In vivo Anti-Cancer Activity of N-halamines
Bibliographic record
Abstract
Purpose: N-halamines were known for their antimicrobial action due to the presence of halogen in their structure. In our search for new anti-cancer agents, we have evaluated the anti-cancer and anti-oxidant properties of some synthetic N-Halamines with high and low molecular weight in comparison with their non-halogenated forms. Urea epichlorohydrin copolymer (1), 4(1H, 3H-2, 6-dioxo-1, 3, 5-trizenyl)-O-iminomethylpolyethylene (3) and cynuric acid (5) in addition to their halogenated forms 2, 4 and 6 were selected for this study. Methodology: the toxicity for the synthesized compounds was determined. The anti-cancer and anti-oxidant activities were studied by evaluation the viability of tumor cells, life span prolongation, and estimation of antioxidants, and effects of these compounds on liver histology. Findings: Doses up to 2000 mg/kg indicated good safety in all investigated compounds. In Vivo antitumor activity results against Ehrlich ascites carcinoma (EAC) cells for the investigated compounds revealed that, the volume of ascites was significantly decreased in compounds 1, 2, 3, 4, 5 and 6 treated groups. EAC cell count was significantly reduced for similar groups, respectively, compared to the positive control group. Malonadildehyde, and nitric oxide showed a significant reduction in their levels in the treated groups, while catalase showed a significant elevation in its activity in the same groups compared to positive control group. Conclusion: Halogenated compounds showed good anti-oxidant behavior while compound 6 showed the best anti-tumor effect.
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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".