<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Shah, Manan</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Sarode, Priyanka</style></author><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed G.</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh S.</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metagenomic insights to understand transient influence of Yamuna River on taxonomic and functional aspects of bacterial and archaeal communities of River Ganges</style></title><secondary-title><style face="normal" font="default" size="100%">Science of the Total Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Confluence zone</style></keyword><keyword><style  face="normal" font="default" size="100%">Ganges</style></keyword><keyword><style  face="normal" font="default" size="100%">Metagenomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Transient influence</style></keyword><keyword><style  face="normal" font="default" size="100%">Yamuna</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">674</style></volume><pages><style face="normal" font="default" size="100%">288-299</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;River confluences are interesting ecosystems to investigate for their microbial community structure and functional potentials. River Ganges is one of the most important and holy river of India with great mythological history and religious significance. The Yamuna River meets Ganges at the Prayagraj (formerly known as Allahabad), India to form a unique confluence. The influence of Yamuna River on taxonomic and functional aspects of microbiome at this confluence and its downstream, remains unexplored. To unveil this dearth, whole metagenome sequencing of the microbial (bacterial and archaeal) community from the sediment samples of December 2017 sampling expedition was executed using high throughput MinION technology. Results revealed differences in the relative abundance of bacterial and archaeal communities across the confluence. Grouped by the confluence, a higher abundance of Proteobacteria and lower abundance of Bacteroidetes and Firnacutes was observed for Yamuna River (G15Y) and at immediate downstream of confluence of Ganges (G15DS), as compared to the upstream, confluence, and farther downstream of confluence. A similar trend was observed for archaeal communities with a higher abundance of Euryarchaeoto in G15Y and G15DS, indicating Yamuna River's influence. Functional gene(s) analysis revealed the influence of Yamuna River on xenobiotic degradation, resistance to toxic compounds, and antibiotic resistance interceded by the autochthonous microbes at the confluence and succeeding downstream locations. Overall, similar taxonomic and functional profiles of microbial communities before confluence (upstream of Ganges) and farther downstream of confluence, suggested a transient influence of Yamuna River. Our study is significant since it may be foundational basis to understand impact of Yamuna River and also rare event of mass bathing on the microbiome of River Ganges. Further investigation would be required to understand, the underlying cause behind the restoration of microbial profiles post-confluence farther zone, to unravel the rejuvenation aspects of this unique ecosystem. (C) 2019 Elsevier B.A. All rights reserved.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">4.610</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Navale, Govinda R.</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Biosensors: frontiers in rapid detection of COVID-19</style></title><secondary-title><style face="normal" font="default" size="100%">3 Biotech</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biosensors</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Rapid detection</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">385</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The rapid community-spread of novel human coronavirus 2019 (nCOVID19 or SARS-Cov2) and morbidity statistics has put forth an unprecedented urge for rapid diagnostics for quick and sensitive detection followed by contact tracing and containment strategies, especially when no vaccine or therapeutics are known. Currently, quantitative real-time polymerase chain reaction (qRT-PCR) is being used widely to detect COVID-19 from various types of biological specimens, which is time-consuming, labor-intensive and may not be rapidly deployable in remote or resource-limited settings. This might lead to hindrance in acquiring realistic data of infectivity and community spread of SARS-CoV-2 in the population. This review summarizes the existing status of current diagnostic methods, their possible limitations, and the advantages of biosensor-based diagnostics over the conventional ones for the detection of SARS-Cov-2. Novel biosensors used to detect RNA-viruses include CRISPR-Cas9 based paper strip, nucleic-acid based, aptamer-based, antigen-Au/Ag nanoparticles-based electrochemical biosensor, optical biosensor, and Surface Plasmon Resonance. These could be effective tools for rapid, authentic, portable, and more promising diagnosis in the current pandemic that has affected the world economies and humanity. Present challenges and future perspectives of developing robust biosensors devices for rapid, scalable, and sensitive detection and management of COVID-19 are presented in light of the test-test-test theme of the World Health Organization (WHO).&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><work-type><style face="normal" font="default" size="100%">Review</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;1.798&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Shah, Manan</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Sarode, Priyanka</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed G.</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh S.