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Record W1816880077 · doi:10.1139/bcb-2015-0023

Cross-talk between α7 nAChR-mediated cholinergic pathway and acylation stimulating protein signaling in 3T3-L1 adipocytes: role of NFκB and STAT3

2015· article· en· W1816880077 on OpenAlexaffvenue
Jing Wu, Zhouyang Jiao, Zhe Zhang, Zhihui Tang, Haohao Zhang, Huiling Lü, Katherine Cianflone

Bibliographic record

VenueBiochemistry and Cell Biology · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer, Stress, Anesthesia, and Immune Response
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsSTAT33T3-L1CholinergicActivator (genetics)ChemistryTranscription factorCell biologySignal transductionInflammationAgonistSTAT proteinInternal medicineEndocrinologyBiologyAdipose tissueReceptorAdipocyteBiochemistryImmunologyMedicine

Abstract

fetched live from OpenAlex

Inflammation is a key feature in adipose tissue, especially in association with obesity comorbidies. The novel adipokine acylation stimulating protein (ASP) is one factor implicated in the inflammatory response. The disruption of the α7 nicotine acetylcholine receptor (α7nAChR), an important component of the endogenous non-neural cholinergic defense system, may exacerbate sustained inflammatory phenotype. We examined cholinergic regulation of ASP-initiated inflammatory response in 3T3-L1 adipocytes. Our results show that preincubation of 3T3-L1 cells with α7nAChR agonist GTS-21 significantly reduces ASP-mediated chemokine MCP-1 secretion, which is regulated though nuclear factor κB (NFκB) and signal transducer and activator of transcription 3 (STAT3). Treatment of 3T3-L1 cells with GTS-21 significantly reduced NFκB activation by DNA binding and STAT3 activation by disturbing post-translational modification.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

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