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Record W2075288292 · doi:10.1159/000345725

Sonic Hedgehog Signaling and VACTERL Association

2012· article· en· W2075288292 on OpenAlexafffund
Esw Ngan, Kyoung-Han Kim, Chi‐chung Hui

Bibliographic record

VenueMolecular Syndromology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsHospital for Sick Children
FundersCanadian Cancer Society Research InstituteCancer Research Institute
KeywordsHedgehogSonic hedgehogPathogenesisHedgehog signaling pathwayBiologyGeneticsBioinformaticsAtresiaTracheoesophageal fistulaMedicinePathologySignal transductionAnatomy

Abstract

fetched live from OpenAlex

Hedgehog (Hh) signaling is vital for the patterning and organogenesis of almost every system. The specificity of these developmental processes is achieved through a tight spatio-temporal regulation of Hh signaling. Mice with defective Hh signal exhibit a wide spectrum of anomalies, including Vertebral defects, Anal atresia, Cardiovascular anomalies, Tracheoesophageal fistula, Renal dysplasia, and Limb defects, that resemble strikingly the phenotypes observed in VACTERL association in humans. In this review, we summarize our current understanding of mammalian Hh signaling and highlight the relevance of various mouse models for studying the etiology and pathogenesis of VACTERL association. In addition, recent advances in genetic study for unraveling the complexity of genetic inheritance of VACTERL and the implication of the Sonic hedgehog pathway in disease pathogenesis are also discussed.

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)0.000
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.231
Teacher spread0.224 · 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

Citations32
Published2012
Admission routes2
Has abstractyes

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