Photocatalytic activity of biosynthesized silver nanoparticle fosters oxidative stress at nanoparticle interface resulting in antimicrobial and cytotoxic activities.

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.

Volatile Profiling of Magnolia champaca Accessions by Gas Chromatography Mass Spectrometry Coupled with Chemometrics.

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 ß-elemene (6.64 to 38.80%), γ-muurolene (4.63 to 22.50%), and ß-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 (ß-elemene), chemotype II (γ-muurolene) and chemotype III (ß-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.

Application of a Multilayer Perceptron Artificial Neural Network for the Prediction and Optimization of the Andrographolide Content in Andrographis paniculata.

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.

Elucidating the anti-cancer potential of Cinnamomum tamala essential oil against non-small cell lung cancer: A multifaceted approach involving GC-MS profiling, network pharmacology, and molecular dynamics simulations.

Cinnamomum tamala (Buch.-Ham.) T.Nees & Eberm., or Indian Bay Leaf, is a well-known traditional ayurvedic medicine used to treat various ailments. However, the molecular mechanism of action of Cinnamomum tamala essential oil (CTEO) against non-small cell lung cancer (NSCLC) remains elusive. The present study aims to decipher the molecular targets and mechanism of CTEO in treating NSCLC. GC-MS analysis detected 49 constituents; 44 successfully passed the drug-likeness screening and were identified as active compounds. A total of 3961 CTEO targets and 4588 anti-NSCLC-related targets were acquired. JUN, P53, IL6, MAPK3, HIF1A, and CASP3 were determined as hub genes, while cinnamaldehyde, ethyl cinnamate and acetophenone were identified as core compounds. Enrichment analysis revealed that targets were mainly involved in apoptosis, TNF, IL17, pathways in cancer and MAPK signalling pathways. mRNA expression, pathological stage, survival analysis, immune infiltrate correlation and genetic alteration analysis of the core hub genes were carried out. Kaplan-Meier overall survival (OS) curve revealed that HIF1A and CASP3 are linked to worse overall survival in Lung Adenocarcinoma (LUAD) cancer patients compared to normal patients. Ethyl cinnamate and cinnamaldehyde showed high binding energy with the MAPK3 and formed stable interactions with MAPK3 during the molecular dynamic simulations for 100 ns. The MM/PBSA analysis revealed that van der Waals (VdW) contributions predominantly account for a significant portion of the compound interactions within the binding pocket of MAPK3. Density functional theory analysis showed cinnamaldehyde as the most reactive and least stable compound. CTEO exhibited selective cytotoxicity by inhibiting the proliferation of A549 cells while sparing normal HEK293 cells. CTEO triggered apoptosis by arresting the cell cycle, increasing ROS accumulation, causing mitochondrial depolarisation, and elevating caspase-3, caspase-8 and caspase-9 levels in A549 cells. The above study provides insights into the pharmacological mechanisms of action of Cinnamomum tamala essential oil against non-small cell lung cancer treatment, suggesting its potential as an adjuvant therapy.

Chemical fingerprinting and multicomponent quantitative analysis for quality control of Cinnamomum tamala collected from Western Himalaya by HPLC-DAD.

Cinnamomum tamala, commonly known as "Indian bay leaf" or "Tejpat", is an economically important plant widely used in medicine, food and cosmetic industries. Growing demand for its leaf and bark in the herbal trade and non-availability of quality materials lead to large-scale species admixture and adulteration in the global market. The present study aims at developing a validated HPLC-DAD (High-performance liquid chromatography coupled with diode array detection) method and multiple markers-based chemical fingerprints for quality evaluation of C. tamala leaf extracts. Five bioactive compounds, viz., coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate, were identified and quantified in 28 samples collected from the western Himalayan region of India. The chromatographic separation was achieved on Shimadzu Shimpak C18 column (dimension 250 × 4.6 mm, pore size 5 µm) with a gradient elution of mobile phase using acetonitrile and 0.1 percent phosphate buffer and the chromatograms were obtained at a wavelength of 265 nm. The method validation was done by analyzing the linearity, LOD, LOQ, precision, stability, repeatability and recovery rates of standard compounds for quantitative analysis. The values of coefficient of correlation (R2) were found to be close to 1 for linearity and similarity analysis; and standard deviation was less than 3 percent in case of precision, stability, repeatability and recovery rates. The content of target compounds such as coumarin, cinnamyl alcohol, cinnamic acid, cinnamaldehyde and cinnamyl acetate varied in the range of 0-1.09, 0-0.05, 0.07-0.51, 0.39-1.27 and 0-0.27 percent, respectively. In the chemical fingerprint of C. tamala leaves, a total of 13 peaks were assigned as common peaks. The results of the study indicated that the HPLC method now developed combining chemical fingerprint with quantification of analytes could serve as a useful tool for quality evaluation of herbal raw materials of C. tamala and a valuable reference for further study.

Effect of different drying treatments on the physicochemical, functional, and antioxidant properties of Bacopa monnieri.

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*), ΔE 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.