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World's highest arsenic (As) contamination is well-documented for the groundwater system of southwestern region (mainly Jashore district) of Bangladesh, where the majority of inhabitants are underprivileged. To mitigate As poisoning in southwestern Bangladesh, numerous steps have been taken so far by the government and non-governmental organizations (NGOs). Among them, digging deep tube wells and As removal by naturally deposited Fe(OH) 3 species are being widely practiced in the contaminated areas. However, these actions have been left unmonitored for decades, making people unaware of this naturally occurring deadly poison in their drinking water. Hence, water samples (n = 63, both treated and untreated) and soil samples (n = 4) were collected from different spots in Jashore district to assess the safety level of drinking water and to understand the probable reasons for high As(III) contamination. About 93.7% of samples were found to contain As(III) above 10 μg/L; among them, 38% contained above 50 μg/L. The study shows that current As(III) removal strategies in the study area are ineffective. In this connection, a simple low-cost As(III) removal adsorbent is proposed that can be prepared with very cheap and locally available materials like iron sludge and charcoal. The adsorbent was characterized in terms of SEM, EDX, and XPS. The optimal dosage of the adsorbent was investigated for real-life application concerning several vital water quality parameters. The Fe-C adsorbent exhibited a maximum As(III) removal efficiency of 92% in real groundwater samples. The study will allow policymakers for informed decision-making regarding water body management as well as enable the local people to avail As-safe water in a way that aligns with their economic factors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Chemoresistance is an imminent therapeutic challenge for breast cancer. Previous evidence suggests that breast cancer stem cells (BCSC) develop resistance through upregulation of stemness and chemo-evasion markers viz. SOX2, OCT4, NANOG, MDR1 and CD44, following anticancer chemotherapeutic treatments. Early studies suggest an inhibitory role of Kaempferol in BCSC propagation through downregulation of epithelial to mesenchymal transition. We hypothesized that the pathway involved in chemoresistance could be effectively addressed through Kaempferol (K), alone or in combination with Verapamil (V), which is an inhibitor of MDR1. We used K in combination with V, in multiple assays to determine if there was an inhibitory effect on BCSC. Both K and KV attenuated pH-dependent mammosphere formation in primary BCSC and MDA-MB-231 cells. RNA and protein (immunocytochemistry, western blot) expression of candidate markers viz. SOX2, OCT4, NANOG, MDR1 and CD44 were carried out in the presence or absence of candidate drugs in ex-vivo grown primary BCSC and MDA-MB-231 cell line. Immunoprecipitation assay, cell cycle analysis was carried out in MDA-MB-231. Our candidate drugs were not only anti-proliferative, but also downregulated candidate genes expression at RNA and protein level in both settings, with more robust efficacy in KV treatment than K; induced G2/M dependent cell cycle arrest, and interrupted physical association of CD44 with NANOG as well as MDR1 in MDA-MB-231. In primary tumor explant but not in adjacent normal tissue, our candidate drugs K and KV induced robust γH2AX expression. Thus, our candidate drugs are effective in attenuating BCSC survival., (Copyright © 2022. Published by Elsevier Inc.)

In a context specific manner, Intra-species genomic variation plays an important role in phenotypic diversity observed among pathogenic microbes. Efficient classification of these pathogens is important for diagnosis and treatment of several infectious diseases. NGS technologies have provided access to wealth of data that can be utilized to discover important markers for pathogen classification. In this paper, we described three different approaches (Jensen-Shannon divergence, random forest and Shewhart control chart) for identification of a minimal set of SNPs that can be used for classification of organisms. These methods are generic and can be implemented for analysis of any organism. We have shown usefulness of these approaches for analysis of Mycobacterium tuberculosis and Escherichia coli isolates. We were able to identify a minimal set of 18 SNPs that can be used as molecular markers for phylogroup based classification and 8 SNPs for pathogroup based classification of E. coli., (Copyright © 2018 Elsevier Inc. All rights reserved.)