Dichloroacetyl Amides of 3,5-Bis(benzylidene)-4-piperidones Displaying Greater Toxicity to Neoplasms than to Non-Malignant Cells
Bibliographic record
Abstract
A series of 3,5-bis(benzylidene)-1-dichloroacetyl-4-piperidones 1a–l was evaluated against Ca9-22, HSC-2, HSC-3, and HSC-4 squamous cell carcinomas. Virtually all of the compounds displayed potent cytotoxicity, with 83% of the CC50 values being submicromolar and several CC50 values being in the double digit nanomolar range. The compounds were appreciably less toxic to human HGF, HPLF, and HPC non-malignant cells, which led to some noteworthy selectivity index (SI) figures. From these studies, 1d,g,k emerged as the lead molecules in terms of their potencies and SI values. A Quantitative Structure-Activity Relationship (QSAR) study revealed that cytotoxic potencies and potency–selectivity expression figures increased when the magnitude of the sigma values in the aryl rings was elevated. The modes of action of the representative cytotoxins in Ca9-22 cells were found to include G2/M arrest and stimulation of the cells to undergo mitosis and cause poly(ADP-ribose) polymerase (PARP) and procaspase 3 cleavage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".