High‐fat diet‐induced downregulation of anorexic leukemia inhibitory factor in the brain stem
Bibliographic record
Abstract
OBJECTIVE: High-fat diet (HFD) is known to induce low-grade hypothalamic inflammation. Whether inflammation occurs in other brain areas remains unknown. This study tested the effect of short-term HFD on cytokine gene expression and identified leukemia inhibitory factor (LIF) as a responsive cytokine in the brain stem. Thus, functional and cellular effects of LIF in the brain stem were investigated. METHODS: Male rats were fed chow or HFD for 3 days, and then gene expression was analyzed in different brain regions for IL-1β, IL-6, TNF-α, and LIF. The effect of intracerebroventricular injection of LIF on chow intake and body weight was also tested. Patch clamp recording was performed in the nucleus tractus solitarius (NTS). RESULTS: HFD increased pontine TNF-α mRNA while downregulating LIF in all major parts of the brain stem, but not in the hypothalamus or hippocampus. LIF injection into the cerebral aqueduct suppressed food intake without conditioned taste aversion, suggesting that LIF can induce anorexia via lower brain regions without causing malaise. In the NTS, a key brain stem nucleus for food intake regulation, LIF induced acute changes in neuronal excitability. CONCLUSIONS: HFD-induced downregulation of anorexic LIF in the brain stem may provide a permissive condition for HFD overconsumption. This may be at least partially mediated by the NTS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".