Osteopontin mediates obesity-induced adipose tissue macrophage infiltration and insulin resistance in mice
Bibliographic record
Abstract
Obesity is associated with a state of chronic, low-grade inflammation characterized by abnormal cytokine production and macrophage infiltration into adipose tissue, which may contribute to the development of insulin resistance. During immune responses, tissue infiltration by macrophages is dependent on the expression of osteopontin, an extracellular matrix protein and proinflammatory cytokine that promotes monocyte chemotaxis and cell motility. In the present study, we used a murine model of diet-induced obesity to examine the role of osteopontin in the accumulation of adipose tissue macrophages and the development of insulin resistance during obesity. Mice exposed to a high-fat diet exhibited increased plasma osteopontin levels, with elevated expression in macrophages recruited into adipose tissue. Obese mice lacking osteopontin displayed improved insulin sensitivity in the absence of an effect on diet-induced obesity, body composition, or energy expenditure. These mice further demonstrated decreased macrophage infiltration into adipose tissue, which may reflect both impaired macrophage motility and attenuated monocyte recruitment by stromal vascular cells. Finally, obese osteopontin-deficient mice exhibited decreased markers of inflammation, both in adipose tissue and systemically. Taken together, these results suggest that osteopontin may play a key role in linking obesity to the development of insulin resistance by promoting inflammation and the accumulation of macrophages in adipose tissue.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".