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Record W2592783968 · doi:10.1111/acer.13363

Heavy Prenatal Alcohol Exposure is Related to Smaller Corpus Callosum in Newborn <scp>MRI</scp> Scans

2017· article· en· W2592783968 on OpenAlexaff
Sandra W. Jacobson, Joseph L. Jacobson, Christopher D. Molteno, Christopher M. R. Warton, Pia Wintermark, H. Eugene Hoyme, Greetje de Jong, Paul A. Taylor, Fleur L. Warton, Nadine M. Lindinger, R. Colin Carter, Neil C. Dodge, P. Ellen Grant, Simon K. Warfield, Lilla Zöllei, André van der Kouwe, Ernesta M. Meintjes

Bibliographic record

VenueAlcoholism Clinical and Experimental Research · 2017
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMontreal Children's Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Alcohol Abuse and AlcoholismSouth African Medical Research Council
KeywordsCorpus callosumPrenatal alcohol exposurePrenatal exposureFetal alcoholMedicineMagnetic resonance imagingPsychologyAlcoholNeurosciencePregnancyGestationRadiologyBiologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Magnetic resonance imaging (MRI) studies have consistently demonstrated disproportionately smaller corpus callosa in individuals with a history of prenatal alcohol exposure (PAE) but have not previously examined the feasibility of detecting this effect in infants. Tissue segmentation of the newborn brain is challenging because analysis techniques developed for the adult brain are not directly transferable, and segmentation for cerebral morphometry is difficult in neonates, due to the latter's incomplete myelination. This study is the first to use volumetric structural MRI to investigate PAE effects in newborns using manual tracing and to examine the cross-sectional area of the corpus callosum (CC). METHODS: Forty-three nonsedated infants born to 32 Cape Coloured heavy drinkers and 11 controls recruited prospectively during pregnancy were scanned using a custom-designed birdcage coil for infants, which increases signal-to-noise ratio almost 2-fold compared to the standard head coil. Alcohol use was ascertained prospectively during pregnancy, and fetal alcohol spectrum disorders diagnosis was conducted by expert dysmorphologists. Data were acquired using a multi-echo FLASH protocol adapted for newborns, and a knowledge-based procedure was used to hand-segment the neonatal brains. RESULTS: CC was disproportionately smaller in alcohol-exposed neonates than controls after controlling for intracranial volume. By contrast, CC area was unrelated to infant sex, gestational age, age at scan, or maternal smoking, marijuana, or methamphetamine use during pregnancy. CONCLUSIONS: Given that midline craniofacial anomalies have been recognized as a hallmark of fetal alcohol syndrome in humans and animal models since this syndrome was first identified, the CC deficit identified here in newborns may support early identification of a range of midline structural impairments. Smaller CC during the newborn period may provide an early indicator of fetal alcohol-related cognitive deficits that have been linked to this critically important brain structure in childhood and adolescence.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.117
GPT teacher head0.456
Teacher spread0.338 · 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 designObservational
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

Citations72
Published2017
Admission routes1
Has abstractyes

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