Malaria hotspots and climate change trends in the hyper-endemic malaria settings of Mizoram along the India-Bangladesh borders.

India has made tremendous progress in reducing malaria mortality and morbidity in the last decade. Mizoram State in North-East India is one of the few malaria-endemic regions where malaria transmission has continued to remain high. As Mizoram shares international borders with Bangladesh and Myanmar, malaria control in this region is critical for malaria elimination efforts in all the three countries. For identifying hotspots for targeted intervention, malaria data from 385 public health sub-centers across Mizoram were analyzed in the Geographic Information System. Almost all the sub-centers reporting high Annual Parasite Index (> 10) are located in Mizoram's districts that border Bangladesh. Getis-Ord Gi* statistic shows most of the sub-centers located along the Bangladesh border in the Lawngtlai and Lunglei districts to be the malaria hotspots. The hotspots also extended into the Mamit and Siaha districts, especially along the borders of Lawngtlai and Lunglei. Analysis of terrain, climatic, and land use/land cover datasets obtained from the Global Modelling and Assimilation Office and satellite images show Mizoram's western part (Lawngtlai, Lunglei, and Mamit districts) to experience similar topographic and climatic conditions as the bordering Rangamati district in the Chittagong division of Bangladesh. Climatic trends in this region from 1981 to 2021, estimated by the Mann-Kendall test and Sen's slope estimates, show an increasing trend in minimum temperature, relative humidity, rainfall, and the associated shift of climatic pattern (temperate to tropical monsoon) could facilitate malaria transmission. The quasi-Poisson regression model estimates a strong association (p < 0.001) between total malaria cases, temperature range, and elevation. The Kruskal-Wallis H test shows a statistically significant association between malaria cases and forest classes (p < 0.001). A regional coordination and strategic plan are required to eliminate malaria from this hyper-endemic malaria region of North-East India.

Adsorptive removal of noxious atrazine using graphene oxide nanosheets: Insights to process optimization, equilibrium, kinetics, and density functional theory calculations.

Atrazine is a toxic herbicide whose alarming rate of contamination in the drinking water and wastewater poses a severe threat to the environment and human health. Here in this study, the graphene oxide (GO) nanosheets were prepared using Hummers' method with minor modification and studied as a potential adsorbent for atrazine removal from simulated wastewater. The spectroscopy and microscopic analysis confirmed the successful formation of GO with a multilayer structure resembling the crumpled sheets with random stacking. The Response Surface Methodology (RSM) employing Box Behnken design (BBD) was successfully developed to predict the optimal conditions for maximal atrazine removal as adsorbent dosage 121.45 mg/L; initial feed concentration 27.03 mg/L; temperature 27.69 °C, pH 5.37, and time 180 min. The atrazine adsorption onto GO was found to be higher in acidic pH and lower temperature. Density functional theory (DFT) calculation of adsorbent-adsorbate complex in the implicit solvent medium suggests adsorption affinity energy of -24.4 kcal/mol for atrazine. A careful observation of the molecules configuration and binding energy showed that the π-π interactions and hydrogen bonds played a significant role in the adsorption phenomena. Langmuir isotherm suited well to the adsorption process with a maximum adsorption capacity of 138.19 mg/g, at 318 K. The fitness of kinetic models for atrazine adsorption onto GO nanosheets were in following order Ho < Sobkowsk-Czerwi < Avrami model based on their correlation coefficient (R2) values. Reusability analysis showed that GO nanosheets could be effectively recycled using 0.01 N NaOH up to six cycles of atrazine removal. Thus, this study provided a theoretical and experimental basis for the potential application of GO nanosheets as a novel adsorbent for the removal of hazardous atrazine.

Crystallographic, spectral and computational studies on (S)-4-(4-aminobenzyl) oxazolidin-2-one.

The experimental geometry (XRD), vibrational (IR and Raman), electronic (UV-visible) and NMR spectra of (S)-4-(4-Amino-benzyl)-oxazolidin-2-one (ABO) have been corroborated with the corresponding first principle calculated values at DFT using hybrid B3LYP exchange correlation functional invoking 6-311++g(d, p) basis set. The optimized geometrical parameters were found to be in satisfactory agreement with the experimental values obtained from the X-ray diffraction structural features of ABO. The scaled down computed vibrational frequencies with appropriate scaling factors were in good correspondence with the experimental observations. Room-temperature 1H and 13C nuclear magnetic resonance (NMR) studies were supported by advanced density functional theory calculations. The theoretical spectrograms of FT-IR, FT-Raman, 1H NMR, 13C NMR and UV of the title compound have been constructed and compared with experimental spectra and Hirshfeld surface analysis has also been made to study the intermolecular interactions. The electronic structure of the title compound has also been studied in terms of HOMO, LUMO and MESP diagrams.

Seroprevalence and risk factors of brucellosis in livestock in the wildlife and livestock interface area of Similipal Biosphere Reserve, India.

BACKGROUND AND AIM: Brucellosis is an important zoonotic disease that affects fertility in farm animals. The risk factors of brucellosis have not been well studied. This study aimed to understand the seroprevalence and risk factors of brucellosis among livestock in Bangriposi block of Mayurbhanj district in Odisha, a region that borders Similipal wildlife reserve. MATERIALS AND METHODS: Rose Bengal plate test (RBPT) was carried out to estimate the seroprevalence of the livestock in this region. Bivariate analysis was carried out to analyze the association between the variables and brucellosis. Binary logistic regression was performed to assess the risk factors associated with brucellosis in the livestock. RESULTS: Based on RBPT, the seroprevalence of brucellosis among cattle and goats was estimated to be 1.1% and 11.2%, respectively. Binary logistic regression analysis indicates that study area, age, goats, animals with a history of abortion, and rearing practices were the major risk factors in this region. CONCLUSION: This is one of the first studies in India to shed light on risk factors of brucellosis, an important neglected disease that affects the health of animals and humans and nation's economy.