Knowledge extraction of sonophotocatalytic treatment for acid blue 113 dye removal by artificial neural networks

Removing decolorizing acid blue 113 (AB113) dye from textile wastewater is challenging due to its high stability and resistance to removal. In this study, we used an artificial neural network (ANN) model to estimate the effect of five different variables on AB113 dye removal in the sonophotocatalytic process. The five variables considered were reaction time (5-25 min), pH (3-11), ZnO dosage (0.2-1.0 g/L), ultrasonic power (100-300 W/L), and persulphate dosage (0.2-3 mmol/L). The most effective model had a 5-7-1 architecture, with an average deviation of 0.44 and R² of 0.99. A sensitivity analysis was used to analyze the impact of different process variables on removal efficiency and to identify the most effective variable settings for maximum dye removal. Then, an imaginary sonophotocatalytic system was created to measure the quantitative impact of other process parameters on AB113 dye removal. The optimum process parameters for maximum AB 113 removal were identified as 6.2 pH, 25 min reaction time, 300 W/L ultrasonic power, 1.0 g/L ZnO dosage, and 2.54 mmol/L persulfate dosage. The model created was able to identify trends in dye removal and can contribute to future experiments.

Development of artificial neural networks software for arsenic adsorption from an aqueous environment

Arsenic contamination is a global problem, as it affects the health of millions of people. For this study, data-driven artificial neural network (ANN) software was developed to predict and validate the removal of As(V) from an aqueous solution using graphene oxide (GO) under various experimental conditions. A reliable model for wastewater treatment is essential in order to predict its overall performance and to provide an idea of how to control its operation. This model considered the adsorption process parameters (initial concentration, adsorbent dosage, pH, and residence time) as the input variables and arsenic removal as the only output. The ANN model predicted the adsorption efficiency with high accuracy for both training and testing datasets, when compared with the available response surface methodology (RSM) model. Based on the best model synaptic weights, user-friendly ANN software was created to predict and analyze arsenic removal as a function of adsorption process parameters. We developed various graphical user interfaces (GUI) for easy use of the developed model. Thus, a researcher can efficiently operate the software without an understanding of programming or artificial neural networks. Sensitivity analysis and quantitative estimation were carried out to study the function of adsorption process parameter variables on As(V) removal efficiency, using the GUI of the model. The model prediction shows that the adsorbent dosages, initial concentration, and pH are the most influential parameters. The efficiency was increased as the adsorbent dosages increased, decreasing with initial concentration and pH. The result show that the pH 2.0-5.0 is optimal for adsorbent efficiency (%).

Comparative analysis of the diagnostic performance of five commercial COVID-19 qRT PCR kits used in India

To meet the unprecedented requirement of diagnostic testing for SARS-CoV-2, a large number of diagnostic kits were authorized by concerned authorities for diagnostic use within a short period of time during the initial phases of the ongoing pandemic. We undertook this study to evaluate the inter-test agreement and other key operational features of 5 such commercial kits that have been extensively used in India for routine diagnostic testing for COVID-19. The five commercial kits were evaluated, using a panel of positive and negative respiratory samples, considering the kit provided by National Institute of Virology, Indian Council of Medical Research (2019-nCoV Kit) as the reference. The positive panel comprised of individuals who fulfilled the 3 criteria of being clinically symptomatic, having history of contact with diagnosed cases and testing positive in the reference kit. The negative panel included both healthy and disease controls, the latter being drawn from individuals diagnosed with other respiratory viral infections. The same protocol of sample collection, same RNA extraction kit and same RT-PCR instrument were used for all the kits. Clinical samples were collected from a panel of 92 cases and 60 control patients, who fulfilled our inclusion criteria. The control group included equal number of healthy individuals and patients infected with other respiratory viruses (n = 30, in each group). We observed varying sensitivity and specificity among the evaluated kits, with LabGun COVID-19 RT-PCR kit showing the highest sensitivity and specificity (94% and 100% respectively), followed by TaqPath COVID-19 Combo and Allplex 2019-nCoV assays. The extent of inter-test agreement was not associated with viral loads of the samples. Poor correlation was observed between Ct values of the same genes amplified using different kits. Our findings reveal the presence of wide heterogeneity and sub-optimal inter-test agreement in the diagnostic performance of the evaluated kits and hint at the need of adopting stringent standards for fulfilling the quality assurance requirements of the COVID-19 diagnostic process.

