MétaCan
Menu
Back to cohort
Record W4311133826 · doi:10.3390/ph15121535

Cooccurring Type 1 Diabetes Mellitus and Autoimmune Thyroiditis in a Girl with Craniofrontonasal Syndrome: Are EFNB1 Variants Associated with Autoimmunity?

2022· article· en· W4311133826 on OpenAlexafffund
Sebla Güneş, Jiangping Wu, Berk Özyılmaz, Reyhan Deveci Sevim, Tolga Ünüvar, Ahmet Anık

Bibliographic record

VenuePharmaceuticals · 2022
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health Research
KeywordsMedicinePolyuriaThyroiditisAutoimmunityAutoimmune thyroiditisType 1 diabetesPediatricsDiabetes mellitusImmunologyInternal medicineDermatologyThyroidEndocrinologyDisease

Abstract

fetched live from OpenAlex

Craniofrontonasal syndrome (CFNS), also known as craniofrontonasal dysplasia, is an X-linked inherited developmental malformation caused by mutations in the ephrin B1 (EFNB1) gene. The main phenotypic features of the syndrome are coronal synostosis, hypertelorism, bifid nasal tip, dry and curly hair, and longitudinal splitting of nails. A 9-year-and-11-month-old girl with CFNS was admitted due to polyuria, polydipsia, fatigue, and abdominal pain. On physical examination, she had the classical phenotypical features of CFNS. Genetic tests revealed a c.429_430insT (p.Gly144TrpfsTer31) heterozygote variant in the EFNB1 coding region. The patient was diagnosed with type 1 diabetes mellitus (T1DM) and autoimmune thyroiditis based on laboratory findings and symptoms. The mother of the patient, who had the same CFNS phenotype and EFNB1 variant, was screened for autoimmune diseases and was also with autoimmune thyroiditis. This is the first report describing the association of CFNS with T1DM and autoimmune thyroiditis in patients with EFNB1 mutation.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.031
GPT teacher head0.288
Teacher spread0.257 · 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 designCase report
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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuePharmaceuticalsSame topicErythrocyte Function and PathophysiologyFrench-language works237,207