<i>Cucurbita ficifolia</i> (Cucurbitaceae) modulates inflammatory cytokines and IFN-γ in obese mice
Bibliographic record
Abstract
This study investigated the effect of aqueous extract of Cucurbita ficifolia Bouché on systemic chronic inflammation in an obesity model induced by monosodium glutamate (MSG) via modulating the expression of adipokines (TNF-α, IL-6, resistin, and adiponectin) and immune-regulatory cytokines (IFN-γ and IL-10). Cucurbita ficifolia extract was administered daily by gavage to lean and MSG-obese mice for 30 days. At the end of treatment, cytokine mRNA expression in adipose tissue was determined by real-time polymerase chain reaction (PCR), and the protein levels of these cytokines were also quantified by enzyme-linked immunosorbent assay (ELISA). Cucurbita ficifolia extract decreased body mass and inflammation in MSG-obese mice by reducing the expression of TNF-α and IL-6; these decreases were parallel to significant reductions in protein levels. The extract also increased protein levels of IL-10 in lean mice and IFN-γ in both lean and MSG-obese mice. In conclusion, C. ficifolia extract modulates systemic chronic inflammation in MSG-obese mice and could have a beneficial effect on the adaptive immune system in obesity.
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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".