Naringenin has anti‐inflammatory properties in macrophage and <i>ex vivo</i> human whole‐blood models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Periodontitis is a chronic inflammatory disease of bacterial etiology, affecting tooth-supporting tissues. The host inflammatory response to periodontopathogens, notably the high and continuous production of cytokines, is considered a major factor causing the local tissue destruction observed in periodontitis. The aim of the present study was to investigate the effect of naringenin, a major flavanone in grapefruits and tomatoes, on the lipopolysaccharide-induced pro-inflammatory cytokine production by host cells, using two different models. MATERIAL AND METHODS: The effect of naringenin was characterized using macrophages stimulated with the lipopolysaccharide of either Aggregatibacter actinomycetemcomitans or Escherichia coli and using whole blood stimulated with A. actinomycetemcomitans lipopolysaccharide, in the presence or absence of naringenin. Lipopolysaccharide-induced interleukin-1 beta, interleukin-6, interleukin-8 and tumor necrosis factor-alpha production by macrophages and whole-blood samples treated with naringenin were evaluated using an enzyme-linked immunosorbent assay. Changes in the phosphorylation states of macrophage kinases induced by A. actinomycetemcomitans lipopolysaccharide and naringenin were characterized by immunoblot screening. RESULTS: Our results clearly indicated that naringenin is a potent inhibitor of the pro-inflammatory cytokine response induced by lipopolysaccharide in both macrophages and in whole blood. Naringenin markedly inhibited the phosphorylation on serines 63 and 73 of Jun proto-oncogene-encoded AP-1 transcription factor in lipopolysaccharide-stimulated macrophages. CONCLUSION: The results from the present study suggest that naringenin holds promise as a therapeutic agent for treating inflammatory diseases such as periodontitis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it