Residents of Chattogram city areas in Bangladesh use drinking water from three sources, namely CWASA (Chattogram Water supply and Sewerage Authority), groundwater (tube-well), and commercial jar. In this study, we examined the quality of drinking water from these sources following an analytical and residents' perception. Water samples (both untreated and treated) from above three sources were collected from six locations across Chattogram city, and pH, total dissolved solids (TDS), total suspended solids (TSS), bicarbonate, electrical conductivity (EC), salinity, and microbial load were studied following the state-of-art testing methods. A total of 149 respondents were interviewed to understand their perception on the physical properties of water. The pH value of water from all sources and locations and irrespective of treatments, varied from 6.54 to 7.02. TDS of tube-well water in two locations exceeded the standard limit (1000 mg/l). In most locations, TSS varied from 40 to 1888 mg/l (treated and untreated) against the standard value of 10 mg/l, while bicarbonate of CWASA and tube-well water in most locations was also higher than the permissible amount (500 mg/l). Except for jar water, EC of CWASA and tube-well water (treated and untreated) in most locations were higher than the standard value (500 μS) and a similar situation was observed for salinity content. The microbial load was found beyond the permissible limit (0 CFU/ml) for all sources and locations. These parameters of water quality have also been reflected in residents' perceptions of drinking water. Respondents reported an unpleasant odour (56%), the presence of suspended particles (17%), and so CWASA water is not good for drinking (76%). Authorities (CWASA) need to take action toward a safe drinking water supply for residents.
Chitosan is a promising biopolymer for drug delivery systems. Because of its beneficial properties, chitosan is widely used in biomedical and pharmaceutical fields. In this review, we summarize the physicochemical and drug delivery properties of chitosan, selected studies on utilization of chitosan and chitosan-based nanoparticle composites in various drug delivery systems, and selected studies on the application of chitosan films in both drug delivery and wound healing. Chitosan is considered the most important polysaccharide for various drug delivery purposes because of its cationic character and primary amino groups, which are responsible for its many properties such as mucoadhesion, controlled drug release, transfection, in situ gelation, and efflux pump inhibitory properties and permeation enhancement. This review can enhance our understanding of drug delivery systems particularly in cases where chitosan drug-loaded nanoparticles are applied.
Phytosterols provide important health benefits: in particular, the lowering of cholesterol. From environmental and commercial points of view, the most appropriate technique has been searched for extracting phytosterols from plant matrices. As a green technology, supercritical fluid extraction (SFE) using carbon dioxide (CO2) is widely used to extract bioactive compounds from different plant matrices. Several studies have been performed to extract phytosterols using supercritical CO2 (SC-CO2) and this technology has clearly offered potential advantages over conventional extraction methods. However, the efficiency of SFE technology fully relies on the processing parameters, chemistry of interest compounds, nature of the plant matrices and expertise of handling. This review covers SFE technology with particular reference to phytosterol extraction using SC-CO2. Moreover, the chemistry of phytosterols, properties of supercritical fluids (SFs) and the applied experimental designs have been discussed for better understanding of phytosterol solubility in SC-CO2.
Mesoporous carbon is a promising material having multiple applications. It can act as a catalytic support and can be used in energy storage devices. Moreover, mesoporous carbon controls body's oral drug delivery system and adsorb poisonous metal from water and various other molecules from an aqueous solution. The accuracy and improved activity of the carbon materials depend on some parameters. The recent breakthrough in the synthesis of mesoporous carbon, with high surface area, large pore-volume, and good thermostability, improves its activity manifold in performing functions. Considering the promising application of mesoporous carbon, it should be broadly illustrated in the literature. This review summarizes the potential application of mesoporous carbon in many scientific disciplines. Moreover, the outlook for further improvement of mesoporous carbon has been demonstrated in detail. Hopefully, it would act as a reference guidebook for researchers about the putative application of mesoporous carbon in multidimensional fields.
We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.
Child and adolescent mental health (CAMH) are a global priority. Different countries across the globe face unique challenges in CAMH services that are specific to them. However, there are multiple issues that are also similar across countries. These issues have been presented in this commentary from the lens of early career CAMH professionals who are alumni of the Donald J Cohen Fellowship program of the IACAPAP. We also present recommendations that can be implemented locally, namely, how promoting mental health and development of children and adolescents can result in better awareness and interventions, the need to improve quality of care and access to care, use of technology to advance research and practices in CAMH, and how investing in research can secure and support CAMH professionals and benefit children and adolescents across the globe. As we continue to navigate significant uncertainty due to dynamic circumstances globally, bolstering collaborations by "bringing change locally, while thinking globally" are invaluable to advancing global CAMH research, clinical service provision, and advancement of the field.
In the modern world, wheat, a vital global cereal and the second most consumed, is vulnerable to climate change impacts. These include erratic rainfall and extreme temperatures, endangering global food security. Research on hydrogen-rich water (HRW) has gained momentum in plant and agricultural sciences due to its diverse functions. This study examined the effects of different HRW treatment durations on wheat, revealing that the 4-h treatment had the highest germination rate, enhancing potential, vigor, and germination indexes. This treatment also boosted relative water content, root and shoot weight, and average lengths. Moreover, the 4-h HRW treatment resulted in the highest chlorophyll and soluble protein concentrations in seeds while reducing cell death. The 4-h and 5-h HRW treatments significantly increased H2O2 levels, with the highest NO detected in both root and shoot after 4-h HRW exposure. Additionally, HRW-treated seeds exhibited increased Zn and Fe concentrations, along with antioxidant enzyme activities (CAT, SOD, APX) in roots and shoots. These findings suggest that HRW treatment could enhance wheat seed germination, growth, and nutrient absorption, thereby increasing agricultural productivity. Molecular analysis indicated significant upregulation of the Dreb1 gene with a 4-h HRW treatment. Thus, it shows promise in addressing climate change effects on wheat production. Therefore, HRW treatment could be a hopeful strategy for enhancing wheat plant drought tolerance, requiring further investigation (field experiments) to validate its impact on plant growth and drought stress mitigation.