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Record W3167810339 · doi:10.2337/db19-731-p

731-P: Exercise Training Does Not Alter Resting Fatty Acid Mobilization from Adipose Tissue

2019· article· en· W3167810339 on OpenAlexaboutno aff
Michael W. Schleh, Benjamin J. Ryan, Jenna B. Gillen, Pallavi Varshney, KATIE FOUG, Alison C. Ludzki, Jeffrey F. Horowitz

Bibliographic record

VenueDiabetes · 2019
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdipose tissueInternal medicineEndocrinologyInsulin resistanceInterval trainingHigh-intensity interval trainingAerobic exerciseObesity

Abstract

fetched live from OpenAlex

Excessive fatty acid (FA) mobilization from subcutaneous adipose tissue into systemic circulation underlies many metabolic health complications associated with obesity, such as insulin resistance. Exercise is often used to help treat and/or prevent insulin resistance, but the direct effects of exercise training (without weight loss) on systemic FA mobilization are unclear. The aim of this study was to determine the effect of both high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on FA rate of appearance (FA Ra) into systemic circulation and factors regulating FA mobilization from subcutaneous adipose tissue. 18 obese adults (33±3 kg•m-2) were randomized to 12 weeks (4 d/week) of either HIIT (10 x 1 min at 90% HRmax with 1 min recovery; n=8) or MICT (45 min at 70% HRmax; n=10), and were required to maintain bodyweight throughout. Resting FA Ra (13C palmitate dilution) and abdominal subcutaneous adipose tissue samples were collected in the overnight fasted state before and after training (72h following their final exercise session). The abundance of key lipolytic and lipid storage proteins in adipose tissue were measured via immunoblot. Aerobic fitness (VO2peak) increased ∼10% after training (P = 0.002), with no difference between HIIT and MICT. Body weight remained unchanged after training (HIIT: 98±12 vs. 98±13 kg, MICT: 101±12 vs. 100±13), as did fat mass (HIIT: 40±5 vs. 39±5 kg, MICT: 42±8 vs. 41±9). Training did not affect resting FA Ra in either HIIT (16.5±3.2 vs. 15.3±1.8 μmol•kg FM-1•min-1) or MICT (16.5±2.6 vs. 15.8±1.4 μmol•kg FM-1•min-1). In line with this finding, neither HIIT nor MICT altered adipose tissue abundance or phosphorylation-state of the lipolytic enzymes ATGL and HSL, or other factors involved in FA mobilization and storage in adipose tissue (e.g., GPAT, DGAT, CGI-58, G0S2, CD36). In summary, in the absence of weight loss, 12 weeks HIIT or MICT did not alter the regulation of resting FA mobilization from subcutaneous adipose tissue. Disclosure M.W. Schleh: None. B.J. Ryan: None. J.B. Gillen: None. P. Varshney: None. K. Foug: None. A. Ludzki: None. J.F. Horowitz: Research Support; Self; American Diabetes Association. Funding National Institutes of Health (R01DK077966, P30DK089503, T32DK007245); Canadian Institutes of Health Research (DFS146190)

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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.036
GPT teacher head0.310
Teacher spread0.274 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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