A Novel and Different Approach for the Synthesis of Quinoline Derivatives Starting Directly from Nitroarenes and Their Evaluation as Anti-Cancer Agents
Bibliographic record
Abstract
A series of new quinoline derivatives (6-phenyl-6H-chromeno, [4,3-b] quinoline) have been prepared by using 4-chloro-2-phenyl-2H-chromene-3-carbaldehyde and various substituted nitroarenes as starting materials in the presence of Tin (II) chloride dihydrate and ethanol. The conversion in this synthesis involves the following steps (i) reduction of nitroarenes to anilines, (ii) Coupling of the anilines, chromene aldehydes (iii) Cyclization of resulting species and (iv) dehydration of cyclic intermediates. Several new quinolones have been prepared. We screened eight compounds of this novel series (6a-r) in three different cancer cell lines (B16F10, MCF7 and A549). The screened compounds showed moderate anticancer activity on two of the studied cell lines with best IC50 values of compound 6i (6.10±1.23 µM) and 6m (8.21±2.31 µM) on MCF7 cells. The selected compounds 6i and 6m led to morphological changes after treatment on MCF7 cell line. Interestingly, detailed studies suggested that the compounds 6i and 6m induced apoptosis in MCF7 cells in an oxidative stress independent manner without causing necrosis. In addition, we found destabilization of mitochondrial membrane potential behind the observed anticancer activity. Our results clearly indicate the promising anticancer potential of this novel series. This method is operationally simple and works with a diverse range of substrates.
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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 | 0.001 |
| 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".