Does Ortho-Substitution Enhance Cytotoxic Potencies in a Series of 3,5-Bis(benzylidene)-4-piperidones?
Bibliographic record
Abstract
Background: A series of 3,5-benzylidene-4-piperidones, 1a–n, were prepared to evaluate the hypothesis that the placement of different groups in the ortho-location of the aryl rings led to compounds with greater cytotoxic potencies than structural analogs. Methods: The bioevaluation of 1a–n was undertaken using human Molt/4C8 and CEM cells as well as murine L1210 cells. Correlations were sought between the interplanar angles θA and θB and the cytotoxic potencies. A QSAR analysis was also undertaken. In order to evaluate whether these compounds demonstrated greater toxicity to neoplasms than non-malignant cells, 1a–n were evaluated against HSC-2, HSC-3, HSC-4 and HL60 neoplasms as well as non-malignant HGF, HPC and HPLF cells. Results: A positive correlation was noted between the interplanar angle θA of one of the aryl rings and the adjacent olefinic linkage with IC50 values in the Molt4/C8 screens. The QSAR analysis revealed a positive correlation between the Hansch pi (π) value of the aryl substituents and the IC50 values of the compounds towards the Molt4/C8 and CEM cells. The dienones in series 1 demonstrated higher tumor-selective toxicity towards HSC-2, HSC-3, HSC-4 and HL-60 neoplasms than HGF, HPC and HPLF cells. Conclusions: The bioevaluations revealed some support for greater cytotoxic potencies to be displayed by compounds having ortho-substituents.
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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".