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Record W2079924157 · doi:10.1074/jbc.m114.554915

A Critical Role for the Neural Zinc Factor ST18 in Pancreatic β-Cell Apoptosis

2014· article· en· W2079924157 on OpenAlexafffund
Cyndi Henry, Anne-Françoise Close, Jean Buteau

Bibliographic record

VenueJournal of Biological Chemistry · 2014
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of AlbertaUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsCell biologyLipotoxicityGene knockdownBiologyApoptosisBiochemistryBiotechnologyInsulin

Abstract

fetched live from OpenAlex

The tumor suppressor gene ST18 was originally characterized as the third member of the neural zinc finger transcription factor family. However, little is known about its biological functions. Herein, we demonstrate that, in the pancreas, ST18 expression is restricted to endocrine cells. The detection of ST18 expression in pancreatic β-cells prompted us to investigate its regulation and its role in β-cell mass and function. We show that ST18 expression and activity are increased by cytotoxic concentrations of fatty acids and cytokines in INS832/13 cells. Furthermore, ST18 is also increased in islets of diet-induced obese animals. Overexpression and RNA interference knockdown studies demonstrate that ST18 induces β-cell apoptosis and curtails β-cell replication. Finally, our data suggest that ST18 impairs insulin secretion. Taken together, our findings indicate that ST18 could represent a novel transcriptional mediator of lipotoxicity and cytokine-induced β-cell death. We suggest that genetic or pharmacologic manipulations of ST18 could help maintain a functional β-cell mass.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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 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

Citations36
Published2014
Admission routes2
Has abstractyes

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