Naringenin inhibits human osteoclastogenesis and osteoclastic bone resorption
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Naringenin, a naturally occurring flavonoid, possesses a wide range of pharmacological properties. The purpose of this study was to investigate the effect of naringenin on human osteoclastogenesis and osteoclastic bone resorption. MATERIAL AND METHODS: Naringenin was tested in a human osteoclastogenesis model using primary osteoclast precursor cells activated by receptor activator of nuclear factor-kappaB ligand (RANKL) and macrophage colony-stimulating factor (M-CSF) for 6 days. Osteoclastogenesis was assessed by determining the number of tartrate-resistant acid phosphatase (TRAP)-stained multinuclear cells, while the secretion of factors involved in osteoclastogenesis was assessed using enzyme-linked immunosorbent assays. The effect of naringenin on bone resorption was investigated using an OsteoAssay human bone plate coupled with an immunoassay to evaluate the release of helical peptide 620-633 from the alpha1 chain of type I collagen. RESULTS: Naringenin was non-toxic at the highest concentration used (50 microg/ml). Naringenin (10, 25 and 50 microg/ml) significantly inhibited osteoclastogenesis (by 29 +/- 5, 57 +/- 8 and 96 +/- 1%, respectively). Naringenin also markedly inhibited the secretion of interleukin (IL)-1alpha (by 59%), IL-23 (by 87%) and monocyte chemoattractant protein-1 (by 58%). Lastly, naringenin (10, 25 and 50 microg/ml) significantly decreased the release of helical peptide 620-633, an indicator of bone resorption activity (by 44 +/- 0.5, 73 +/- 0.5 and 86 +/- 1%, respectively). CONCLUSIONS: Naringenin can inhibit human osteoclastogenesis and osteoclastic bone resorption. It thus holds promise as a therapeutic or preventive agent for bone-related 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 | 0.001 | 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) | 0.000 | 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