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Early protein energy malnutrition impacts life-long developmental trajectories of the sources of EEG rhythmic activity

2022· article· en· W4220785566 on OpenAlexafffund
Jorge Bosch‐Bayard, Fuleah A. Razzaq, Carlos Lopez-Naranjo, Ying Wang, Min Li, Lídice Galán‐Garcia, Ana Calzada‐Reyes, Trinidad Virues‐Alba, Arielle G. Rabinowitz, Carlos Suárez-Murias, Yanbo Guo, Manuel Sánchez-Castillo, Kassandra Roger, Anne Gallagher, Leslie S. Prichep, Simon Anderson, Christoph M. Michel, Alan C. Evans, María L. Bringas-Vega, Janina R. Galler, Pedro A. Valdés‐Sosa

Bibliographic record

VenueNeuroImage · 2022
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversité de MontréalMcGill UniversityMontreal Neurological Institute and Hospital
FundersFonds de Recherche du Québec - SantéCanada First Research Excellence FundFondation NestléNational Institutes of HealthUniversity of Electronic Science and Technology of ChinaNational Natural Science Foundation of ChinaFondation Brain Canada
KeywordsRhythmMalnutritionElectroencephalographyProtein–energy malnutritionNeurosciencePhysical medicine and rehabilitationPsychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Protein Energy Malnutrition (PEM) has lifelong consequences on brain development and cognitive function. We studied the lifelong developmental trajectories of resting-state EEG source activity in 66 individuals with histories of Protein Energy Malnutrition (PEM) limited to the first year of life and in 83 matched classmate controls (CON) who are all participants of the 49 years longitudinal Barbados Nutrition Study (BNS). qEEGt source z-spectra measured deviation from normative values of EEG rhythmic activity sources at 5-11 years of age and 40 years later at 45-51 years of age. The PEM group showed qEEGt abnormalities in childhood, including a developmental delay in alpha rhythm maturation and an insufficient decrease in beta activity. These profiles may be correlated with accelerated cognitive decline.

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 score0.701
Threshold uncertainty score0.447

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 head0.021
GPT teacher head0.252
Teacher spread0.230 · 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

Citations22
Published2022
Admission routes2
Has abstractyes

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