</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering taxonomic and functional diversity of fungi as potential bioindicators within confluence stretch of Ganges and Yamuna Rivers, impacted by anthropogenic activities</style></title><secondary-title><style face="normal" font="default" size="100%">Chemosphere</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">252</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;River confluences are interesting ecological niche with limited information in respect of the structure and the functions of diverse microbial communities. Fungi are gaining global attention as promising biological spectacles for defining the trophic status of riverine systems. We condense existing knowledge in confluence diversity in two Indian rivers (i.e. Ganges and Yamuna), by combining sediment metagenomics using long read aided MinION nanopore sequencing. A total of 63 OTU’s were observed, of which top 20 OTU’s were considered based on relative abundance of each OTU at a particular location. Fungal genera such as&amp;nbsp;&lt;/span&gt;&lt;em style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;Aspergillus, Penicillium&lt;/em&gt;&lt;span style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;,&amp;nbsp;&lt;/span&gt;&lt;em style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;Kluveromyces, Lodderomyces,&lt;/em&gt;&lt;span style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;&amp;nbsp;and&amp;nbsp;&lt;/span&gt;&lt;em style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;Nakaseomyces&lt;/em&gt;&lt;span style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;&amp;nbsp;were deciphered as potential bio indicators of river pollution and eutrophication in the confluent zone.&amp;nbsp;&lt;/span&gt;&lt;em style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;In silico&lt;/em&gt;&lt;span style=&quot;color: rgb(46, 46, 46); font-family: NexusSerif, Georgia, &amp;quot;Times New Roman&amp;quot;, Times, STIXGeneral, &amp;quot;Cambria Math&amp;quot;, &amp;quot;Lucida Sans Unicode&amp;quot;, &amp;quot;Microsoft Sans Serif&amp;quot;, &amp;quot;Segoe UI Symbol&amp;quot;, &amp;quot;Arial Unicode MS&amp;quot;, serif; font-size: 18px; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400;&quot;&gt;&amp;nbsp;functional gene analysis uncovered hits for neurodegenerative diseases and xenobiotic degradation potential, supporting bioindication of river pollution in wake of anthropogenic intervention.&lt;/span&gt;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;5.778&lt;/p&gt;</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Gohil, Kushal</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Probiotics in the prophylaxis of COVID-19: something is better than nothing</style></title><secondary-title><style face="normal" font="default" size="100%">3 Biotech</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Anti-viral</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Gut-lung axis</style></keyword><keyword><style  face="normal" font="default" size="100%">Probiotics</style></keyword><keyword><style  face="normal" font="default" size="100%">Respiratory tract infection</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The new viral pandemic of COVID-19 is caused by a novel coronavirus (SARS-CoV-2) that has brought the world at another unprecedented crisis in terms of health and economy. The lack of specific therapeutics necessitates other strategies to prevent the spread of infection caused by this previously unknown viral etiological agent. Recent pieces of evidence have shown an association between COVID-19 disease and intestinal dysbiosis. Probiotics comprise living microbes that upon oral administration benefit human health by reshaping the composition of gut microbiota. The close kinship of the gastrointestinal and respiratory tract suggests why the dysfunction of one may incite illness in others. The emerging studies suggest the capability of probiotics to regulate immune responses in the respiratory system. The efficacy of probiotics has been studied previously on several respiratory tract viral infections. Therefore, the purpose of this review is to comprehend existing information on the gut mediated-pulmonary immunity conferred by probiotic bacteria, in the course of respiratory virus infections and administration as a prophylactic measure in COVID-19 pandemic in managing intestinal dysbiosis as well.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Review</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">2.406
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">COVID-19 associated mucormycosis: evolving technologies for early and rapid diagnosis</style></title><secondary-title><style face="normal" font="default" size="100%">3 Biotech</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biosensors</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Diagnostics</style></keyword><keyword><style  face="normal" font="default" size="100%">Mucormycosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Probiotics</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">6</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The post-coronavirus disease (COVID-19) mucormycosis is a deadly addition to the pandemic spectrum. Although it's a rare, aggressive, and opportunistic disease, the associated morbidity and mortality are significant. The complex interplay of factors aggravating CAM is uncontrolled diabetes, irrational and excessive use of antibiotics, steroids, and an impaired immune system. Recently, India has been witnessing a rapid surge in the cases of coronavirus disease-associated mucormycosis (CAM), since the second wave of COVID-19. The devastating and lethal implications of CAM had now become a matter of global attention. A delayed diagnosis is often associated with a poor prognosis. Therefore, the rapid and early diagnosis of infection would be life-saving. Prevention and effective management of mucormycosis depend upon its early and accurate diagnosis followed by a multimodal therapeutic approach. The current review summarizes an array of detection methods and highlights certain evolving technologies for early and rapid diagnosis of CAM. Furthermore, several potential management strategies have also been discussed, which would aid in tackling the neglected yet fatal crisis of mucormycosis associated with COVID-19.