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Record W1684727510 · doi:10.1002/pd.4264

TCF2/HNF-1beta mutations: 3 cases of fetal severe pancreatic agenesis or hypoplasia and multicystic renal dysplasia

2013· article· en· W1684727510 on OpenAlexaff
Delphine Body-Bechou, Philippe Loget, Dominique D’Hervé, Bernard Le Fiblec, Anne-Gaelle Grébille, Hélène Le Guern, Caroline Labarthe, Margaret Redpath, Anne-Sophie Cabaret-Dufour, Sylvie Odent, Alice Fiévet, Corinne Antignac, Laurence Heidet, Sophie Taque, P. Poulain

Bibliographic record

VenuePrenatal Diagnosis · 2013
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsJewish General HospitalMcGill University
Fundersnot available
KeywordsHypoplasiaAgenesisRenal agenesisPancreasMedicineDysplasiaRenal dysplasiaEndocrinologyPathologyInternal medicineKidneyAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to document the association between pancreatic agenesis or hypoplasia and multicystic renal dysplasia related to transcription factor 2 (TCF2) or hepatocyte nuclear factor 1 beta mutations. METHODOLOGY: We describe the phenotype of the pancreas and the kidneys from three fetuses heterozygous for a mutation of TCF2. CASES: Case 1 had bilateral hyperechogenic, multicystic kidneys, bilateral clubfoot and pancreatic agenesis. Case 2 had two enlarged polycystic kidneys, anamnios and pancreatic agenesis. Case 3 had multicystic renal dysplasia, oligohydramnios and hypoplasia of the tail of the pancreas. CONCLUSION: TCF2 mutations are frequently discovered in fetuses presenting with bilateral hyperechogenic kidneys. The association between pancreatic agenesis and a TCF2 mutation has not previously been reported. TCF2 deficiency in mice leads to pancreatic agenesis, suggesting that the gene is essential for pancreatic development. Our observations indicate the importance of visualizing the pancreas during ultrasound examinations if renal malformations are discovered.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.022
GPT teacher head0.257
Teacher spread0.236 · 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.

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

Citations32
Published2013
Admission routes1
Has abstractyes

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