Peroxisome Proliferator-Activated Receptor γ and Adipose Tissue—Understanding Obesity-Related Changes in Regulation of Lipid and Glucose Metabolism
Why this work is in the frame
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Bibliographic record
Abstract
CONTEXT: Adipose tissue is a metabolically dynamic organ, serving as a buffer to control fatty acid flux and a regulator of endocrine function. In obese subjects, and those with type 2 diabetes or the metabolic syndrome, adipose tissue function is altered (i.e. adipocytes display morphological differences alongside aberrant endocrine and metabolic function and low-grade inflammation). EVIDENCE ACQUISITION: Articles on the role of peroxisome proliferator-activated receptor gamma (PPARgamma) in adipose tissue of healthy individuals and those with obesity, metabolic syndrome, or type 2 diabetes were sourced using MEDLINE (1990-2006). EVIDENCE SYNTHESIS: Articles were assessed to provide a comprehensive overview of how PPARgamma-activating ligands improve adipose tissue function, and how this links to improvements in insulin resistance and the progression to type 2 diabetes and atherosclerosis. CONCLUSIONS: PPARgamma is highly expressed in adipose tissue, where its activation with thiazolidinediones alters fat topography and adipocyte phenotype and up-regulates genes involved in fatty acid metabolism and triglyceride storage. Furthermore, PPARgamma activation is associated with potentially beneficial effects on the expression and secretion of a range of factors, including adiponectin, resistin, IL-6, TNFalpha, plasminogen activator inhibitor-1, monocyte chemoattractant protein-1, and angiotensinogen, as well as a reduction in plasma nonesterified fatty acid supply. The effects of PPARgamma also extend to macrophages, where they suppress production of inflammatory mediators. As such, PPARgamma activation appears to have a beneficial effect on the relationship between the macrophage and adipocyte that is distorted in obesity. Thus, PPARgamma-activating ligands improve adipose tissue function and may have a role in preventing progression of insulin resistance to diabetes and endothelial dysfunction to atherosclerosis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it