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">Review</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.406</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Singh, Prateek</style></author><author><style face="normal" font="default" size="100%">Ujjainiya, Rajat</style></author><author><style face="normal" font="default" size="100%">Prakash, Satyartha</style></author><author><style face="normal" font="default" size="100%">Naushin, Salwa</style></author><author><style face="normal" font="default" size="100%">Sardana, Viren</style></author><author><style face="normal" font="default" size="100%">Bhatheja, Nitin</style></author><author><style face="normal" font="default" size="100%">Singh, Ajay Pratap</style></author><author><style face="normal" font="default" size="100%">Barman, Joydeb</style></author><author><style face="normal" font="default" size="100%">Kumar, Kartik</style></author><author><style face="normal" font="default" size="100%">Gayali, Saurabh</style></author><author><style face="normal" font="default" size="100%">Khan, Raju</style></author><author><style face="normal" font="default" size="100%">Rawat, Birendra Singh</style></author><author><style face="normal" font="default" size="100%">Tallapaka, Karthik Bharadwaj</style></author><author><style face="normal" font="default" size="100%">Anumalla, Mahesh</style></author><author><style face="normal" font="default" size="100%">Lahiri, Amit</style></author><author><style face="normal" font="default" size="100%">Kar, Susanta</style></author><author><style face="normal" font="default" size="100%">Bhosale, Vivek</style></author><author><style face="normal" font="default" size="100%">Srivastava, Mrigank</style></author><author><style face="normal" font="default" size="100%">Mugale, Madhav Nilakanth</style></author><author><style face="normal" font="default" size="100%">Pandey, C. P.</style></author><author><style face="normal" font="default" size="100%">Khan, Shaziya</style></author><author><style face="normal" font="default" size="100%">Katiyar, Shivani</style></author><author><style face="normal" font="default" size="100%">Raj, Desh</style></author><author><style face="normal" font="default" size="100%">Ishteyaque, Sharmeen</style></author><author><style face="normal" font="default" size="100%">Khanka, Sonu</style></author><author><style face="normal" font="default" size="100%">Rani, Ankita</style></author><author><style face="normal" font="default" size="100%">Promila</style></author><author><style face="normal" font="default" size="100%">Sharma, Jyotsna</style></author><author><style face="normal" font="default" size="100%">Seth, Anuradha</style></author><author><style face="normal" font="default" size="100%">Dutta, Mukul</style></author><author><style face="normal" font="default" size="100%">Saurabh, Nishant</style></author><author><style face="normal" font="default" size="100%">Veerapandian, Murugan</style></author><author><style face="normal" font="default" size="100%">Venkatachalam, Ganesh</style></author><author><style face="normal" font="default" size="100%">Bansal, Deepak</style></author><author><style face="normal" font="default" size="100%">Gupta, Dinesh</style></author><author><style face="normal" font="default" size="100%">Halami, Prakash M.</style></author><author><style face="normal" font="default" size="100%">Peddha, Muthukumar Serva</style></author><author><style face="normal" font="default" size="100%">Veeranna, Ravindra P.</style></author><author><style face="normal" font="default" size="100%">Pal, Anirban</style></author><author><style face="normal" font="default" size="100%">Singh, Ranvijay Kumar</style></author><author><style face="normal" font="default" size="100%">Anandasadagopan, Suresh Kumar</style></author><author><style face="normal" font="default" size="100%">Karuppanan, Parimala</style></author><author><style face="normal" font="default" size="100%">Rahman, Syed Nasar</style></author><author><style face="normal" font="default" size="100%">Selvakumar, Gopika</style></author><author><style face="normal" font="default" size="100%">Venkatesan, Subramanian</style></author><author><style face="normal" font="default" size="100%">Karmakar, Malay Kumar</style></author><author><style face="normal" font="default" size="100%">Sardana, Harish Kumar</style></author><author><style face="normal" font="default" size="100%">Kothari, Anamika</style></author><author><style face="normal" font="default" size="100%">Parihar, Devendra Singh</style></author><author><style face="normal" font="default" size="100%">Thakur, Anupma</style></author><author><style face="normal" font="default" size="100%">Saifi, Anas</style></author><author><style face="normal" font="default" size="100%">Gupta, Naman</style></author><author><style face="normal" font="default" size="100%">Singh, Yogita</style></author><author><style face="normal" font="default" size="100%">Reddu, Ritu</style></author><author><style face="normal" font="default" size="100%">Gautam, Rizul</style></author><author><style face="normal" font="default" size="100%">Mishra, Anuj</style></author><author><style face="normal" font="default" size="100%">Mishra, Avinash</style></author><author><style face="normal" font="default" size="100%">Gogeri, Iranna</style></author><author><style face="normal" font="default" size="100%">Rayasam, Geethavani</style></author><author><style face="normal" font="default" size="100%">Padwad, Yogendra</style></author><author><style face="normal" font="default" size="100%">Patial, Vikram</style></author><author><style face="normal" font="default" size="100%">Hallan, Vipin</style></author><author><style face="normal" font="default" size="100%">Singh, Damanpreet</style></author><author><style face="normal" font="default" size="100%">Tirpude, Narendra</style></author><author><style face="normal" font="default" size="100%">Chakrabarti, Partha</style></author><author><style face="normal" font="default" size="100%">Maity, Sujay Krishna</style></author><author><style face="normal" font="default" size="100%">Ganguly, Dipyaman</style></author><author><style face="normal" font="default" size="100%">Sistla, Ramakrishna</style></author><author><style face="normal" font="default" size="100%">Balthu, Narender Kumar</style></author><author><style face="normal" font="default" size="100%">Kumar, Kiran A.</style></author><author><style face="normal" font="default" size="100%">Ranjith, Siva</style></author><author><style face="normal" font="default" size="100%">Kumar, B. Vijay</style></author><author><style face="normal" font="default" size="100%">Jamwal, Piyush Singh</style></author><author><style face="normal" font="default" size="100%">Wali, Anshu</style></author><author><style face="normal" font="default" size="100%">Ahmed, Sajad</style></author><author><style face="normal" font="default" size="100%">Chouhan, Rekha</style></author><author><style face="normal" font="default" size="100%">Gandhi, Sumit G.