Synthesis and Characterization of Zn <sub>(1-x-y)</sub> Mn <sub>x</sub> Co <sub>y</sub> O NPs for Liver Cancer Treatment
Bibliographic record
Abstract
Introduction: In this study, pure and cobalt manganese-doped ZnO nanoparticles (Zn(1-x-y)MnxCoyO NPs) at varying concentrations were synthesized through sol-gel method, and zinc acetate dihydrate, manganese nitrate, cobalt acetate, and diethyl amine were used as precursors, with samples finally calcined at 700oC. Methods: The hexagonal wurtzite structure of pure and co-doped ZnO NPs was confirmed by X-ray diffraction (XRD). The computed grain sizes of pure and co-doped ZnO NPs, according to Scherrer's formula, were 32 nm, 32.5 nm, 36.3 nm, and 36.5 nm, respectively. SEM was used to observe the morphology of nanoparticles. FTIR spectroscopy was used to examine the chemical make-up and vibrational modes of pure and co-doped ZnO NPs. The bandgaps of pure and doped ZnO were examined using UV-Vis spectroscopy. Results: It was found that the optical bandgap of ZnO was lowered by 3.21 eV by manganese and cobalt doping. Elemental composition analysis was performed by using EDX analysis. Finally, anticancer activity of pure and co-doped ZnO NPs was assessed by employing MTT assay, which indicated that Zn0.8 Mn0.1 Co0.1O NPs showed significant anticancer results against liver cancer (HepG-2) cells as compared to ZnO, Zn0.98 Mn0.01Co0.01O and Zn0.90 Mn0.05 Co0.05O NPs. Moreover, Zn0.8 Mn0.1 Co0.1O NPs showed low toxicity and good biocompatibility comparable to doxorubicin (DOX). Conclusion: Comprehensive experimental findings have demonstrated an authentic way of obtaining feasible in vivo liver cancer therapy. conclusion: It is concluded that current form of comprehensive experimental finding will demonstrate the authentic way towards feasibility of liver cancer cure.
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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 | 0.000 |
| 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".