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Record W2011217861 · doi:10.1139/h04-045

Elevation of Creatine in Red Blood Cells in Vegetarians and Nonvegetarians After Creatine Supplementation

2004· article· en· W2011217861 on OpenAlexafffund
Vanessa Marie MacCormick, Lisa M. Hill, Lauren MacNeil, Darren Burke, Truis Smith‐Palmer

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCreatineRed blood cellInternal medicineEndocrinologyChemistryAnimal scienceMedicineBiology

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the effect of a 5-day creatine (CR) supplementation period on red blood cell (RBC) CR uptake in vegetarian and nonvegetarian young women. Blood samples were collected from lacto-ovo vegetarians (VG, n = 6, age 21.8 +/- 1.9 yrs) and nonvegetarians (NV, n = 6, age 21.7 +/- 1.9 yrs) before and after a 5-day CR loading period (0. 3g CR/kg lean body mass/day), and from a control group of nonvegetarians (NV, n = 5, age 22.0 +/- 0.7 yrs) who did not supplement with creatine. RBC and plasma samples were analyzed for the presence of creatine. Significant increases (p < .05) in RBC and plasma CR levels were found for vegetarians and nonvegetarians following supplementation. The initial RBC CR content was significantly lower (p < .05) in the vegetarian group. There was no significant difference between vegetarians and nonvegetarians in final RBC CR content, suggesting that a ceiling had been reached. As the uptake into both muscle and RBC is moderated by creatine transporter proteins, analysis of the uptake of CR into RBC may reflect the uptake of CR into muscle, offering an alternative to biopsies.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.003
GPT teacher head0.189
Teacher spread0.185 · 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

Citations23
Published2004
Admission routes2
Has abstractyes

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