Habitual physical activity protects against lipopolysaccharide-induced inflammation in mouse adipose tissue
Bibliographic record
Abstract
Sepsis is a systemic inflammatory response to infection, with no preventative strategies. In this study, we identify a role for habitual physical activity in the prevention of adipose tissue inflammation induced by a model of sepsis, lipopolysaccharide (LPS). Male C57BL/6J mice (8 weeks old) were housed with access to voluntary wheel running (VWR) or sedentary (SED) for 10 weeks. Mice were then injected with LPS (2 mg/kg) or saline (SAL), and tissues were removed 6 hours post-injection. VWR attenuated body, epididymal adipose tissue (eWAT), and subcutaneous inguinal adipose tissue (iWAT) mass gain, improved glucose tolerance, increased markers of mitochondrial biogenesis in iWAT and eWAT, and increased UCP-1 protein content in iWAT. In iWAT, VWR attenuated the LPS induced increase in mRNA expression of TNF-α, MCP-1, and follistatin, along with phosphorylation of STAT3. In addition, VWR had a main effect for reducing iWAT mRNA expression of IL-1β, IL-6, and SOCS3. In eWAT, VWR had a main effect for reducing mRNA expression of IL-1β, MCP-1, IL-6, and follistatin. Further, VWR increased SOCS3 mRNA expression and phosphorylation of STAT3 in SAL mice, thus the relative change in response to LPS for these markers was attenuated. The protective effect of prior physical activity occurred in conjunction with increases in the protein content of a component of the LPS binding complex, MyD88. Overall, the results from this study demonstrate that habitual physical activity can attenuate the LPS induced inflammatory response in adipose tissue and this occurs to a greater extent in iWAT compare with eWAT.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".