1-[4-(2-Dimethylaminoethoxy)phenylcarbonyl]-3,5-Bis(3,4,5-Trimethoxybenzylidene)-4-Piperidone Hydrochloride and Related Compounds: PotentCytotoxins Demonstrate Greater Toxicity to Neoplasms than Non-Malignant Cells
Bibliographic record
Abstract
BACKGROUND: The incidence of cancer has been increasing worldwide. Unfortunately, the drugs used in cancer chemotherapy are toxic to both neoplasms and normal tissues, while many available medications have low potencies. Conjugated α,β-unsaturated ketones differ structurally from contemporary anticancer medications , some of which have noteworthy antineoplastic properties. OBJECTIVES: This study aimed to design and synthesize highly potent cytotoxins with far greater toxicity to neoplasms than to non-malignant cells. METHODS: A series of N-acyl-3,5-bis(benzylidene)-4-piperidone hydrochlorides 4a-n were prepared and evaluated against Ca9-22, HSC-2, HSC-3, and HSC-4 squamous cell carcinomas as well as against HGF, HPLF, and HPC non-malignant cells. QSAR and western blot analyses were performed. RESULTS: values than those of melphalan, 5-fluorouracil, and methotrexate, while some compounds are equitoxic with doxorubicin. The compounds are far less toxic to the non-malignant cells, giving rise to substantial selectivity index (SI) figures. A QSAR study revealed that both potency and the SI data were controlled to a large extent by the electronic properties of the substituents in the arylidene aryl rings. Two representative compounds, 4f and 4g, caused apoptosis in HSC-2 cells. CONCLUSION: value of 0.04 μM towards four malignant cell lines and a selectivity index of 46.3 is clearly a lead molecule that should be further evaluated.
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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".