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Record W2904110979 · doi:10.1002/pd.5395

Abnormal fetal cerebral and vascular development in hypoplastic left heart syndrome

2018· article· en· W2904110979 on OpenAlexaff
Caroline Kinnear, Maruti Haranal, Patrick Shannon, Edgar Jaeggi, David Chitayat, Seema Mital

Bibliographic record

VenuePrenatal Diagnosis · 2018
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMount Sinai HospitalHospital for Sick Children
Fundersnot available
KeywordsHypoplastic left heart syndromeFetusMedicinePeriventricular leukomalaciaInternal medicineGerminal matrixCardiologyGestational ageCerebral blood flowHeart diseasePregnancyIntraventricular hemorrhageBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the cerebral and vascular development in fetuses with hypoplastic left heart syndrome (HLHS). METHODS: Pregnant women carrying fetuses diagnosed with HLHS who decided to interrupt their pregnancies were included in our study. Aortic size and blood flow were assessed based from fetal echocardiography. Immunohistochemical staining was performed in brain sections obtained from pathology in fetuses with HLHS and control fetuses without heart disease. RESULTS: Twenty-seven midgestation fetal HLHS were included (gestational age, 23.3 ± 3.4 weeks). Head circumference z scores were lower in HLHS fetuses. Middle cerebral artery pulsatility index, a measure of cerebrovascular resistance, was inversely correlated with the ascending aortic z score (P < 0.05). Fetuses with HLHS had lower capillary density in the germinal matrix and their capillaries were larger compared with control fetuses with (P < 0.05). The expression of neuronal differentiation marker, FGFR1, and oligodendrocyte precursor, O4, were lower in HLHS brains compared with controls (P < 0.05). CONCLUSION: Our study identified abnormalities of vascular flow and structural brain abnormalities in fetal HLHS associated with impaired neuronal and oligodendrocyte differentiation, as well as cerebral growth impairment, early in gestation. These findings may be related in part to early vascular abnormalities.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.725

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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 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

Citations19
Published2018
Admission routes1
Has abstractyes

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