Evaluation of the Effect of Five Colombian Propolis Extracts on the Expression of Genes Associated with Cell Cycle and Inflammation in a Canine Osteosarcoma Cell Line
Bibliographic record
Abstract
Introduction: Propolis has anti-inflammatory, antitumor, antibacterial and immunomodulatory properties, which is why it is suggested that it could be used as an alternative or complementary drug therapy in the treatment of various pathologies such as cancer, diseases chronic-degenerative and infectious.Materials and Methods: In this study, canine bone fibroblasts were used as control cells, and the canine Osteosarcoma cell line (OSCA-8) was acquired to evaluate the effects of ethanol extracts of propolis from five Colombian regions on these cells.The cytotoxic effect was evaluated by examining changes in cell viability and proliferation.Furthermore, the expression of some relevant and characteristic genes related to the tumor phenotype, related to the proinflammatory process and cell cycle, was assessed.Results: Thus, the evaluation of the relative expression of some genes associated with the cell cycle and inflammation could improve the understanding of the cytotoxic effect of propolis extracts on OSCA-8 cell lines.Conclusion: The first time in Colombia, the biological activity of ethanol extracts of propolis was evaluated regarding the inflammation and cell cycle pathways.After 48 hr, the Colombian EEP had an effect on the increase in both OSCA-8 cells and fibroblasts.
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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".