Modeling and optimization of process parameters of biofilm reactor for wastewater treatment

The efficiency of heavy metal in biofilm reactors depends on absorption process parameters, and those relationships are complicated. This study explores artificial neural networks (ANNs) feasibility to correlate the biofilm reactor process parameters with absorption efficiency. The heavy metal removal and turbidity were modeled as a function of five process parameters, namely pH, temperature(°C), feed flux(ml/min), substrate flow(ml/min), and hydraulic retention time(h). We developed a standalone ANN software for predicting and analyzing the absorption process in handling industrial wastewater. The model was tested extensively to confirm that the predictions are reasonable in the context of the absorption kinetics principles. The model predictions showed that the temperature and pH values are the most influential parameters affecting absorption efficiency and turbidity.

Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass

Heavy metal ions in aqueous solutions are taken into account as one of the most harmful environmental issues that ominously affect human health. Pb(II) is a common pollutant among heavy metals found in industrial wastewater, and various methods were developed to remove the Pb(II). The adsorption method was more efficient, cheap, and eco-friendly to remove the Pb(II) from aqueous solutions. The removal efficiency depends on the process parameters (initial concentration, the adsorbent dosage of T-Fe3O4 nanocomposites, residence time, and adsorbent pH). The relationship between the process parameters and output is non-linear and complex. The purpose of the present study is to develop an artificial neural networks (ANN) model to estimate and analyze the relationship between Pb(II) removal and adsorption process parameters. The model was trained with the backpropagation algorithm. The model was validated with the unseen datasets. The correlation coefficient adj.R² values for total datasets is 0.991. The relationship between the parameters and Pb(II) removal was analyzed by sensitivity analysis and creating a virtual adsorption process. The study determined that the ANN modeling was a reliable tool for predicting and optimizing adsorption process parameters for maximum lead removal from aqueous solutions.

Prediction of batch sorption of barium and strontium from saline water

Celestite and barite formation results in contamination of barium and strontium ions hinder oilfield water purification. Conversion of bio-waste sorbent products deals with a viable, sustainable and clean remediation approach for removing contaminants. Biochar sorbent produced from rice straw was used to remove barium and strontium ions of saline water from petroleum industries. The removal efficiency depends on biochar amount, pH, contact time, temperature, and Ba/Sr concentration ratio. The interactions and effects of these parameters with removal efficiency are multifaceted and nonlinear. We used an artificial neural network (ANN) model to explore the correlation between process variables and sorption responses. The ANN model is more accurate than that of existing kinetic and isotherm equations in assessing barium and strontium removal with adj. R² values of 0.994 and 0.991, respectively. We developed a standalone user interface to estimate the barium and strontium removal as a function of sorption process parameters. Sensitivity analysis and quantitative estimation were carried out to study individual process variables' impact on removal efficiency.

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

Bifidobacterium longum-fermented rice bran and rice bran supplementation affects the gut microbiome and metabolome

