Differential roles of tumor necrosis factor-alpha and interferon-gamma in mouse hypermetabolic and anorectic responses induced by LPS.
Bibliographic record
Abstract
Lipopolysaccharide (LPS)-induced effects on energy balance are characterized by alterations in energy expenditure (hypermetabolism) and food intake (anorexia). To study the role of tumour necrosis factor alpha (TNF-alpha) on some of these metabolic responses to endotoxin, we have used transgenic mice expressing soluble tumour necrosis factor receptor-1 IgG fusion protein (TNFR1-IgG) as well as TNF-alpha knockout (KO), lymphotoxin-alpha (LT-alpha) KO, and interferon-gamma receptor (IFN-gamma R) KO mice. The results from TNFR1-IgG transgenic mice suggest that the hypermetabolic and anorectic responses induced by LPS are independently regulated since, in the absence of TNF-alpha or LT-alpha, the LPS-induced hypermetabolism is almost prevented but not the anorexia. The anorectic response shows the strongest association with IFN-gamma since both IFN-gamma R KO mice and mice treated with anti-IFN-gamma antibody showed marked reduction in the LPS-induced anorexia compared to other mice. IFN-gamma R KO mice also have an attenuated thermogenic response to endotoxin. Anti-Asialo GM1 antibody treatment attenuated both the hypermetabolic and anorectic responses to LPS, to an extent comparable to that observed in IFN-gamma R KO mice. This finding suggests that natural killer cells (lymphocytic subsets) may be involved in IFN-gamma production and play an important role in the metabolic alterations induced by LPS. We also showed that the hypermetabolic response of control mice is associated with an upregulation of cytokine expression within the brain and an increase in permeability of the blood brain barrier. LPS-induced anorexia appears to involve peripheral cytokine expression.
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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) | 0.000 | 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".