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Inside the biological milieu, nanoparticles with photocatalytic activity have potential to trigger cell death non‐specifically due to production of reactive oxygen species (ROS) upon reacting with biological entities. Silver nanoparticle (AgNP) possessing narrow band gap energy can exhibit high light absorption property and significant photocatalytic activity. This study intends to explore the effects of ROS generated due to photocatalytic activity of AgNP on antimicrobial and cytotoxic propensities. To this end, AgNP was synthesized using the principle of green chemistry from the peel extract of Punica granatum L., and was characterized using UV–Vis spectroscope, transmission electron microscope and x‐ray diffraction, and so forth. The antimicrobial activity of AgNP against studied bacteria indicated that, ROS generated at AgNP interface develop stress on bacterial membrane leading to bacterial cell death, whereas Alamar Blue dye reduction assay indicated that increased cytotoxic activity with increasing concentrations of AgNP. The γH2AX activity assay revealed that increasing the concentrations of AgNP increased DNA damaging activity. The results altogether demonstrated that both antimicrobial and cytotoxic propensities are triggered primarily due interfacial ROS generation by photocatalytic AgNP, which caused membrane deformation in bacteria and DNA damage in HT1080 cells resulting in cell death.

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Magnolia champaca (L.) Baill. ex Pierre of family Magnoliaceae, is a perennial tree with aromatic, ethnobotanical, and medicinal uses. The M. champaca leaf is reported to have a myriad of therapeutic activities, however, there are limited reports available on the chemical composition of the leaf essential oil of M. champaca. The present study explored the variation in the yield and chemical composition of leaf essential oil isolated from 52 accessions of M. champaca. Through hydrodistillation, essential oil yield was obtained, varied in the range of 0.06 ± 0.003% and 0.31 ± 0.015% (v/w) on a fresh weight basis. GC-MS analysis identified a total of 65 phytoconstituents accounting for 90.23 to 98.90% of the total oil. Sesquiterpene hydrocarbons (52.83 to 65.63%) constituted the major fraction followed by sesquiterpene alcohols (14.71 to 22.45%). The essential oils were found to be rich in β-elemene (6.64 to 38.80%), γ-muurolene (4.63 to 22.50%), and β-caryophyllene (1.10 to 20.74%). Chemometrics analyses such as PCA, PLS-DA, sPLS-DA, and cluster analyses such as hierarchical clustering, i.e., dendrogram and partitional clustering, i.e., K-means classified the essential oils of M. champaca populations into three different chemotypes: chemotype I (β-elemene), chemotype II (γ-muurolene) and chemotype III (β-caryophyllene). The chemical polymorphism analyzed in the studied populations would facilitate the selection of chemotypes with specific compounds. The chemotypes identified in the M. champaca populations could be developed as promising bio-resources for conservation and pharmaceutical application and further improvement of the taxa.

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Bacopa monnieri (L.) Wettst is a very high-value medicinal plant that is commonly used for improving cognitive functions. However, the availability of very limited information on the drying method of B. monnieri has prompted to optimize a suitable drying method. The present study therefore aimed to evaluate the influence of the following six drying treatments on the quality of B. monnieri sample: microwave drying at 300 W and 600 W, hot air-drying at 50°C and 70°C, solar drying, and freeze-drying (FD). The quality attributes of the dried samples were comparatively analyzed in terms of color, total color difference, moisture content, water activity ( a w ), antioxidant activity, and bacoside A and bacopaside I content. The results of this study showed significant differences ( P < 0.05) among the different drying methods in International Commission on Illumination (CIE) parameters, namely lightness index ( L *), red-green index ( a *), and yellow-blue index ( b *), Δ E and a values. Among the samples dried with the six drying methods, freeze-dried B. monnieri samples had an attractive color with the lowest total color difference value (11.415%), a w value (0.15%), and maximum bacoside A (3.389%) and bacopaside I (0.620%) content. Moreover, Fourier transform infrared spectroscopy (FT-IR) analysis showed no major difference in the functional groups in B. monnieri samples processed by the different drying methods. Considering the retention of quality after drying, FD was found to be very effective for future large-scale production of good quality dried B. monnieri products.

Andrographolide, the principal secondary metabolite of Andrographis paniculata, displays a wide spectrum of medicinal activities. The content of andrographolide varies significantly in the species collected from different geographical regions. Therefore, this study aims at investigating the role of different abiotic factors and selecting suitable sites for the cultivation of A. paniculata with high andrographolide content using a multilayer perceptron artificial neural network (MLP-ANN) approach. A total of 150 accessions of A. paniculata collected from different regions of Odisha and West Bengal in eastern India showed a variation in andrographolide content in the range of 0.28–5.45% on a dry weight basis. The MLP-ANN was trained using climatic factors and soil nutrients as the input layer and the andrographolide content as the output layer. The best topological ANN architecture, consisting of 14 input neurons, 12 hidden neurons, and 1 output neuron, could predict the andrographolide content with 90% accuracy. The developed ANN model showed good predictive performance with a correlation coefficient (R2) of 0.9716 and a root-mean-square error (RMSE) of 0.18. The global sensitivity analysis revealed nitrogen followed by phosphorus and potassium as the predominant input variables influencing the andrographolide content. The andrographolide content could be increased from 3.38% to 4.90% by optimizing these sensitive factors. The result showed that the ANN approach is reliable for the prediction of suitable sites for the optimum andrographolide yield in A. paniculata.