</style></author><author><style face="normal" font="default" size="100%">Sharma, Nancy</style></author><author><style face="normal" font="default" size="100%">Rai, Garima</style></author><author><style face="normal" font="default" size="100%">Irshad, Faisal</style></author><author><style face="normal" font="default" size="100%">Jamwal, Vijay Lakshmi</style></author><author><style face="normal" font="default" size="100%">Paddar, Masroor Ahmad</style></author><author><style face="normal" font="default" size="100%">Khan, Sameer Ullah</style></author><author><style face="normal" font="default" size="100%">Malik, Fayaz</style></author><author><style face="normal" font="default" size="100%">Ghosh, Debashish</style></author><author><style face="normal" font="default" size="100%">Thakkar, Ghanshyam</style></author><author><style face="normal" font="default" size="100%">Barik, S. K.</style></author><author><style face="normal" font="default" size="100%">Tripathi, Prabhanshu</style></author><author><style face="normal" font="default" size="100%">Satija, Yatendra Kumar</style></author><author><style face="normal" font="default" size="100%">Mohanty, Sneha</style></author><author><style face="normal" font="default" size="100%">Khan, Md Tauseef</style></author><author><style face="normal" font="default" size="100%">Subudhi, Umakanta</style></author><author><style face="normal" font="default" size="100%">Sen, Pradip</style></author><author><style face="normal" font="default" size="100%">Kumar, Rashmi</style></author><author><style face="normal" font="default" size="100%">Bhardwaj, Anshu</style></author><author><style face="normal" font="default" size="100%">Gupta, Pawan</style></author><author><style face="normal" font="default" size="100%">Sharma, Deepak</style></author><author><style face="normal" font="default" size="100%">Tuli, Amit</style></author><author><style face="normal" font="default" size="100%">Chaudhuri, Saumya Ray</style></author><author><style face="normal" font="default" size="100%">Krishnamurthi, Srinivasan</style></author><author><style face="normal" font="default" size="100%">Prakash, L.</style></author><author><style face="normal" font="default" size="100%">Rao, V. Ch</style></author><author><style face="normal" font="default" size="100%">Singh, B. N.</style></author><author><style face="normal" font="default" size="100%">Chaurasiya, Arvindkumar</style></author><author><style face="normal" font="default" size="100%">Chaurasiya, Meera</style></author><author><style face="normal" font="default" size="100%">Bhadange, Mayuri</style></author><author><style face="normal" font="default" size="100%">Likhitkar, Bhagyashree</style></author><author><style face="normal" font="default" size="100%">Mohite, Sharada</style></author><author><style face="normal" font="default" size="100%">Patil, Yogita</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Mahesh</style></author><author><style face="normal" font="default" size="100%">Joshi, Rakesh</style></author><author><style face="normal" font="default" size="100%">Pandya, Vaibhav</style></author><author><style face="normal" font="default" size="100%">Mahajan, Sachin</style></author><author><style face="normal" font="default" size="100%">Patil, Amita</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Vare, Tejas</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author><author><style face="normal" font="default" size="100%">Giri, Ashok</style></author><author><style face="normal" font="default" size="100%">Mahajan, Sachin</style></author><author><style face="normal" font="default" size="100%">Paranjape, Shilpa</style></author><author><style face="normal" font="default" size="100%">Sastry, G. Narahari</style></author><author><style face="normal" font="default" size="100%">Kalita, Jatin</style></author><author><style face="normal" font="default" size="100%">Phukan, Tridip</style></author><author><style face="normal" font="default" size="100%">Manna, Prasenjit</style></author><author><style face="normal" font="default" size="100%">Romi, Wahengbam</style></author><author><style face="normal" font="default" size="100%">Bharali, Pankaj</style></author><author><style face="normal" font="default" size="100%">Ozah, Dibyajyoti</style></author><author><style face="normal" font="default" size="100%">Sahu, RaviKumar</style></author><author><style face="normal" font="default" size="100%">Dutta, Prachurjya</style></author><author><style face="normal" font="default" size="100%">Singh, Moirangthem Goutam</style></author><author><style face="normal" font="default" size="100%">Gogoi, Gayatri</style></author><author><style face="normal" font="default" size="100%">Tapadar, Yasmin Begam</style></author><author><style face="normal" font="default" size="100%">Babu, Elapavalooru V. S. S. K.</style></author><author><style face="normal" font="default" size="100%">Sukumaran, Rajeev K.</style></author><author><style face="normal" font="default" size="100%">Nair, Aishwarya R.</style></author><author><style face="normal" font="default" size="100%">Puthiyamadam, Anoop</style></author><author><style face="normal" font="default" size="100%">Valappil, Prajeesh Kooloth</style></author><author><style face="normal" font="default" size="100%">Prasannakumari, Adrash Velayudhan Pillai</style></author><author><style face="normal" font="default" size="100%">Chodankar, Kalpana</style></author><author><style face="normal" font="default" size="100%">Damare, Samir</style></author><author><style face="normal" font="default" size="100%">Agrawal, Ved Varun</style></author><author><style face="normal" font="default" size="100%">Chaudhary, Kumardeep</style></author><author><style face="normal" font="default" size="100%">Agrawal, Anurag</style></author><author><style face="normal" font="default" size="100%">Sengupta, Shantanu</style></author><author><style face="normal" font="default" size="100%">Dash, Debasis</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys</style></title><secondary-title><style face="normal" font="default" size="100%">Computers in Biology and Medicine</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">BBV152</style></keyword><keyword><style  face="normal" font="default" size="100%">Covaxin</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Ensemble methods</style></keyword><keyword><style  face="normal" font="default" size="100%">Infection</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUL</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">146</style></volume><pages><style face="normal" font="default" size="100%">105419</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	6.698&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Metagenomic mining of Indian river confluence reveal functional microbial community with lignocelluloytic potential</style></title><secondary-title><style