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Record W1989025995 · doi:10.1677/joe-10-0044

Insulin treatment and high-fat diet feeding reduces the expression of three Tcf genes in rodent pancreas

2010· article· en· W1989025995 on OpenAlexafffund
Joshua Columbus, Yuting Chiang, Weijuan Shao, Nina Zhang, Dingyan Wang, Herbert Y. Gaisano, Qinghua Wang, David M. Irwin, Tianru Jin

Bibliographic record

VenueJournal of Endocrinology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsSt. Michael's HospitalUniversity Health NetworkUniversity of Toronto
FundersBanting and Best Diabetes Centre, University of TorontoCanadian Institutes of Health Research
KeywordsInternal medicineEndocrinologyRodentPancreasInsulinBiologyGeneGene expressionMedicineGenetics

Abstract

fetched live from OpenAlex

Specific single-nucleotide polymorphisms in intronic regions of human TCF7L2 are associated with an elevated risk of developing type 2 diabetes. Whether Tcf7l2 is expressed in pancreatic islets of rodent species at a considerable level, however, remains controversial. We used RT-PCR and quantitative RT-PCR to examine Tcf7l2 expression in rodent gut, pancreas, isolated pancreatic islets, and cultured cell lines. The expression level of Tcf7l2 was relatively lower in the pancreas compared to the gut or the pancreatic β-cell line Ins-1. Immunostaining did not detect a Tcf7l2 signal in mouse pancreatic islets. Endogenous canonical Wnt activity was not appreciable in the pancreas of TOPGAL transgenic mice. Both Tcf7 and Tcf7l1, but not Lef1, were expressed in the pancreas. The expression of the three Tcf genes (Tcf7, Tcf7l1, and Tcf7l2) in the pancreas was reduced by treatment with insulin or high-fat diet feeding, in contrast to the stimulation of Tcf7l2 expression by insulin in the gut. We suggest that hyperinsulinemia represses Tcf gene expression in the pancreas. Whether and how this reduction alters the function of pancreatic β cells during hyperinsulinemia deserves further investigation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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 designBench or experimental
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

Citations25
Published2010
Admission routes2
Has abstractyes

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