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Record W1589156288 · doi:10.1159/000350258

Effect of β-Alanine Supplementation on High-Intensity Exercise Performance

2013· review· en· W1589156288 on OpenAlexaff
Roger C. Harris, Trent Stellingwerff

Bibliographic record

VenueNestlé Nutrition Institute Workshop series · 2013
Typereview
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsCanadian Sport Centre Pacific
Fundersnot available
KeywordsCarnosineAlanineAnserineChemistryHistidineDipeptideInternal medicineBiochemistryFood scienceMedicineAmino acid

Abstract

fetched live from OpenAlex

Carnosine is a dipeptide of β-alanine and L-histidine found in high concentrations in skeletal muscle. Combined with β-alanine, the pKa of the histidine imidazole ring is raised to ∼6.8, placing it within the muscle intracellular pH high-intensity exercise transit range. Combination with β-alanine renders the dipeptide inert to intracellular enzymic hydrolysis and blocks the histidinyl residue from participation in proteogenesis, thus making it an ideal, stable intracellular buffer. For vegetarians, synthesis is limited by β-alanine availability; for meat-eaters, hepatic synthesis is supplemented with β-alanine from the hydrolysis of dietary carnosine. Direct oral β-alanine supplementation will compensate for low meat and fish intake, significantly raising the muscle carnosine concentration. This is best achieved with a sustained-release formulation of β-alanine to avoid paresthesia symptoms and decreasing urinary spillover. In humans, increased levels of carnosine through β-alanine supplementation have been shown to increase exercise capacity and performance of several types, particularly where the high-intensity exercise range is 1-4 min. β-Alanine supplementation is used by athletes competing in high-intensity track and field cycling, rowing, swimming events and other competitions.

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 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 score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
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 head0.030
GPT teacher head0.336
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

Citations16
Published2013
Admission routes1
Has abstractyes

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