face="normal" font="default" size="100%">3 Biotech</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">CAZymes</style></keyword><keyword><style  face="normal" font="default" size="100%">Confluence (Sangam)</style></keyword><keyword><style  face="normal" font="default" size="100%">Lignocellulosic</style></keyword><keyword><style  face="normal" font="default" size="100%">River Ganges</style></keyword><keyword><style  face="normal" font="default" size="100%">River Yamuna</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">132</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Microbial carbohydrate-active enzymes (CAZyme) can be harnessed for valorization of Lignocellulosic biomass (LCB) to value-added chemicals/products. The two Indian Rivers Ganges and the Yamuna having different origins and flow, face accumulation of carbon-rich substrates due to the discharge of wastewater from adjoining paper and pulp industries, which could potentially contribute to the natural enrichment of LCB utilizing genes, especially at their confluence. We analyzed CAZyme diversity in metagenomic datasets across the sacred confluence of the Rivers Ganges and Yamuna. Functional annotation using CAZyme database identified a total of 77,815 putative genes with functional domains involved in the catalysis of carbohydrate degradation or synthesis of glycosidic bonds. The metagenomic analysis detected similar to 41% CAZymes catalyzing the hydrolysis of lignocellulosic biomass polymers- cellulose, hemicellulose, lignin, and pectin. The Beta diversity analysis suggested higher CAZyme diversity at downstream region of the river confluence, which could be useful niche for culture-based studies. Taxonomic origin for CAZymes revealed the predominance of bacteria (97%), followed by archaea (1.67%), Eukaryota (0.63%), and viruses (0.7%). Metagenome guided CAZyme diversity of the microflora spanning across the confluence of Ganges-Yamuna River, could be harnessed for biomass and bioenergy applications.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">6</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	2.893&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Pramanik, Rinka</style></author><author><style face="normal" font="default" size="100%">Malik, Vinita</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Kadam, Pradnya</style></author><author><style face="normal" font="default" size="100%">Bhalerao, Unnati</style></author><author><style face="normal" font="default" size="100%">Tupekar, Manisha</style></author><author><style face="normal" font="default" size="100%">Deshpande, Dipti</style></author><author><style face="normal" font="default" size="100%">Shah, Priyanki</style></author><author><style face="normal" font="default" size="100%">Shashidhara, L. S.</style></author><author><style face="normal" font="default" size="100%">Boargaonkar, Radhika</style></author><author><style face="normal" font="default" size="100%">Patil, Dhawal</style></author><author><style face="normal" font="default" size="100%">Kale, Saurabh</style></author><author><style face="normal" font="default" size="100%">Bhalerao, Asim</style></author><author><style face="normal" font="default" size="100%">Jain, Nidhi</style></author><author><style face="normal" font="default" size="100%">Kamble, Sanjay</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Karmodiya, Krishanpal</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Science and Pollution Research </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bioinformatics pipeline</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Early warning</style></keyword><keyword><style  face="normal" font="default" size="100%">India</style></keyword><keyword><style  face="normal" font="default" size="100%">Next-generation sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Omicron</style></keyword><keyword><style  face="normal" font="default" size="100%">Public health</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">wastewater</style></keyword><keyword><style  face="normal" font="default" size="100%">Wastewater-based epidemiology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">118976-118988</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (similar to 28%), BA.1.X (1.0-72%), BA.2 (1.0-18%), BA.2.X (1.0-97.4%) BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-21.83%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">56</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	5.8&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Shah, Manan</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatio-temporal variation of the microbiome and resistome repertoire along an anthropogenically dynamic segment of the Ganges River, India</style></title><secondary-title><style face="normal" font="default" size="100%">Science of the Total Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antibiotics (ARGs)</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteriophages</style></keyword><keyword><style  face="normal" font="default" size="100%">Heavy metals (MRGs)</style></keyword><keyword><style  face="normal" font="default" size="100%">Metagenomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbiome</style></keyword><keyword><style  face="normal" font="default" size="100%">River Ganges</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAY</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">872</style></volume><pages><style face="normal" font="default" size="100%">162125</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Aquatic ecosystems are regarded as a hub of antibiotic and metal resistance genes. River Ganges is a unique riverine system in India with socio-cultural and economic significance. However, it remains underexplored for its microbiome and associated resistomes along its anthropogenically impacted course. The present study utilized a nanopore sequenc-ing approach to depict the microbial community structure in the sediments of the river Ganges harboring antibiotic and metal resistance genes (A/MRGs) in lower stretches known for anthropogenic impact. Comprehensive microbiome analyses revealed resistance genes against 23 different types of metals and 28 classes of antibiotics. The most dominant ARG category was multidrug resistance, while the most prevalent MRGs conferred resistance against copper and zinc. Seasonal differences dismally affected the microbiota of the Ganges. However, resistance genes for fosmidomycin and tetracycline varied with season ANOVA, p &amp;lt; 0.05. Interestingly, 333 and 334 ARG subtypes were observed at all the locations in pre-monsoon and post-monsoon, respectively. The taxa associated with the dominant ARGs and MRGs were Pseudomonas and Burkholderia, which are important nosocomial pathogens. A substantial phage diversity for pathogenic and putrefying bacteria at all locations attracts attention for its use to tackle the dissemination of antibiotic and metal-resistant bacteria. This study suggests the accumulation of antibiotics and metals as the driving force for the emergence of resistance genes and the affiliated bacteria trafficking them. The present metagenomic as-sessment highlights the need for comprehensive, long-term biological and physicochemical monitoring and mitigation strategies toward the contaminants associated with ARGs and MRGs in this nationally important river.