In-situ observation and transport modelling of arsenic in Gangetic plain, India

The focus of this study is to investigate the arsenic movement and impacts on the residual concentrations on groundwater pollution load. The Gangetic plain area in the Ballia, Uttar Pradesh is selected as study area, which is also reported to extreme arsenic pollution in soil-water system. A modelling approach is developed to assess the arsenic flux in partially saturated zone using data of soil texture, soil hydraulic properties and stratigraphy. Soil type, slope, and land-use cover is considered for estimating the transient flux at the top boundary from daily precipitation and evapotranspiration data of the study area. Solute transport in the subsurface is predicted by the mass transfer equation, which is derived by integrating Darcy\u27s law with the equation of mass balance. The arsenic profiles of varying hydrogeological conditions associated with different locations in the study area are presented as breakthrough curves. The results shows that the arsenic transport is dominated by the advective flux and strongly depends on the soilmoisture flow conditions. Which may increases the arsenic load to underlaying groundwater resources. The simulated results suggest that mobility plays a vital role arsenic transport as well as on adsorbed arsenic concentration in subsurface. Likewise, the adsorption isotherms show that the high peak curve for Bairai and low at Sikarderpur. A higher pollution risk is observed in the Belthara Road, whereas a lower vulnerability is computed in the north and northeast regions. This study can help in strategising sustainable groundwater management and protection planning of identified regions of India

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches

An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has infected approximately 220 million people worldwide with a death toll of 4.5 million as of September 2021. This study is focused on finding potential vaccine candidates and designing an in-silico subunit multi-epitope vaccine candidates using a unique computational pipeline, integrating reverse vaccinology, molecular docking and simulation methods. A protein named spike protein of SARS-CoV-2 with the GenBank ID QHD43416.1 was shortlisted as a potential vaccine candidate and was examined for presence of B-cell and T-cell epitopes. We also investigated antigenicity and interaction with distinct polymorphic alleles of the epitopes. High ranking epitopes such as DLCFTNVY (B cell epitope), KIADYNKL (MHC Class-I) and VKNKCVNFN (MHC class-II) were shortlisted for subsequent analysis. Digestion analysis verified the safety and stability of the shortlisted peptides. Docking study reported a strong binding of proposed peptides with HLA-A*02 and HLA-B7 alleles. We used standard methods to construct vaccine model and this construct was evaluated further for its antigenicity, physicochemical properties, 2D and 3D structure prediction and validation. Further, molecular docking followed by molecular dynamics simulation was performed to evaluate the binding affinity and stability of TLR-4 and vaccine complex. Finally, the vaccine construct was reverse transcribed and adapted for E. coli strain K 12 prior to the insertion within the pET-28-a (+) vector for determining translational and microbial expression followed by conservancy analysis. Also, six multi-epitope subunit vaccines were constructed using different strategies containing immunogenic epitopes, appropriate adjuvants and linker sequences. We propose that our vaccine constructs can be used for downstream investigations using in-vitro and in-vivo studies to design effective and safe vaccine against different strains of COVID-19

In-situ observation and transport modelling of arsenic in Gangetic plain, India

The focus of this study is to investigate the arsenic movement and impacts on the residual concentrations on groundwater pollution load. The Gangetic plain area in the Ballia, Uttar Pradesh is selected as study area, which is also reported to extreme arsenic pollution in soil-water system. A modelling approach is developed to assess the arsenic flux in partially saturated zone using data of soil texture, soil hydraulic properties and stratigraphy. Soil type, slope, and land-use cover is considered for estimating the transient flux at the top boundary from daily precipitation and evapotranspiration data of the study area. Solute transport in the subsurface is predicted by the mass transfer equation, which is derived by integrating Darcy\u27s law with the equation of mass balance. The arsenic profiles of varying hydrogeological conditions associated with different locations in the study area are presented as breakthrough curves. The results shows that the arsenic transport is dominated by the advective flux and strongly depends on the soilmoisture flow conditions. Which may increases the arsenic load to underlaying groundwater resources. The simulated results suggest that mobility plays a vital role arsenic transport as well as on adsorbed arsenic concentration in subsurface. Likewise, the adsorption isotherms show that the high peak curve for Bairai and low at Sikarderpur. A higher pollution risk is observed in the Belthara Road, whereas a lower vulnerability is computed in the north and northeast regions. This study can help in strategising sustainable groundwater management and protection planning of identified regions of India

In-situ observation and transport modelling of arsenic in Gangetic plain, India

The focus of this study is to investigate the arsenic movement and impacts on the residual concentrations on groundwater pollution load. The Gangetic plain area in the Ballia, Uttar Pradesh is selected as study area, which is also reported to extreme arsenic pollution in soil-water system. A modelling approach is developed to assess the arsenic flux in partially saturated zone using data of soil texture, soil hydraulic properties and stratigraphy. Soil type, slope, and land-use cover is considered for estimating the transient flux at the top boundary from daily precipitation and evapotranspiration data of the study area. Solute transport in the subsurface is predicted by the mass transfer equation, which is derived by integrating Darcy's law with the equation of mass balance. The arsenic profiles of varying hydrogeological conditions associated with different locations in the study area are presented as breakthrough curves. The results shows that the arsenic transport is dominated by the advective flux and strongly depends on the soil-moisture flow conditions. Which may increases the arsenic load to underlaying groundwater resources. The simulated results suggest that mobility plays a vital role arsenic transport as well as on adsorbed arsenic concentration in subsurface. Likewise, the adsorption isotherms show that the high peak curve for Bairai and low at Sikarderpur. A higher pollution risk is observed in the Belthara Road, whereas a lower vulnerability is computed in the north and northeast regions. This study can help in strategising sustainable groundwater management and protection planning of identified regions of India. Keywords: Arsenic transport, Adsorption, Subsurface, Sustainable groundwater managemen