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Elevated intramyocellular lipid concentration in obese subjects is not reduced after diet and exercise training

2001· article· en· W2127285606 on OpenAlexaff
Patrick R. L. Malenfant, Angelo Tremblay, Éric Doucet, Pascal Imbeault, Jean‐Aimé Simoneau, Denis R. Joanisse

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGlycogenInternal medicineEndocrinologyVastus lateralis muscleWeight lossEndurance trainingChemistryMuscle fibreAnimal scienceObesitySkeletal muscleBiologyMedicine

Abstract

fetched live from OpenAlex

To determine the effects of weight loss on intramyocellular energy substrates, vastus lateralis muscle biopsies were taken from six obese subjects (body mass index 34 +/- 5 kg/m(2)) before, after 15 wk of energy restriction (ER; -700 kcal/day), and after a further average 20.7 +/- 1.6 wk of endurance training plus low-fat diet (ET-LFD). Body weight fell from 100 +/- 6 to 89 +/- 6 kg during ER and to 84 +/- 4 kg after ET-LFD. Lipids and glycogen were histochemically measured in type I, IIA, and IIB fibers. Total muscle glycogen content (MGC; per 100 fibers) decreased after ER [from 72 +/- 13 to 55 +/- 8 arbitrary units (AU)]. A similar but not significant decrease was seen in total muscle lipid content (MLC; 14 +/- 5 to 9 +/- 1 AU). After ET-LFD, MGC returned to initial values (74 +/- 8 AU), and MLC approached near-initial values (12 +/- 3 AU). Individual fiber lipid concentration did not change throughout the protocol in all fiber types, whereas glycogen concentration increased after ET-LFD. The training effects of ET-LFD were measured as increasing activities of key mitochondrial enzymes. Although total muscle energy reserves can be reduced after weight loss, their concentration within individual myofibers remains elevated. Weight loss does not appear sufficient to correct the potential detrimental effects of high intracellular lipid concentrations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.656
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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 teacher head, 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".

Quick stats

Citations79
Published2001
Admission routes1
Has abstractyes

Explore more

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