This study investigated gut microbiota composition along with food, host, and microbial derived metabolites in the colon and systemic circulation of healthy mice following dietary rice bran and fermented rice bran intake. Adult male BALB/c mice were fed a control diet or one of two experimental diets containing 10% w/w rice bran fermented by Bifidobacterium longum or 10% w/w non-fermented rice bran for 15 weeks. Metabolomics was performed on the study diets (food), the murine colon and whole blood. These were analysed in concert with 16S rRNA amplicon sequencing of faeces, caecum, and colon microbiomes. Principal components analysis of murine microbiota composition displayed marked separation between control and experimental diets, and between faecal and tissue (caecum and colon) microbiomes. Colon and caecal microbiomes in both experimental diet groups showed enrichment of Roseburia, Lachnospiraceae, and Clostridiales related amplicon sequence variants compared to control. Bacterial composition was largely similar between experimental diets. Metabolite profiling revealed 530 small molecules comprising of 39% amino acids and 21% lipids that had differential abundances across food, colon, and blood matrices, and statistically significant between the control, rice bran, and fermented rice bran groups. The amino acid metabolite, N-delta-acetylornithine, was notably increased by B. longum rice bran fermentation when compared to non-fermented rice bran in food, colon, and blood. These findings support that dietary intake of rice bran fermented with B. longum modulates multiple metabolic pathways important to the gut and overall health.

Use of GenoType® MTBDRplus assay to assess drug resistance and mutation patterns of multidrug-resistant tuberculosis isolates in northern India

PURPOSE

The emergence and spread of multidrug-resistant tuberculosis (MDR-TB) is a major public health problem. The diagnosis of MDR-TB is of paramount importance in establishing appropriate clinical management and infection control measures. The aim of this study was to evaluate drug resistance and mutational patterns in clinical isolates MDR-TB by GenoType® MTBDRplus assay.

MATERIAL AND METHODS

A total of 350 non-repeated sputum specimens were collected from highly suspected drug-resistant pulmonary tuberculosis (PTB) cases; which were processed by microscopy, culture, differentiation and first line drug susceptibility testing (DST) using BacT/ALERT 3D system.

RESULTS

Among a total of 125 mycobacterium tuberculosis complex (MTBC) strains, readable results were obtained from 120 (96%) strains by GenoType® MTBDRplus assay. Only 45 MDR-TB isolates were analysed for the performance, frequency and mutational patterns by GenoType® MTBDRplus assay. The sensitivity of the GenoType® MDRTBplus assay for detecting individual resistance to rifampicin (RIF), isoniazid (INH) and multidrug resistance was found to be 95.8%, 96.3% and 97.7%, respectively. Mutation in codon S531L of the rpoB gene and codon S315T1 of katG genes were dominated in MDR-TB strains, respectively (P < 0.05).

CONCLUSIONS

The GenoType® MTBDRplus assay is highly sensitive with short turnaround times and a rapid test for the detection of the most common mutations conferring resistance in MDR-TB strains that can readily be included in a routine laboratory workflow.

Detection of 123 bp fragment of insertion element IS6110 Mycobacterium tuberculosis for diagnosis of extrapulmonary tuberculosis

PURPOSE

Extrapulmonary tuberculosis (EPTB) is emerging problem in developing and developed countries. The diagnosis of EPTB in its different clinical presentations remains a true challenge. IS6110-based polymerase chain reaction (PCR) is used for rapid identification and positivity rate of the Mycobacterium tuberculosis complex in clinical isolates of different sites of EPTB. The present study was carried out to study the prevalence of M. tuberculosis complex in clinical isolates of EPTB at tertiary care centres in Lucknow.

MATERIALS AND METHODS

Seven hundred fifty-six specimens were collected from the suspected cases of EPTB which were processed for Mycobacteria by Ziehl Neelson (ZN) staining and BACTEC culture. All the specimens were also processed for IS6110-based PCR amplification with primers targeting 123 bp fragment of insertion element IS6110 of the M. tuberculosis complex.

RESULTS

Of these 756 specimens, 71(9.3%) were positive for acid fast bacilli (AFB) by ZN staining, 227(30.1%) were positive for mycobacteria by BACTEC culture and IS6110 PCR were positive for M. tuberculosis complex in 165 (20.7%) isolates. We found a significant difference in sensitivities of different tests (P<0.05).

