Effects of Obesity-Associated Chronic Inflammation on Peripheral Blood Immunophenotype Are Not Mediated by TNF in Female C57BL/6J Mice
Bibliographic record
Abstract
Abstract Chronic low-grade systemic inflammation in obesity contributes to the development and progression of aspects of metabolic syndrome. In obese male mice, expanded adipose tissue releases proinflammatory cytokines, including TNF, which promotes an increase in immature, proinflammatory, peripheral blood Ly-6Chigh monocytes. The aim of this study was to characterize how TNF alters circulating cellular immunity in female mice with diet-induced obesity. We initially quantified peripheral blood immune cells by flow cytometry in female wild-type C57BL/6J mice after 3–30 wk of allocation to a high-fat (HF) or standard chow diet. We assessed effects of diet and time on neutrophil, monocyte, B cell, NK cell, CD4+ T cell, and CD8+ T cell populations. There was a significant interaction of the effects of diet type and time on the numbers and prevalence of circulating total monocytes and Ly-6Chigh, Ly-6Clow, and Ly-6C− subsets. Circulating monocytes, in particular Ly-6Chigh monocytes, were increased in HF-fed mice compared with chow-fed mice. Ly-6Chigh monocytes from HF-fed mice also had a more immature phenotype yet were highly responsive to the chemotactic ligand CCL2 and had greater intracellular production of TNF. Comparisons of the effects of HF diet feeding in littermate wild-type (TNF+/+) and TNF−/− female mice showed that genetic ablation of TNF did not protect from higher adiposity or an increase in circulating, immature, proinflammatory Ly-6Chigh monocytes during HF diet–induced obesity. These data emphasize the importance of considering biological sex when determining the mechanisms of TNF action in obesity-induced cellular inflammation and in other chronic inflammatory conditions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".