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	10.753&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Bacteriophages: status quo and emerging trends toward one health approach</style></title><secondary-title><style face="normal" font="default" size="100%">Science of The Total Environment</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antimicrobial resistance (AMR)</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteriophages</style></keyword><keyword><style  face="normal" font="default" size="100%">One-health</style></keyword><keyword><style  face="normal" font="default" size="100%">Therapeutics commercialization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">908</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The alarming rise in antimicrobial resistance (AMR) among the drug-resistant pathogens has been attributed to the ESKAPEE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, Enterobacter sp., and Escherichia coli). Recently, these AMR microbes have become difficult to treat, as they have rendered the existing therapeutics ineffective. Thus, there is an urgent need for effective alternatives to lessen or eliminate the current infections and limit the spread of emerging diseases under the ``One Health'' framework. Bacteriophages (phages) are naturally occurring biological resources with extraordinary potential for biomedical, agriculture/food safety, environmental protection, and energy production. Specific unique properties of phages, such as their bactericidal activity, host specificity, potency, and biocompatibility, make them desirable candidates in therapeutics. The recent biotechnological advancement has broadened the repertoire of phage applications in nanoscience, material science, physical chemistry, and soft&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Review</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;9.8&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mahale, Mithil</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author><author><style face="normal" font="default" size="100%">Kodam, Kisan</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Harnessing the potential of Achromobacter sp. M1 to remediate heavy metals from wastewater: genomic insights and environmental applications</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Hazardous Materials</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Achromobacter sp. M1</style></keyword><keyword><style  face="normal" font="default" size="100%">Metal biosorption</style></keyword><keyword><style  face="normal" font="default" size="100%">Metal transporters</style></keyword><keyword><style  face="normal" font="default" size="100%">Toxic trio</style></keyword><keyword><style  face="normal" font="default" size="100%">Whole genome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">480</style></volume><pages><style face="normal" font="default" size="100%">136125</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Lead, mercury, and cadmium are classified as toxic under the toxic Substances' Priority List by CDC-ATSDR (Center for Disease Control-Agency for Toxic Substances and Disease Registry). This toxic trio is capable of disrupting the one-health harmony due to its human, animal, and environmental hazards. The present study aimed in removing the toxic trio within 24 h using a novel Achromobacter sp. M1. Atomic absorption spectroscopic evaluation for removal efficiency of Pb, Hg, and Cd by M1 was 68.8 +/- 0.9%, 82.7 +/- 1.9%, and 94.9 +/- 1.2 %, respectively, within 24 h. Lab-scale evaluation of strain M1 with wastewater showed the removal of the toxic trio together with the reduction in TSS from 140 to 118 ppm, BOD from 100 to 58 ppm, and COD from 381 to 222 ppm. Furthermore, strain M1 was capable of mitigating heavy metal stress and promoting plant growth, evidenced through chlorophyll, malondialdehyde, and proline estimation, together with the production of indole acetic acid (23.84 mu g/mL), siderophore (85 %), and solubilization of silica (39.66 mu g/mL). Whole genome sequencing revealed an ANI of 89 %, indicating a novel species of Achromobacter genus. A total of 23 putative genes for Cd, Hg, and Pb resistance were identified through genome mining.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	12.2&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Pawar, Ameya</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of a novel Tequatrovirus phage from pristine stretch of the Ganges River, India, in reducing bacterial load from sewage water</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Environmental Chemical Engineering</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antibiofouling</style></keyword><keyword><style  face="normal" font="default" size="100%">Biofilm</style></keyword><keyword><style  face="normal" font="default" size="100%">Coliform</style></keyword><keyword><style  face="normal" font="default" size="100%">Ganges</style></keyword><keyword><style  face="normal" font="default" size="100%">Green approach</style></keyword><keyword><style  face="normal" font="default" size="100%">Phages</style></keyword><keyword><style  face="normal" font="default" size="100%">wastewater</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><pages><style face="normal" font="default" size="100%">116315</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Effective treatment of wastewater (WW) and its reuse is necessary to meet certain sustainable development goals and a circular economy. Escherichia coli is one of the primary contaminants in the WW, and its extra-intestinal