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Record W2950133516 · doi:10.21037/atm.2019.05.52

Nutrition and exercise in Pompe disease

2019· review· en· W2950133516 on OpenAlexafffund
Mark A. Tarnopolsky, Mats I. Nilsson

Bibliographic record

VenueAnnals of Translational Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchSanofi
KeywordsMedicineMicronutrientAutophagyDiseaseEnergy expenditureMedical nutrition therapyArginineIntensive care medicineVitamin B12VitaminObesityPhysical therapyPhysiologyInternal medicineEndocrinologyBioinformaticsBiologyAmino acidBiochemistryPathology

Abstract

fetched live from OpenAlex

. Nutritional assessment is important in patients with locomotor disability because the relative hypodynamia limits energy expenditure and thus the total amount of energy must be reduced to avoid obesity. A lower total energy intake often leads to lower protein and micronutrient intake. Consequently, ensuring that Pompe patients are tested for and replaced for deficiencies (protein, vitamin D, vitamin B12, etc.) is an important aspect of care. Furthermore, given the role of autophagy in the pathophysiology of PD and the fact that fasting induces autophagy, it is important that strategies such as nutritional timing and amino acid intake (L-arginine, L-leucine) be evaluated as therapies. Exercise interventions have been shown to improve six-minute walk testing distance by more than what was seen in the seminal ERT study in late-onset PD. Exercise therapy can also activate autophagy, and this is likely another component of its efficacy. The current review will evaluate the theoretical and practical aspects of nutrition and exercise as therapies for patients with PD.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.218
GPT teacher head0.456
Teacher spread0.238 · 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 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

Citations22
Published2019
Admission routes2
Has abstractyes

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