Pollution, Toxicity and Carcinogenicity of Organic Dyes and their Catalytic Bio-Remediation.

Water pollution due to waste effluents of the textile industry is seriously causing various health problems in humans. Water pollution with pathogenic bacteria, especially Escherichia coli (E. coli) and other microbes is due to the mixing of fecal material with drinking water, industrial and domestic sewage, pasture and agricultural runoff. Among the chemical pollutants, organic dyes due to toxic nature, are one of the major contaminants of industrial wastewater. Adequate sanitation services and drinking quality water would eliminate 200 million cases of diarrhea, which results in 2.1 million less deaths caused by diarrheal disease due to E. coli each year. Nanotechnology is an excellent platform as compared to conventional treatment methods of water treatment and remediation from microorganisms and organic dyes. In the current study, toxicity and carcinogenicity of the organic dyes have been studied as well as the remediation/inactivation of dyes and microorganism has been discussed. Remediation by biological, physical and chemical methods has been reviewed critically. A physical process like adsorption is cost-effective, but can't degrade dyes. Biological methods were considered to be ecofriendly and cost-effective. Microbiological degradation of dyes is cost-effective, eco-friendly and alternative to the chemical reduction. Besides, certain enzymes especially horseradish peroxidase are used as versatile catalysts in a number of industrial processes. Moreover, this document has been prepared by gathering recent research works related to the dyes and microbial pollution elimination from water sources by using heterogeneous photocatalysts, metal nanoparticles catalysts, metal oxides and enzymes.

Overcoming challenges for amplified expression of recombinant proteins using Escherichia coli.

A thorough characterisation of the genetics, physiology and metabolism of Escherichia coli has led to the availability of a large number of strains and vectors suitable for recombinant protein expression. Despite the relative ease in using E. coli for achieving amplified expression of many recombinant proteins, for some proteins this can be a frustrating and time-consuming process leading to very low expression or no expression at all. This is especially true for membrane proteins, which introduce additional challenges. A number of factors can be considered and optimised for achieving required levels of amplified expression of recombinant proteins in E. coli that are broadly classified as host strain, expression vector and growth conditions. In this paper we summarise these factors and consolidate the common challenges encountered and approaches to overcome them, focusing in particular on cases where there is low amplified expression or no expression at all of the desired recombinant protein, due to various reasons.

Polymer Nanocomposite Membranes for Antifouling Nanofiltration.

Fouling refers to the unwanted and undesirable attachment of biological macromolecules, inorganic, organic matter, and microorganisms on water contact surfaces. Fouling reduces the performance of devices involving these submerged surfaces and is considered the bottle-neck issue for various applications in the biomedical industry, food processing, and water treatment, especially in reverse osmosis (RO) desalination. Investigations have proven that nanocomposite membranes can exhibit enhanced antifouling performances and can be used for longer life times. The nanocomposite means addition of nanomaterials to main matrix at low loadings, exhibiting better properties compared to virgin matrix. In this review, a summarized description about related methods and their mechanisms for the fabrication of nanocomposite membranes with antifouling properties has been documented. Around 87 manuscripts including 10 patents were used to demonstrate the antifouling applications of of various nanocomposite membranes.

Withanolides: Biologically Active Constituents in the Treatment of Alzheimer's Disease.

The use of natural products in drug discovery and development have an important history. Several therapeutic agents have been investigated during the biological screenings of natural compounds. It is well documented that plants are possibly the core of novel substances that led to the discovery of new, novel, and effective therapeutic agents. Therefore, in the last few decades, scientists were thoroughly attempting for the search of benevolent drugs to protect mankind from various diseases and discomforts. The diverse chemical structures of natural products are the key element of their success in modern drug discovery. Cholinesterase enzyme inhibitors (ChEI) are chemicals which inhibit the splitting of cholinesterase enzymes (acetylcholinesterase and butyrylcholinesterase). Acetyl cholinesterase (AChE) and butyrylcholinesterase (BChE) are two types of cholinesterase enzymes that have been identified in vertebrates that are responsible for Alzheimer's disease and related dementia. Withanolides are affective plant secondary metabolites which inhibit acetylcholinesterase and butyrylcholinesterase enzyme and thus possibly will be the future drug for Alzheimer's disease. By viewing the importance of natural products in drug discovery and development, we present here, the importance of withanolides in the treatment of Alzheimer's disease. In this article, we also describe the classification and structural characterization of withanolides. This review comprises of 114 compounds.

Bond-based 2D quadratic fingerprints in QSAR studies: virtual and in vitro tyrosinase inhibitory activity elucidation.

In this report, we show the results of quantitative structure-activity relationship (QSAR) studies of tyrosinase inhibitory activity, by using the bond-based quadratic indices as molecular descriptors (MDs) and linear discriminant analysis (LDA), to generate discriminant functions to predict the anti-tyrosinase activity. The best two models [Eqs (6) and (12)] out of the total 12 QSAR models developed here show accuracies of 93.51% and 91.21%, as well as high Matthews correlation coefficients (C) of 0.86 and 0.82, respectively, in the training set. The validation external series depicts values of 90.00% and 89.44% for these best two equations (6) and (12), respectively. Afterwards, a second external prediction data are used to perform a virtual screening of compounds reported in the literature as active (tyrosinase inhibitors). In a final step, a series of lignans is analysed using the in silico-developed models, and in vitro corroboration of the activity is carried out. An issue of great importance to remark here is that all compounds present greater inhibition values than Kojic acid (standard tyrosinase inhibitor: IC50 = 16.67 µm). The current obtained results could be used as a framework to increase the speed, in the biosilico discovery of leads for the treatment of skin disorders.