Abstract 58: Signal Transducer and Activation of Transcription (STAT) 4 Deficiency Reduces Adipose Tissue Inflammation and Atherosclerosis
Bibliographic record
Abstract
Adipose tissue (AT) inflammation is key for the development of insulin resistance (IR) and contributes to progression of atherosclerosis. Previous work from our group showed that STAT4 deficiency is protective for IR in obesity and reduces atherosclerosis. However, the mechanisms are not completely understood. In this study we examined the effect of STAT4 deficiency on peri-vascular and visceral AT inflammation in atherosclerosis. To this purpose we: i) generated STAT4-deficient apo E-deficient ( Stat-4 -/- Apoe -/- ) mice and, ii) used a novel small molecule inhibitor of the IL12/STAT4 pathway (Cpd9) in Apoe -/- mice. Compared to Apoe -/- controls, Stat-4 -/- Apoe -/- female mice fed Western diet (WD) for 12 weeks showed a ~40% reduction in the thoracic aorta lesion area. Peri-aortic AT immune cells analyzed by flow cytometry showed a significant (p<0.001) and prominent decrease in CD45+CD3+ (3-fold), CD3+CD8+ (10-fold) and Nk46+ (9-fold) cells in Stat-4 -/- Apoe -/- vs. Apoe -/- mice. Also, the percentage of CD206+/F4/80+ macrophages was increased by ~8.5-fold, while the CD45+/F4/80+ cells were reduced by ~5-fold in the Stat-4 -/- Apoe -/- mice (p<0.01). In addition gene expression of TNFα and IL12p40 were both reduced by 3.5 and 6-fold, respectively in Stat-4 -/- Apoe -/- , while PPARγ expression was increased by 2-fold (p<0.05). Peri-gonadal adipose tissue showed similar reduction in CD8+ and NK cell infiltration in STAT4 deficient mice but no differences were found in macrophage numbers or phenotype. The short-term effects of IL12/STAT4 inhibition on AT inflammation were examined in Apoe -/- mice on 7 days WD alone or with oral Cpd9 treatment (0.3mmol/kg). Gene array analysis showed between 2.5- and 6-fold reduction of several cytokines and chemokines such as Ccl2, Ccl12, Cxcl13. Also, adiponectin as well and Bmp2, 4 and 7 were 4- to 15-fold reduced, suggesting reduced inflammation and possibly adipogenesis. Vegfa expression was one of the 4 up-regulated genes by 2.5-fold in Cpd9 treated mice. Collectively, data show that STAT4 reduction has early beneficial effects on AT inflammation and that peri-aortic AT inflammation is dramatically reduced. Thus targeting STAT4 may be a novel approach to treat atherosclerosis by reducing peri-vascular AT inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".