Investigation of the survival viability of cervical cancer cells (HeLa) under visible light induced photo-catalysis with facile synthesized WO3/ZnO nanocomposite
Bibliographic record
Abstract
The photo catalytic degradation, a proven chemical process used for the decontamination of organic/inorganic pollutants and microorganisms in water was implemented. In this work for the selective killing of cervical cancer cells (HeLa cells) by using nano-composite of ZnO (Zinc Oxcide), WO3 (tungsten oxide) and (n-WO3/ZnO) as a photo-catalyst under the irradiation of visible light. All the three nanostructured semiconducting materials (WO3, ZnO and n-WO3/ZnO) were synthesized by facile chemical precipitation method and their morphological and optical characterization studies were carried out to elucidate the observed enhancement in the photo-catalytic killing of HeLa cancer cells with n-WO3/ZnO as a photo-catalyst. After 60 min of photo-catalytic reaction with n-WO3/ZnO as a photo-catalyst, a survival viability of HeLa cancer cells as low as 15% was achieved (nearly 85% of killing), as compared to 65% of HeLa cancer cell survival viability (nearly 35% of killing) with individual use of WO3 and ZnO as photo-catalysts under the same irradiation and experimental conditions. This improved photo-catalytic killing of HeLa cancer cells using n-WO3/ZnO in the visible spectral region is attributed to the enhanced visible light absorption and reduced electron hole recombination, characteristically brought about in the n-WO3/ZnO composite material. As photo-catalytic killing of the cancer cells can be selective, localized and reasonably efficient, in principle, this method can be considered as a non-invasive targeted treatment option for killing any type of cancer cells. HeLa cells, in particular are the cervical cancer cell and the tumors in and around cervix, containing HeLa cells can be non-surgically accessed and photo-catalytically treated with appropriate photo-catalyst and light source.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".