Obesity predisposes to Th17 bias
Bibliographic record
Abstract
Obesity is associated with numerous inflammatory conditions including atherosclerosis, autoimmune disease and cancer. Although the precise mechanisms are unknown, obesity-associated rises in TNF-alpha, IL-6 and TGF-beta are believed to contribute. Here we demonstrate that obesity selectively promotes an expansion of the Th17 T-cell sublineage, a subset with prominent pro-inflammatory roles. T-cells from diet-induced obese mice expand Th17 cell pools and produce progressively more IL-17 than lean littermates in an IL-6-dependent process. The increased Th17 bias was associated with more pronounced autoimmune disease as confirmed in two disease models, EAE and trinitrobenzene sulfonic acid colitis. In both, diet-induced obese mice developed more severe early disease and histopathology with increased IL-17(+) T-cell pools in target tissues. The well-described association of obesity with inflammatory and autoimmune disease is mechanistically linked to a Th17 bias.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".