Application of phytoaccumulation perspective of Monochoria hastate L. on fluoride contaminated water in hydroponic treatment: its statistical design and characterization studies.

The present research work approaches the accumulation of fluoride ions from contaminated water using an aquatic plant Monochoria hastate L. in hydroponic culture. A design of experiment (DOE) has been adopted and an analysis of variance has been conducted to establish the statistical significance of various process parameters. The different experimental factors are root and shoot (Factor A), fluoride concentration (Factor B), and experimental days (Factor C) largely influence the output response. Plants treated with 5 mg/L of fluoride solutions accumulated the highest concentration in root biomass 1.23 mg/gm, and shoot biomass 0.820 mg/gm, dry weight after 21 days' experimentation. The accumulation mechanism and potentiality of treated plants depend on root cells of the plasma membrane and energy-capturing molecules of adenosine triphosphate. Monochoria hastate L. root biomass was characterized to confirm the accumulation of fluoride ions in the experimented plants using scanning electron micrographs-energy dispersive spectrum (SEM-EDS), and Fourier transforms infrared analysis (FTIR) analysis.

The novelty of this study is the high fluoride accumulation efficiency in hydroponic treatment by Monochoria hastate L an excellent choice for phytoremediation technique. The Design of Experiment (DOE) has a good approach for the optimization of fluoride in the accumulation process. The maximum absorption of fluoride ions in root biomass is 1.23 mg/gm, and shoot biomass is 0.820 mg/gm, dry weight after 21 days of treatment. To know the fluoride ions in shoot and root biomass are characterized using scanning electron micrographs-energy dispersive spectrum (SEM-EDS), and Fourier transforms infrared analysis (FTIR).

Removal of Cr (VI) from aqueous solution by activated charcoal derived from Sapindus trifoliate L fruit biomass using continuous fixed bed column studies.

In this study, the removal of hexavalent chromium from aqueous solution were examined using activated charcoal derived from Sapindus trifoliate L fruit biomass in continuous fixed-bed column studies. The activated S. trifoliate L fruit charcoal was prepared by treating the fruit powder using concentrated nitric acid solution. Experiments were performed to investigate the effect of bed height and initial concentration on the breakthrough and saturation times. The breakthrough and saturation time increases with increase in bed height and initial concentration of chromium solutions. The maximum adsorption capacity of S. trifoliate L charcoal for hexavalent chromium was found to be 1.719 mg/g in the bed height 15 cm and initial concentration 10 mg/L, respectively. Column data required at various conditions were explained using Bohart-Adams and Thomas model. Two models were found to be suitable to describe the definite part of the dynamic behaviour of the column with regard to bed-height and initial concentration of hexavalent chromium. On comparison of Adjusted R2 and estimated standard error, the Thomas model was found to best-fitted model and can be used to predict the adsorption of the hexavalent chromium in fixed-bed column studies. Activated S. trifoliate L fruit charcoal was characterised by SEM-EDX and FTIR analysis.

Adsorption studies of chromium (VI) removal from water by lanthanum diethanolamine hybrid material.

In the present research work, lanthanum diethanolamine hybrid material is synthesized by co-precipitation method and used for the removal of Cr(VI) from synthetic dichromate solution and hand pump water sample. The sorption experiments were carried out in batch mode to optimize various influencing parameters such as adsorbent dose, contact time, pH, competitive anions and temperature. The characterization of the material and mechanism of Cr(VI) adsorption on the material was studied by using scanning electron microscope, Fourier transform infrared, X-ray diffraction, Brunauer-Emmett-Teller and thermogravimetric analysis-differential thermal analysis. Adsorption kinetics studies reveal that the adsorption process followed first-order kinetics and intraparticle diffusion model with correlation coefficients (R2) of 0.96 and 0.97, respectively. The adsorption data were best fitted to linearly transformed Langmuir isotherm with correlation coefficient (R2) of 0.997. The maximum removal of Cr(VI) is found to be 99.31% at optimal condition: pH = 5.6 of the solution, adsorbent dose of 8 g L(-1) with initial concentration of 10mgL(-1) of Cr(VI) solution and an equilibrium time of 50 min. The maximum adsorption capacity of the material is 357.1 mg g(-1). Thermodynamic parameters were evaluated to study the effect of temperature on the removal process. The study shows that the adsorption process is feasible and endothermic in nature. The value of E (260.6 kJ mol(-1)) indicates the chemisorption nature of the adsorption process. The material is difficult to be regenerated. The above studies indicate that the hybrid material is capable of removing Cr(VI) from water.

