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Record W2320932223 · doi:10.1097/mco.0b013e32835a88ee

Muscle protein anabolism in type 2 diabetes

2012· review· en· W2320932223 on OpenAlexaff
Maya Bassil, Réjeanne Gougeon

Bibliographic record

VenueCurrent Opinion in Clinical Nutrition & Metabolic Care · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsRoyal Victoria HospitalRoyal Victoria Regional Health CentreMcGill University Health Centre
Fundersnot available
KeywordsAnabolismSarcopeniaEndocrinologyInternal medicineInsulin resistanceLeucineCatabolismInsulinSkeletal muscleMedicineType 2 diabetesAmino acidMuscle massDiabetes mellitusBiologyMetabolismBiochemistry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Protein anabolism is abnormal in human type 2 diabetes (T2DM). We review studies of anabolic stimuli that identify potential causes. If uncorrected, and combined with aging effects, they will compromise muscle function and mass. Knowing causes can guide studies of preventive and treatment measures. RECENT FINDINGS: T2DM accelerates age-related decreases in muscle mass. This could be related to insulin resistance of whole-body protein anabolism demonstrated in hyperglycemic obese men. In contrast, their protein anabolic response to hyperaminoacidemia suggested that ample amino acid administration, especially branched chain amino acids might overcome such insulin resistance. One study of chronic leucine supplementation in elderly T2DM patients did not increase muscle mass. However, they lacked sarcopenia and had adequate dietary protein intake, so may be atypical. Exercise induced similar increases in muscle protein synthesis, mass and strength in healthy and T2DM patients suggesting that physical activity might also overcome insulin resistance of protein anabolism. SUMMARY: Muscle protein anabolism in T2DM is resistant to the action of insulin but perhaps not to amino acid supply or exercise. Whether leucine supplementation improves muscle mass and function in persons with T2DM (especially elderly) with reduced protein intake or muscle mass needs to be determined.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.131
GPT teacher head0.436
Teacher spread0.305 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations77
Published2012
Admission routes1
Has abstractyes

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