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Record W3155975690 · doi:10.1016/j.ymgmr.2021.100757

Long term follow-up of the dietary intake in propionic acidemia

2021· article· en· W3155975690 on OpenAlexaff
Amira Mobarak, Sylvia Stöckler, Ramona Salvarinova, Clara van Karnebeek, Gabriella Horváth

Bibliographic record

VenueMolecular Genetics and Metabolism Reports · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsPacific Centre for Reproductive MedicineUniversity of British ColumbiaBC Children's Hospital
Fundersnot available
KeywordsValineLeucineIsoleucineDietary managementMethionineMedicineAmino acidDietary Reference IntakeInternal medicinePropionic acidemiaReference Daily IntakeEndocrinologyChemistryFood scienceBiochemistryNutrient

Abstract

fetched live from OpenAlex

Long-term dietary management of Propionic acidemia (PA) includes natural protein restriction, and supplementation with medical formula enriched with leucine (Leu) and free of valine (Val), isoleucine (Ileu), methionine (Met), and threonine (Thr). As PA medical formulas have high leucine content, concerns started to arise regarding potential long-term health risks of unbalanced leucine intake. PA patients have chronically low plasma levels of Ile and Val, which led to the paradoxical need to supplement with propiogenic single amino acids (AAs). Our report takes a retrospective look at the long-term dietary management of four patients and its reflection on their plasma amino acids. The patients' total protein intake was above the recommended dietary allowance (RDA) and had a high Leu/Val and Leu/Ile intake ratios in diet. Despite adequate total protein intake, patients had chronically low plasma Ile and Val and a high plasma Leu/Val and Leu/Ile ratios, which could be attributed to high Leu intake. We conclude that the best approach to PA dietary management is to only use medical formula with patients not meeting their RDA through natural protein, and to monitor plasma amino acids levels closely.

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 score0.411
Threshold uncertainty score0.789

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 head0.008
GPT teacher head0.235
Teacher spread0.227 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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