Exploring the Synthesis, Anti-Inflammatory and Anti-Tumor Potential of 4-Maleimidylphenyl-Hydrazide Derivatives
Bibliographic record
Abstract
The design of innovative compounds displaying anti-inflammatory activity in oncological context is a subject of great interest in drug development. It has been proved that a pro-inflammatory microenvironment which accelerates cancer growth and cellular differentiation is often present in malignant bladder tumor. In earlier work, we reported the synthesis of p-aminobenzoic acid derivatives that act as anti-inflammatory compounds able to inhibit the pro-inflammatory markers present in bladder cancer microenvironment. DAB-1 rapidly emerged as an effective lead candidate in this investigation, with its ability to shrink by 90% in 25 days the size of human bladder cancer tumors in an ectopic mouse model. This manuscript discloses the synthesis of 23 new hydrazide derivatives of DAB-1 and reports their in vitro and in vivo biological evaluation. It was discovered that most of the new compounds are essentially nontoxic against RAW 264.7 cells, as evaluated by an MTT assay. Anti-inflammatory activity of the new derivatives was investigated by evaluation of their impact on cellular nitric oxide production, measured by a Griess assay. Some compounds did significatively inhibit nitric oxide production much more effectively than the original DAB-1. Striking activity of 14, which is around four times more potent than DAB-1, promotes this derivative as new lead compound in this study. The study of these analogs reveals that a phenolic/anisole core is a key component to achieve high biological activity. Furthermore, mice models of acute inflammation and invasive BCa tumors were used to assess the in vivo impact of derivative 14, and it was found that this compound does reduce inflammation in these mice, possess similar anti-inflammatory activity but higher anti-tumoral activity compared to DAB-1 with no apparent signs of toxicity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".