MétaCan
Menu
Back to cohort
Record W2222866022 · doi:10.1152/ajpendo.0319.2001

Phenylalanine requirement in children with classical PKU determined by indicator amino acid oxidation

2002· article· en· W2222866022 on OpenAlexaff
Glenda Courtney‐Martin, Rachelle Bross, Mahroukh Raffi, Joe T.R. Clarke, Ronald O. Ball, Paul B. Pencharz

Bibliographic record

VenueAmerican Journal of Physiology-Endocrinology and Metabolism · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of AlbertaUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsPhenylalanineAmino acidChemistryCrossover studyPopulationInternal medicineEndocrinologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Dietary restriction of phenylalanine is the main treatment for phenylketonuria (PKU), and current estimates of requirements are based on plasma phenylalanine concentration and growth. The present study aimed to determine more precisely the phenylalanine requirements in patients with the disease by use of indicator amino acid oxidation, with L-[1-13C]lysine as the indicator. Breath 13CO2 production (F 13 CO2) was used as the end point. Finger-prick blood samples were also collected for measurement of phenylalanine to relate phenylalanine intake to blood phenylalanine levels. The mean phenylalanine requirement, estimated using a two-phase linear regression crossover analysis, was 14 mg. kg(-1). day(-1), and the safe population intake (upper 95% confidence interval of the mean) was found to be 19.5 mg. kg(-1). day(-1). A balance between phenylalanine intake and the difference between fed and fasted blood phenylalanine concentration was observed at an intake of 20 mg. kg(-1). day(-1). The similarity between these two values (19.5 and 20 mg. kg(-1). day(-1)) suggests that the maximal phenylalanine intake for children with PKU should be no higher than 20 mg. kg(-1). day(-1).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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

Citations57
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Endocrinology and MetabolismSame topicMetabolism and Genetic DisordersFrench-language works237,207