MétaCan
Menu
Back to cohort
Record W2025127402 · doi:10.1139/o10-116

Rosiglitazone regulates IL-6-stimulated lipolysis in porcine adipocytes

2010· article· en· W2025127402 on OpenAlexvenueno aff
Yongqing Yang, Gongshe Yang

Bibliographic record

VenueBiochemistry and Cell Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsnot available
FundersShanxi UniversityNational Natural Science Foundation of China
KeywordsRosiglitazoneLipolysisEndocrinologyInternal medicinePerilipinChemistryAdipocyteAdipose tissuePeroxisome proliferator-activated receptorBiologyReceptorInsulinMedicine

Abstract

fetched live from OpenAlex

Interleukin (IL)-6, a proinflammatory cytokine, stimulates adipocyte lipolysis and induces insulin resistance in obese and diabetic subjects. However, the effects of the anti-diabetic drug rosiglitazone on IL-6-stimulated lipolysis and the underlying molecular mechanism are largely unknown. In this study, we demonstrated that rosiglitazone suppressed IL-6-stimulated lipolysis in differentiated porcine adipocytes by inactivation of extracellular signal-related kinase (ERK). Meanwhile, rosiglitazone enhanced the lipolysis response of adipocytes to isoprenaline. In addition, rosiglitazone significantly reversed IL-6-induced down-regulation of several genes such as perilipin A, peroxisome proliferators activated receptor gamma (PPARγ), and fatty acid synthetase, as well as the up-regulation of IL-6 mRNA. However, mRNA expression of PPARγ coactivator-1 alpha (PCG-1α) was enhanced by rosiglitazone in IL-6-stimulated adipocytes. These results indicate that rosiglitazone suppresses IL-6-stimulated lipolysis in porcine adipocytes through multiple molecular mechanisms.

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 score0.002

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 integrity0.0000.001
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 head0.004
GPT teacher head0.216
Teacher spread0.212 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueBiochemistry and Cell BiologySame topicPeroxisome Proliferator-Activated ReceptorsFrench-language works237,207