Potential use of alexidine dihydrochloride as an apoptosis-promoting anticancer agent
Bibliographic record
Abstract
Despite advances in surgery, radiation, and chemotherapy, novel therapeutics are needed for head and neck cancer treatment. The objective of this current study was to evaluate alexidine dihydrochloride as a novel compound lead for head and neck cancers. Using a tetrazolium-based assay, the dose required to reduce cell viability by 50% (ED50) was found to be approximately 1.8 micromol/L in FaDu (human hypopharyngeal squamous cancer) and approximately 2.6 micromol/L in C666-1 (human undifferentiated nasopharyngeal cancer) cells. In contrast, the ED50 values were much higher in untransformed cells, specifically at approximately 8.8 micromol/L in GM05757 (primary normal human fibroblast), approximately 8.9 micromol/L in HNEpC (primary normal human nasal epithelial), and approximately 19.6 micromol/L in NIH/3T3 (mouse embryonic fibroblast) cells. Alexidine dihydrochloride did not interfere with the activities of cisplatin, 5-fluorouracil, or radiation, and interacted in a less-than-additive manner. DNA content analyses and Hoechst 33342 staining revealed that this compound induced apoptosis. Alexidine dihydrochloride-induced mitochondrial damage was visualized using transmission electron microscopy. Mitochondrial membrane potential (DeltaPsiM) depolarization was detectable after only 3 hours of treatment, and was followed by cytosolic Ca2+ increase along with loss of membrane integrity/cell death. Caspase-2 and caspase-9 activities were detectable at 12 hours, caspase-8 at 24 hours, and caspase-3 at 48 hours. FaDu cell clonogenic survival was reduced to < 5% with 1 micromol/L alexidine dihydrochloride, and, correspondingly, this compound decreased the in vivo tumor-forming potential of FaDu cells. Thus, we have identified alexidine dihydrochloride as the first bisbiguanide compound with anticancer specificity.
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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) | 0.000 | 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 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".