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Record W2260019640 · doi:10.1155/2016/3582616

Identification of HNF4A Mutation p.T130I and HNF1A Mutations p.I27L and p.S487N in a Han Chinese Family with Early-Onset Maternally Inherited Type 2 Diabetes

2016· article· en· W2260019640 on OpenAlexaff
Ying Yang, Taicheng Zhou, Yongying Liu, Xiao Li, Wenxue Wang, David M. Irwin, Ya‐Ping Zhang

Bibliographic record

VenueJournal of Diabetes Research · 2016
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsHNF1AGeneticsMutationAge of onsetMaturity onset diabetes of the youngDiabetes mellitusPhenotypeFamily historyBiologyGeneMedicineInternal medicineEndocrinologyDisease

Abstract

fetched live from OpenAlex

Maturity-onset diabetes of the young (MODY) is characterized by the onset of diabetes before the age of 25 years, positive family history, high genetic predisposition, monogenic mutations, and an autosomal dominant mode of inheritance. Here, we aimed to investigate the mutations and to characterize the phenotypes of a Han Chinese family with early-onset maternally inherited type 2 diabetes. Detailed clinical assessments and genetic screening for mutations in the HNF4α, GCK, HNF-1α, IPF-1, HNF1β, and NEUROD1 genes were carried out in this family. One HNF4A mutation (p.T130I) and two HNF1A polymorphisms (p.I27L and p.S487N) were identified. Mutation p.T130I was associated with both early-onset and late-onset diabetes and caused downregulated HNF4A expression, whereas HNF1A polymorphisms p.I27L and p.S487N were associated with the age of diagnosis of diabetes. We demonstrated that mutation p.T130I in HNF4A was pathogenic as were the predicted polymorphisms p.I27L and p.S487N in HNF1A by genetic and functional analysis. Our results show that mutations in HNF4A and HNF1A genes might account for this early-onset inherited type 2 diabetes.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.295
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.024
GPT teacher head0.330
Teacher spread0.305 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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