Amino-functionalized novel biosorbent for effective removal of fluoride from water: process optimization using artificial neural network and mechanistic insights.

Aqueous fluoride ( F - ) pollution is a global threat to potable water security. The present research envisions the development of novel adsorbents from indigenous Limonia acidissima L. (fruit pericarp) for effective aqueous defluoridation. The adsorbents were characterized using instrumental analysis, e.g., TGA-DTA, ATR-FTIR, SEM-EDS, and XRD. The batch-mode study was performed to investigate the influence of experimental variables. The artificial neural network (ANN) model was employed to validate the adsorption. The dataset was fed to a backpropagation learning algorithm of the ANN (BPNN) architecture. The four-ten-one neural network model was considered to be functioning correctly with an absolute-relative-percentage error of 0.633 throughout the learning period. The results easily fit the linearly transformed Langmuir isotherm model with a correlation coefficient ( R 2 ) > 0.997. The maximum F - removal efficiency was found to be 80.8 mg/g at the optimum experimental condition of pH 7 and a dosage of 6 g/L at 30 min. The ANN model and experimental data provided a high degree of correlation ( R 2 = 0.9964), signifying the accuracy of the model in validating the adsorption experiments. The effects of interfering ions were studied with real F - water. The pseudo-second-order kinetic model showed a good fit to the equilibrium dataset. The performance of the adsorbent was also found satisfactory with field samples and can be considered a potential adsorbent for aqueous defluoridation.

Application of artificial neural network for prediction of fluoride removal efficiency using neutralized activated red mud from aqueous medium in a continuous fixed bed column.

The present research work approaches the removal of fluoride from aqueous medium using neutralized activated red mud (NARM) in a continuous fixed bed column. Artificial neural network (ANN) technique was applied effectively for optimization of the model for the practicability of the removal process. The consequences of various experimental variables, like bed length, adsorbate concentration, experimental time, and adsorbate solution flow rate are studied to know the breakthrough point and saturation times. The highest removal potentiality of NARM was considered to be 3.815 mg g-1 of F- in the bed height of 15 cm, starting concentration 1 ppm, susceptible time 120 min, adsorbate solution flow rate 0.5 mL min-1, and constant room temperature, respectively. Bohart-Adams and Thomas models were considered to describe the fixed bed column effect to the bed height and adsorbate concentrations. The experimental data were applied to a back propagation (BP) learning algorithm programme with a four-seven-one architecture model. The artificial neural network model was considered to be functioning correctly as absolute relative percentage error throughout the learning period. Differentiation between the predicted outcomes from ANN model and actual results from experimental analysis affords a high degree of correlation (R2 = 0.998) stipulating that the model was able to predict the adsorption efficiency. Experimented adsorbent materials were characterized using different instrumental analysis that is scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD).

Genomewide association study of C-peptide surfaces key regulatory genes in Indians.

Insulin is a commonly used measure of pancreatic ß-cell function but exhibits a short half-life in the human body. During biosynthesis, insulin release is accompanied by C-peptide at an equimolar concentration which has a much higher plasma half-life and is therefore projected as a precise measure of ß-cell activity than insulin. Despite this, genetic studies of metabolic traits haveneglected the regulatory potential of C-peptide for therapeutic intervention of type-2 diabetes. The present study is aimed to search genomewide variants governing C-peptide levels in genetically diverse and high risk population for metabolic diseases-Indians. We performed whole genome genotyping in 877 healthy Indians of Indo-European origin followed by replication of variants with P ≤ 1 × 10-3 in an independent sample-set of 1829 Indians. Lead-associated signals were also tested in-silico in 773 Hispanics. To secure biological rationale for observed association, we further carried out DNA methylation quantitative trait loci analysis in 233 Indians and publicly available regulatory data was mined. We discovered novel lncRNA gene AC073333.8 with the strongest association with C-peptide levels in Indians that however missed genomewide significance. Also, noncoding genes, RP1-209A6.1 and RPS3AP5; protein gene regulators, ZNF831 and ETS2; and solute carrier protein gene SLC15A5 retained robust association with C-peptide after meta-analysis. Integration of methylation data revealed ETS2 and ZNF831 single-nucleotide polymorphisms as significant meth-QTLs in Indians. All genes showed reasonable expression in the human lung, signifying alternate important organs for C-peptide biology. Our findings mirror polygenic nature of C-peptide where multiple small-effect size variants in the regulatory genome principally govern the trait biology.