Effect of<i>Allium cepa</i>L. on Lipopolysaccharide-Stimulated Osteoclast Precursor Cell Viability, Count, and Morphology Using 4′,6-Diamidino-2-phenylindole-Staining
Bibliographic record
Abstract
Allium cepa L. is known to possess numerous pharmacological properties. Our aim was to examine the in vitro effects of Allium cepa L. extract (AcE) on Porphyromonas gingivalis LPS and Escherichia coli LPS-stimulated osteoclast precursor cells to determine cell viability to other future cell-based assays. Osteoclast precursor cells (RAW 264.7) were stimulated by Pg LPS (1 μg/mL) and E. coli LPS (1 μg/mL) in the presence or absence of different concentrations of AcE (10-1000 μg/mL) for 5 days at 37°C/5% CO2. Resazurin reduction and total protein content assays were used to detect cell viability. AcE did not affect cell viability. Resazurin reduction assay showed that AcE, at up to 1000 μg/mL, did not significantly affect cell viability and cellular protein levels. Additionally a caspase 3/7 luminescence assay was used to disclose apoptosis and there was no difference in apoptotic activity between tested groups and control group. Fluorescence images stained by DAPI showed no alteration on the morphology and cell counts of LPS-stimulated osteoclast precursor cells with the use of AcE in all tested concentrations when compared to control. These findings suggest that Allium cepa L. extract could be used for in vitro studies on Porphyromonas gingivalis LPS and Escherichia coli LPS-stimulated osteoclast precursor cells.
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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 | 0.000 | 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 | 0.001 |
| 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".