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Dietary proline and glutamine contribute to arginine and citrulline synthesis in healthy adult men

2010· article· en· W3171803592 on OpenAlexaff
Christopher Tomlinson, Mahroukh Rafii, Ronald O. Ball, Paul Pencharz

Bibliographic record

VenueThe FASEB Journal · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of AlbertaHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsArginineProlineGlutamineCitrullineOrnithineAmino acidChemistryBiochemistryInternal medicineEndocrinologyBiologyMedicine

Abstract

fetched live from OpenAlex

We have previously shown in human neonates and piglets that proline is the sole dietary precursor for arginine synthesis. It is unclear in adult humans whether proline is a dietary precursor for arginine. We performed a multitracer isotope study using 15 N 2 ‐ureido arginine, 15 N proline and 1‐ 13 C glutamine to further elucidate synthesis of citrulline and arginine. Primed, and intermittent infusion of labeled 15 N proline and 1‐ 13 C glutamine were given enterally to 5 healthy men fed a standardized milkshake diet. Blood was sampled at plateau enrichment between 1.5 and 3 hours. Plasma enrichment was seen for all tracers giving flux estimates of 93 μmol/kg/hr for arginine, 154 μmol/kg/hr for proline and 770 μmol/kg/hr for glutamine. Transfer of the label from proline and glutamine to arginine and the intermediaries, ornithine and citrulline, was seen in all subjects. The estimated rate of synthesis of arginine from proline was 3.7 μmol/kg/hr and from glutamine was 8.5 μmol/kg/hr. We have shown that in healthy adult humans, both proline and glutamine contribute significantly in providing the carbon chain for arginine synthesis.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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 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

Citations1
Published2010
Admission routes1
Has abstractyes

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