CONCLUSIONS

This study reveals the positivity of M. tuberculosis complex in clinical isolates of EPTB case in tertiary care hospitals in Northern India. 72.7% of M. tuberculosis complex was confirmed by IS6110-PCR in culture isolates from different sites of EPTB. The high prevalence of the M. tuberculosis complex was seen in lymph node aspirate and synovial fluid. However, utility of PCR may play a potentially significant role in strengthening the diagnosis of EPTB especially targeting IS6110.

Age-related decline in multiple unit action potentials of CA3 region of rat hippocampus: correlation with lipid peroxidation and lipofuscin concentration and the effect of centrophenoxine

Changes in lipid peroxidation, lipofuscin concentration, and multiple unit activity (MUA recorded in conscious animals) in the CA3 region were studied in the hippocampus of male Wistar rats aged 4, 8, 16, and 24 months. The lipid peroxidation and lipofuscin concentration were increased with age. The MUA, however, declined with age. Correlational analyses were performed for the four age groups to determine the relationship between the age-associated decline in MUA with the age-related alterations in lipid peroxidation and lipofuscin concentrations. The age-related increase in lipid peroxidation correlated positively with the age-associated increase in lipofuscin concentration. The age-related increases in lipid peroxidation and lipofuscin concentration correlated negatively with the changes in MUA. Since lipid peroxidation may affect neuronal electrophysiology, our data suggested that age-related increase in lipid peroxidation may contribute to an age-associated decline in neuronal electrical activity. Centrophenoxine effects were studied on the three above-mentioned age-associated changes in the hippocampus. The drug had no effect on all three parameters in 4- and 8-month-old rats. In 16- and 24-month-old rats, however, the drug significantly increased the MUA but concomitantly decreased lipofuscin concentration and lipid peroxidation. Correlational analyses of the data on MUA, lipid peroxidation and lipofuscin concentration from the centrophenoxine-treated animals showed that the drug-induced diminution in both lipofuscin and lipid peroxidation was significantly correlated with the drug-induced increase in MUA. The differential effect of the drug in younger (4-8 months) and older (16-24 months) animals indicated that the stimulation of MUA was clearly associated with concomitant decrease in lipid peroxidation and lipofuscin concentration.

Modulation of mitomycin C resistance by glutathione transferase inhibitor ethacrynic acid

This study was undertaken to elucidate the mechanism(s) of cross-resistance (4.9-fold) to mitomycin C (MMC) in a multi-drug-resistant cell line, P388/R-84. Intracellular accumulation of MMC by sensitive (P388/S) and P388/R-84 cells was comparable. Despite a 32% reduction in NADPH cytochrome P-450 reductase activity (responsible for MMC activation) in P388/R-84 cells, the rate of MMC bio-reduction by sensitive and resistant cells was similar. These results suggested that MMC resistance in P388/R-84 cell line must depend on factors other than impaired drug accumulation or bio-activation. Recent studies suggest that glutathione transferase (GST) dependent drug detoxification also contributes to cellular resistance of a variety of alkylating agents. Even though overexpression of GST has been noted in some MMC resistant tumor cells, it is not known if its level affects sensitivity to MMC. We have, therefore, determined the effect of ethacrynic acid (an inhibitor of GST activity) treatment on MMC cytotoxicity in P388/R-84 cells, which have about 2-fold higher GST activity than P388/S cells. The IC50 value for the inhibition of GST activity in vitro by ethacrynic acid (EA) was 16.5 microM (5 micrograms/ml). A depletion in intracellular GSH was also observed by treating P388/R-84 cells with EA alone or in combination with MMC. A non-toxic concentration of EA (1 microgram/ml; 3.3 microM) increased MMC cytotoxicity by 36% in P388/R-84 cells. MMC cytotoxicity was increased 2-fold by EA treatment in glutathione (GSH)-depleted P388/R-84 cells. These results suggest that GST mediated drug inactivation may represent another important mechanism of MMC resistance.

