Meta-Analysis of Cytotoxicity Studies Using Machine Learning Models on Physical Properties of Plant Extract-Derived Silver Nanoparticles.

Silver nanoparticles (Ag-NPs) demonstrate unique properties and their use is exponentially increasing in various applications. The potential impact of Ag-NPs on human health is debatable in terms of toxicity. The present study deals with MTT(3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl-tetrazolium-bromide) assay on Ag-NPs. We measured the cell activity resulting from molecules' mitochondrial cleavage through a spectrophotometer. The machine learning models Decision Tree (DT) and Random Forest (RF) were utilized to comprehend the relationship between the physical parameters of NPs and their cytotoxicity. The input features used for the machine learning were reducing agent, types of cell lines, exposure time, particle size, hydrodynamic diameter, zeta potential, wavelength, concentration, and cell viability. These parameters were extracted from the literature, segregated, and developed into a dataset in terms of cell viability and concentration of NPs. DT helped in classifying the parameters by applying threshold conditions. The same conditions were applied to RF to extort the predictions. K-means clustering was used on the dataset for comparison. The performance of the models was evaluated through regression metrics, viz. root mean square error (RMSE) and R2. The obtained high value of R2 and low value of RMSE denote an accurate prediction that could best fit the dataset. DT performed better than RF in predicting the toxicity parameter. We suggest using algorithms for optimizing and designing the synthesis of Ag-NPs in extended applications such as drug delivery and cancer treatments.

An In Vitro and In Vivo Study of the Efficacy and Toxicity of Plant-Extract-Derived Silver Nanoparticles.

Silver nanoparticles (AgNPs) display unique plasmonic and antimicrobial properties, enabling them to be helpful in various industrial and consumer products. However, previous studies showed that the commercially acquired silver nanoparticles exhibit toxicity even in small doses. Hence, it was imperative to determine suitable synthesis techniques that are the most economical and least toxic to the environment and biological entities. Silver nanoparticles were synthesized using plant extracts and their physico-chemical properties were studied. A time-dependent in vitro study using HEK-293 cells and a dose-dependent in vivo study using a Drosophila model helped us to determine the correct synthesis routes. Through biological analyses, we found that silver nanoparticles' cytotoxicity and wound-healing capacity depended on size, shape, and colloidal stability. Interestingly, we observed that out of all the synthesized AgNPs, the ones derived from the turmeric extract displayed excellent wound-healing capacity in the in vitro study. Furthermore, the same NPs exhibited the least toxic effects in an in vivo study of ingestion of these NPs enriched food in Drosophila, which showed no climbing disability in flies, even at a very high dose (250 mg/L) for 10 days. We propose that stabilizing agents played a superior role in establishing the bio-interaction of nanoparticles. Our study reported here verified that turmeric-extract-derived AgNPs displayed biocompatibility while exhibiting the least cytotoxicity.