK Almene FondWorld Anti-Doping AgencyDanmarks GrundforskningsfondNovo NordiskSundhed og Sygdom, Det Frie Forskningsråd
KeywordsEndocrinologyInternal medicinePlaceboGrowth hormoneMedicineVO2 maxAerobic exerciseLipid oxidationHormonePhysical exerciseMealChemistryAntioxidantBiochemistryBlood pressureHeart rate

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effects of increased fat availability induced by growth hormone (GH) administration on the oxidative metabolism during exercise. Seven well-trained males (age 25 +/- 2 years (mean +/- S.E.M.); peak oxygen consumption : 62 +/- 1 ml min(-1) kg(-1) (completed four randomised trials: 120 min bicycling at 55% 4 h after receiving either 7.5 IU (2.5 mg) GH or placebo (Plc), and during rest after receiving either GH or Plc. In all studies a standardized meal was given 2 h after GH or Plc injection. GH administration resulted in an approximately 60-fold increase in serum GH concentration at rest (P < 0.0001) and during exercise (P < 0.0001). The increase in serum GH was followed by an increase in circulating glycerol at rest (8%, P < 0.0001). When combined with exercise the increase in plasma glycerol was more pronounced (GH: 716% of baseline versus Plc: 328%, P < 0.0001). However, this increase in fat mobilization did not increase fat oxidation during exercise (indirect calorimetry). In conclusion, GH administration combined with aerobic exercise increased lipolytic parameters substantially more than exercise alone, but did not further augment whole body fat oxidation.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.230
Teacher spread0.225 · 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

Citations27
Published2005
Admission routes1
Has abstractyes

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