Differential induction of glutathione transferase isoenzymes of mice stomach by diallyl sulfide, a naturally occurring anticarcinogen

Diallyl sulfide (DAS), an organosulfur compound identified as the flavor component in garlic, has been shown to inhibit chemically induced neoplasia of forestomach and lung in mice. Even though the exact mechanism(s) of anti-neoplastic activity of DAS is not known, several independent studies suggest that this effect may, at least in part, be due to the elevation of glutathione-S-transferase (GST) activity. To gain further insight into the mechanism(s) of anti-carcinogenic activity of DAS, we have determined effect of orally administered DAS (25, 50 and 75 mumol) on levels of alpha, mu and pi class GSTs and glutathione (GSH) peroxidase and GSH reductase activities of female A/J mice stomach. Western blotting revealed presence of alpha, mu and pi class GSTs in mice stomach. A significant increase in all the three classes of GSTs was observed in the stomach of mice treated with DAS. Maximum increase in GST alpha and pi was evident by treating the animals with 75 mumol DAS whereas maximum induction of GST mu occurred after treating mice with 50 mumol DAS. GSH peroxidase activity towards t-butyl-hydroperoxide increased in a dose-dependent fashion in the mice stomach treated with DAS. Even though this activity towards hydrogen peroxide was similar in mice treated with 50 or 75 mumol DAS, these values were significantly higher than that of the control. GSH reductase was also elevated in the stomach of mice treated with 75 mumol DAS. These results suggest that DAS may exert anti-neoplastic effect by modulating GSH dependent detoxification enzymes.

Sister chromatid exchange in human chromosomes from normal individuals and epileptic patients on combinations of anticonvulsants

Sister chromatid exchange (SCE) frequency, a sensitive indicator in mutagenicity testing, and mitotic index (MI) have been studied to observe genotoxic effects in epileptic patients on routine combinations of anticonvulsant therapy. All patients, both male and female and from various age groups, revealed an increased frequency of SCE per metaphase and a low MI (P less than 0.001) with respect to controls. A nonsignificant decrease in SCE frequency has been observed with an increase in the age of onset of epilepsy. Although the SCE frequency increased and the MI decreased in some groups with respect to the duration of epilepsy, there was no difference observed in SCE frequency with the duration of therapy.

Mutagenic risk in epileptic patients before and after anticonvulsant therapy

Therapy with anticonvulsant drugs has often been found to result in somatic chromosome aberrations in adult patients. There is also the possibility of epileptic fathers or mothers playing a role in the production of congenital malformations in their offspring. We have used the technique of sister chromatid exchange (SCE), a sensitive indicator of mutagenicity, to observe the mutagenic susceptibility in both male and female epileptic patients in different age groups prior to and after anticonvulsant therapy, and with respect to control. The frequency of SCE was significantly higher in all the age groups for treated and untreated cases compared with control. Between treated and untreated subjects in age group 26-50 years, a significantly higher SCE frequency was observed in the untreated patients (p less than 0.01). Similarly, untreated male patients showed a significantly higher SCE frequency (p less than 0.025) compared with treated male patients. Although the results of this study provide a general assessment of mutagenicity in epileptic patients that agrees with other studies and emphasizes the role of the disease in the higher occurrence of congenital malformation in their offspring, the importance of higher SCE frequency in untreated patients remains to be explained in further studies.

Mutagenic potential of anticonvulsant diphyenylhydantoin (DPH) on human lymphocytes in vitro

Diphenylhydantoin (DPH)-treated human peripheral blood cultures were examined for sister chromatid exchange (SCE) frequency and mitotic index. A significantly enhanced SCE frequency in DPH-treated cultures was observed at a 15 micrograms/ml concentration (10-20 micrograms/ml DPH therapeutic range) and above. These results suggest an enhanced SCE response of lymphocytes in the therapeutic blood level of DPH. A significant linear fall in mitotic index was observed with increasing DPH concentrations. It is postulated that even in therapeutic doses DPH possibly affects nucleic acid metabolism.