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Record W2131140798 · doi:10.1155/2014/364976

Metabolic and Physiological Roles of Branched-Chain Amino Acids

2014· article· en· W2131140798 on OpenAlexaff
Md Monirujjaman, Afroza Ferdouse

Bibliographic record

VenueAdvances in Molecular Biology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCatabolismProtein turnoverAmino acidProtein catabolismProtein biosynthesisBiochemistryMetabolismPI3K/AKT/mTOR pathwayImmune systemMetabolic pathwayChemistryBiologySignal transductionEndocrinologyInternal medicineMedicineImmunology

Abstract

fetched live from OpenAlex

Branch chain amino acids (BCAAs) have unique properties with diverse physiological and metabolic roles. They have functions other than simple nutrition. Different diseases including metabolic disease lead to protein loss, especially muscle protein. Supplementation of BCAAs promotes protein synthesis and reduces break down, as well as improving disease conditions. They are important regulators of mTOR signaling pathway and regulate protein synthesis as well as protein turnover. BCAAs facilitate glucose uptake by liver and SK muscle and also enhance glycogen synthesis. Oxidation of BCAAs seems to be beneficial for metabolic health as their catabolism increases fatty acid oxidation and reduces risk of obesity. BCAAs are also important in immunity, brain function, and other physiological aspects of well-being. All three BCAAs are absolutely required for lymphocyte growth and proliferation. They are also important for proper immune cell function. BCAAs may influence brain protein synthesis, and production of energy and may influence synthesis of different neurotransmitters. BCAAs can be used therapeutically and future studies may be directed to investigating the diverse effects of BCAAs in different tissues and their signaling pathways.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.006
GPT teacher head0.266
Teacher spread0.260 · 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

Citations162
Published2014
Admission routes1
Has abstractyes

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