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Record W2154486810 · doi:10.1210/me.2008-0135

Minireview: The Wnt Signaling Pathway Effector TCF7L2 and Type 2 Diabetes Mellitus

2008· review· en· W2154486810 on OpenAlexaff
Tianru Jin, Ling Liu

Bibliographic record

VenueMolecular Endocrinology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsTCF7L2BiologyWnt signaling pathwayEffectorRegulatorTranscription factorType 2 Diabetes MellitusCell biologySignal transductionEndocrinologyCancer researchDiabetes mellitusBioinformaticsInternal medicineGeneticsGeneGenotypeSingle-nucleotide polymorphismMedicine

Abstract

fetched live from OpenAlex

Since the relationship between TCF7L2 (also known as TCF-4) polymorphisms and type 2 diabetes mellitus was identified in 2006, extensive genome-wide association examinations in different ethnic groups have further confirmed this relationship. As a component of the bipartite transcription factor beta-catenin/TCF, TCF7L2 is important in conveying Wnt signaling during embryonic development and in regulating gene expression during adulthood. Although we still do not know mechanistically how the polymorphisms within the intron regions of TCF7L2 affect the risk of type 2 diabetes, this transcriptional regulator was shown to be involved in stimulating the proliferation of pancreatic beta-cells and the production of the incretin hormone glucagon-like peptide-1 in intestinal endocrine L cells. In this review, we introduce background knowledge of TCF7L2 as a component of the Wnt signaling pathway, summarize recent findings demonstrating the association between TCF7L2 polymorphisms and the risk of type 2 diabetes, outline experimental evidence of the potential function of TCF7L2 in pancreatic and intestinal endocrine cells, and present our perspective views.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.006

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 head0.019
GPT teacher head0.273
Teacher spread0.253 · 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

Citations187
Published2008
Admission routes1
Has abstractyes

Explore more

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