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Maternal Care Modulates the Relationship between Prenatal Risk and Hippocampal Volume in Women But Not in Men

2007· article· en· W2050889951 on OpenAlexafffund
Claudia Buß, Catherine Lord, Mehereen Wadiwalla, Dirk H. Hellhammer, Sonia Lupien, Michael J. Meaney, Jens C. Pruessner

Bibliographic record

VenueJournal of Neuroscience · 2007
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsDouglas Mental Health University InstituteDouglas College
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsHippocampal formationHippocampusVulnerability (computing)PsychologyCognitionPhysiologyMagnetic resonance imagingBirth weightMedicineClinical psychologyNeuroscienceAudiologyDevelopmental psychologyPregnancyBiology

Abstract

fetched live from OpenAlex

Smaller hippocampal volume is associated with psychiatric disorders. Variations in hippocampal volume are discussed as both a consequence of the neurotoxic effects of stress and as a pre-existing condition leading to increased vulnerability for cognitive and emotional impairments. To investigate whether early experience can account for variability in hippocampal volume in adulthood (vulnerability hypothesis), we assessed the relationship between birth weight and hippocampal volume in 44 subjects. The reported quality of maternal care in early childhood, as evaluated by the Parental Bonding Inventory, was used as index of the quality of the postnatal environment. Hippocampal volume was assessed from magnetic resonance images using a manual segmentation protocol. We show that birth weight significantly predicts hippocampal volume in adulthood only in female subjects reporting low maternal care. The results suggest that the postnatal environment modulates the neurodevelopmental consequences of prenatal risk and that this effect is sex-specific.

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)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.037
GPT teacher head0.306
Teacher spread0.269 · 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

Citations189
Published2007
Admission routes2
Has abstractyes

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