Lipopolysaccharide inhibits the expression of resistin in adipocytes
Bibliographic record
Abstract
Resistin is an adipocytokine leading to insulin resistance. Endotoxin/lipopolysaccharide (LPS) has been reported to decrease the expression of resistin mRNA and protein in both lean and db/db obese mice, although the underlying mechanism remains unclear. Several models such as ex vivo culture of adipose tissues, primary rat adipocytes and 3T3-L1 adipocytes were used to further characterize the effect of LPS on the expression of resistin. LPS attenuated both the resistin mRNA and protein in a time- and dose-dependent manner. In the presence of actinomycin D, LPS failed to reduce the half-life of resistin mRNA, suggesting a transcriptional mechanism. The lipid A fraction is crucial for the inhibition of resistin expression induced by LPS. Pharmacological intervention of c-Jun N-terminal kinase (JNK) reversed the inhibitory effect of LPS. LPS down-regulated CCAAT/enhancer-binding protein α (C/EBP-α; CEBPA) and peroxisome proliferator-activated receptor γ (PPAR-γ; PPARG), while activation of C/EBP-α or PPAR-γ by either over-expressing these transcriptional factors or by rosiglitazone, an agonist of PPAR-γ, blocked the inhibitory effect of LPS on resistin. C/EBP homologous protein (CHOP-10; DDIT3) was up-regulated by LPS, while a CHOP-10 antisense oligonucleotide reversed the decrement of resistin protein induced by LPS. Taken together, these results suggest that LPS inhibits resistin expression through a unique signaling pathway involving toll-like receptor 4, JNK, CHOP-10 and C/EBP-α/PPAR-γ.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".