occurrence poses a considerable threat under one health. This study is the first report of a novel broadspectrum phage (&amp;amp; fcy;ERS-1) isolated from a pristine stretch of the Ganges River in the biocontrol of E. coli, resistant to 3rd-and 4th generation cephalosporins and aztreonam. This is the first report of a phage from the Tequatrovirus genus to infect P. aeruginosa. The &amp;amp; fcy;ERS-1 could reduce the abundance of E. coli cells by 8.22 log10 CFU/mL &amp;lt;= 24 hrs. Additionally, phi ERS-1 disrupted the biofilm of E. coli with a reduction of 3.88 log10 CFU/mL. Further, phi ERS-1 could inhibit biofilm by multiple strains of E. coli (ATCC 8739, 25922, 43888) and multiple generaincluding E. coli ATCC 8739, Shigella boydii ATCC 9207, P. aeruginosa (ATCC 9027). The phage phi ERS-1 reduced bacterial counts in raw WW by 2 log10 CFU/mL and 4 log10 CFU/mL reduction in coliform-enriched WW in &amp;lt;= 24 hours. Overall, this study suggests that phi ERS-1 could be used as an effective alternative to be combined with other treatments for improving the quality of WW disposal and environmental health by reducing the bacterial load.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	7.2&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Dandekar, Shraddha S.</style></author><author><style face="normal" font="default" size="100%">Thanikkal, Sinta</style></author><author><style face="normal" font="default" size="100%">Londhe, Arti</style></author><author><style face="normal" font="default" size="100%">Bhutada, Pankhudi</style></author><author><style face="normal" font="default" size="100%">Saha, Ujjayni</style></author><author><style face="normal" font="default" size="100%">Pawar, Shubhankar</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author><author><style face="normal" font="default" size="100%">Saroj, Sunil D.</style></author><author><style face="normal" font="default" size="100%">Koratkar, Santosh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Characterization of novel phages KPAФ1, KP149Ф1, and KP149Ф2 for lytic efficiency against clinical MDR Klebsiella pneumoniae infections</style></title><secondary-title><style face="normal" font="default" size="100%">Microbial Pathogenesis</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antimicrobial resistance</style></keyword><keyword><style  face="normal" font="default" size="100%">Bacteriophage</style></keyword><keyword><style  face="normal" font="default" size="100%">MDR-Klebsiella pneumoniae</style></keyword><keyword><style  face="normal" font="default" size="100%">Phage cocktail</style></keyword><keyword><style  face="normal" font="default" size="100%">Phage therapy</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">MAY</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">202</style></volume><pages><style face="normal" font="default" size="100%">107440</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Phage therapy offers a promising approach to the increasing antimicrobial resistance of Klebsiella pneumoniae. This study highlights three novel lytic bacteriophages-KPAc1, KP149c1, and KP149c2-targeting multidrugresistant (MDR) K. pneumoniae. These phages belong to the Myoviridae and Podoviridae family and demonstrate their efficacy and stability across a wide range of temperatures (up to 60 degrees C) and pH levels (pH 4 to 11). Genomic analysis reveals that they are free from virulence, toxicity, and antimicrobial resistance genes, making them promising candidates for therapeutic use. Among these phages, KPAc1 showed the highest lytic activity with a 26.15% lysis against MDR K. pneumoniae isolates. Additionally, a phage cocktail comprising all three phages improved lytic efficacy to 32.30%. This study also examined the antimicrobial resistance profiles of K. pneumoniae isolates, emphasizing the critical need for alternative treatments. By effectively targeting resistant strains, these phages offer a potential candidacy to be used as a viable alternative or a complementary antimicrobial agent to traditional antibiotics, opening up the possibility for advanced phage-based therapies. The promising results from this study pave the way for developing new treatments that could significantly improve patient care and outcomes from the growing issue of resistant bacterial infections.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.3&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Kumar, Shubham</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Khairnar, Krishna</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Deciphering the comprehensive microbiome of glacier-fed Ganges and functional aspects: implications for one health</style></title><secondary-title><style face="normal" font="default" size="100%">Microbiology Spectrum</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bacteriophages</style></keyword><keyword><style  face="normal" font="default" size="100%">glacier-fed-Ganges</style></keyword><keyword><style  face="normal" font="default" size="100%">Microbiome</style></keyword><keyword><style  face="normal" font="default" size="100%">Secondary metabolites</style></keyword><keyword><style  face="normal" font="default" size="100%">special properties</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">AUG</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">13</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Glacier-fed rivers are significant ecological components of the river catchments, yet their microbial diversity and the associated antimicrobial potential remain underexplored. The Ganges is a glacier-fed river of immense cultural, religious, and ecological significance that supports over 400 million people downstream, providing essential water for agriculture, industry, and daily use. Despite its importance, the microbial community composition and antimicrobial potential, across its relatively pristine origin, remain largely underexplored. One possible explanation for this could be the lower microbial load in the upstream glacier-fed region, which likely results in a reduced DNA yield, insufficient for whole-metagenome sequencing, in contrast to the more biologically diverse and nutrient-rich lower reaches. In this study, we developed an efficient DNA extraction and amplification method using low-input DNA to sequence the microbiome from sediments of the glacier-fed Ganges River in pre-monsoon and post-monsoon over 2 years. Taxonomic and functional diversity of bacterial and viral (phage) communities were analyzed, together with the seasonal variations in their composition. Significant differences in microbial communities were observed in response to seasonal shifts (P &amp;lt; 0.05). During the dry season, Proteobacteria and Actinobacteria were predominant, while Bacteroidetes and Firmicutes were abundant post-monsoon (P &amp;lt; 0.05). The microbiome harbors potential for the biosynthesis of streptomycin, phenylpropanoid, penicillin, and cephalosporins. Bacteriophages from Podoviridae, Myoviridae, and Siphoviridae showed lytic potential against putrefying and pathogenic bacteria. This first comprehensive study on the glacier-fed Ganges River highlights significant seasonal shifts in microbial diversity. The initial insights into the functional profile of the bacterial and phage diversity offer opportunities to explore various natural compounds and enzymes to tackle antimicrobial resistance under the one-health canopy.