Immunopathology of adipose tissue during metabolic syndrome
Bibliographic record
Abstract
Excess energy intake and a sedentary lifestyle have led to increasing incidence of obesity which is a major risk factor for the development of insulin resistance. Research in the last two decades has revealed that chronic-low grade inflammation in adipose tissue is a key link between obesity and insulin resistance. As a result, adipose tissue is now considered an active immune organ with a key role in metabolic homeostasis. In the course of obesity, cells of the immune system infiltrate visceral adipose tissue (VAT) in an active process that promotes local and systemic inflammation. This inflammatory process in VAT is driven by various subsets of immune cells and is a central mechanism connecting obesity with its metabolic complications. One key event of adipose tissue inflammation is the switching of macrophages towards a pro-inflammatory phenotype. In addition, recent research has discovered an expanding list of immune cells contributing to this inflammatory process. Pro-inflammatory immune cells are crucial to obese VAT inflammation because of their production of cytokines, which can interfere with insulin signaling in peripheral tissues. This review summarizes our current knowledge of the pathology of innate and adaptive immune cells in obese adipose tissue, with emphasis in the immunological mechanisms mediating obesity-associated insulin resistance.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".