Tumor-selective Cytotoxicity of a Novel Pentadiene Analogue on Human Leukemia/lymphoma Cells
Bibliographic record
Abstract
Background: A novel series of structurally divergent 1,5-diaryl-3-oxo- 1,4-pentadiene analogues 1-10 displayed marked cytotoxic potencies towards a number of human leukemia/lymphoma cells. Objective: To identify novel selective cytotoxic compounds that induce apoptosis. Methods: The Differential Nuclear Staining (DNS) screening protocol was utilized to measure the cytotoxicity of all experimental dienones on several cancerous cells. Additionally, the selective cytotoxicity index was calculated by comparing the dienone’s cytotoxicity between leukemia/lymphoma cells vs. non-cancerous cells. Furthermore, to discern whether a selected dienone induced cell death via apoptosis or necrosis on T-lymphocyte leukemia cells, diverse approaches were utilized to detect individual biochemical facets of apoptosis. Results: The dienones were tested for their anti-neoplastic efficiency on human leukemia/lymphomaderived cell lines. Special emphasis was applied on dienone 1, on the basis of its sub-micromolar cytotoxicity (CC50=0.43+0.02 μM) and high selective cytotoxicity index (11.1) exerted on T-leukemia cells. In general, dienone 1 showed the most potent cytotoxic properties as compared to other dienones and a related reference cytotoxin curcumin as well as the EF-24 curcumin analogue. Dienone 1 caused cell death by apoptosis in Jurkat cells as evidenced by inducing phosphatidylserine externalization, mitochondrial depolarization and caspase-3/7. These effects were mainly attributed to the induction of apoptotic pathways. Conclusion: The novel dienone 1 was found to exhibit potent anti-leukemia activity by inducing programmed cell death/apoptosis. Consequently, dionone 1 should be developed further to examine its potential efficacy to combat malignancies in a pre-clinical animal model. Keywords: Apoptosis, cancer, caspase 3, cytotoxins, curcumin analogue, leukemia, mitochondria.
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".