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	3.8&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Mahajan, Vaishnavi</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genome mining, probiotic characteristics, and in-silico safety assessment of Limosilactobacillus fermentum AV7 isolated from Avocado fruit pulp</style></title><secondary-title><style face="normal" font="default" size="100%">LWT-Food Science and Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">216</style></volume><pages><style face="normal" font="default" size="100%">117231</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	Limosilactobacillus fermentum holds substantial promise for probiotic applications in human health and various industries. Herein, we present the first report of L. fermentum AV7 isolated from the avocado pulp and assessed for its probiotic potentials and safety through probiogenomic analyses and In-vitro probiotic assays. The genomic insights revealed genes associated with acid and bile tolerance and antimicrobial peptide production, highlighting the probiotic potential of the strain AV7. Notably, the in-silico safety analysis showed that the genome of L.fermentum AV7 is devoid of plasmid and lacks any putative antibiotic resistance or pathogenic traits, ensuring its safety for human consumption. Beyond the genomic and in-silico analysis, we also aimed to evaluate the probiotic potentials of AV7 strain using in- vitro tests for acid, gastric juice, intestinal fluid and bile tolerance, resilience to osmotic stress, followed by auto-aggregation and co-aggregation assays with Escherichia coli ATCC 8739. The data obtained through in-vitro studies confirmed the efficacy of L.fermentum AV7 as a probiotic strain, and positions it as a potent probiotic candidate, expanding the scope of probiotic research. Our study investigates avocados, a nutrient-dense fruit, as a novel source of beneficial lactic acid bacteria, thereby attracting innovative dietary and therapeutic applications. By introducing L .fermentum AV7 into the probiotic landscape, we pave the way for new health benefits from this beloved fruit. The research not only adds a new dimension to avocado utilization but also contributes to the relatively unexplored field of isolating beneficial bacteria from avocados, promising exciting advancements in human health.&lt;/p&gt;
</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	6.0&lt;/p&gt;
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pramanik, Rinka</style></author><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Malik, Vinita</style></author><author><style face="normal" font="default" size="100%">Nannaware, Kiran</style></author><author><style face="normal" font="default" size="100%">Matra, Sejal</style></author><author><style face="normal" font="default" size="100%">Joshi, Sai</style></author><author><style face="normal" font="default" size="100%">Kumar, Shubham</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakesh Kumar</style></author><author><style face="normal" font="default" size="100%">Shah, Priyanki</style></author><author><style face="normal" font="default" size="100%">Shashidhara, LS</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Karmodiya, Krishanpal</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Long-term genomic surveillance of SARS-CoV-2 in campus wastewater depicts lineage trends and public health implications during and after omicron waves</style></title><secondary-title><style face="normal" font="default" size="100%">Environment &amp; Health</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2025</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">908–919</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	&lt;span style=&quot;color: rgb(21, 21, 21); font-family: Roboto, arial, sans-serif; font-size: 16px;&quot;&gt;SARS-CoV-2 transmission and detection on academic campuses in low- to middle-income countries has not been explored. The present study explored wastewater surveillance of SARS-CoV-2 in a campus setting in Pune, Maharashtra, India, offering insights into variant-specific trends and their correlation with clinical cases over a 2.5 year period from November 2021 to April 2024. We collected 242 wastewater samples from the campus sewershed and processed them to extract RNA and perform RT-qPCR and sequencing, followed by lineage assignment using the LCS tool. Early signals of different SARS-CoV-2 variants, such as BA.2.X, JN.1.X, and KP.2.X, were detected in wastewater prior to its first clinical report in Maharashtra, India. Wastewater viral load strongly correlated with clinical cases during the Omicron phase (ρ = 0.73–0.81) compared to the post-Omicron phase (ρ = −0.06 to 0.31). This study also highlights that alerts and warnings issued on the basis of wastewater viral hikes have proven instrumental in preventing outbreaks of SARS-CoV-2 variants on campus. However, downgrading COVID-19 from pandemic status by the WHO resulted in a subsequent decrease in public vigilance, changing the viral dynamic in the last phase of the study. This study showcases the utility of wastewater surveillance in a campus setting as an early warning system and understands the interplay of public health policy effects in viral dynamics within controlled ecosystems, such as campuses or offices.&lt;/span&gt;&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">8</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;
	Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	6.3&lt;/p&gt;
</style></custom4></record></records></xml>