01698nas a2200217   4500008004100000022001400041245011300055210006900168260009500237300001200332490000800344520091200352653001201264653001201276653001301288653000901301653000901310100001301319700002401332856012401356       2010                        eng d  a0012-160600aInteraction between ataxin-2 binding protein 1 and cubitus-interruptus during wing development in drosophila0 aInteraction between ataxin2 binding protein 1 and cubitusinterru  a525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USAbACADEMIC PRESS INC ELSEVIER SCIENCEcMAY  a389-3990 v3413 a<p>Animal growth and development is dependent on reiterative use of key signaling pathways such as Hedgehog (Hh) pathway. It is widely believed that Cubitus-interruptus (Ci) mediates all functions of Hh pathway. Here we report that CG32062, the Drosophila homologue of Ataxin-2 Binding Protein 1 (dA2BP1), functions as a cofactor of Ci to specify intervein region between L3 and L4 veins of the adult wing. Specifically, Ci-mediated transactivation of knot/collier (kn) in this region of the developing wing imaginal disc is dependent on dA2BP1 function. Protein interaction studies and chromatin-immunoprecipiation experiments suggest that Ci helps dA2BP1 to bind kn promoter, which in turn may help Ci to activate kn expression. These results suggest a mechanism by which Ci may activate targets such as kn, which do not have classical Ci/Gli-binding sites. (C) 2010 Elsevier Inc. All rights reserved.</p>10aCG3206210aCollier10aHedgehog10aKnot10aSCA21 aUsha, N.1 aShashidhara, L., S.  uhttps://library.ncl.res.in/content/interaction-between-ataxin-2-binding-protein-1-and-cubitus-interruptus-during-wing-003254nas a2200493   4500008004100000022001400041245016200055210006900217260000800286300001800294490000700312520171400319653002802033653001302061653001802074653001002092653003102102653001202133653001802145653001502163653001502178653003402193100001802227700002002245700001802265700002302283700001902306700001902325700002102344700002102365700002102386700001902407700002402426700002502450700001802475700001802493700001902511700001602530700001902546700001902565700002602584700001902610856013102629       2023                        eng d  a0944-134400aGenomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India0 aGenomic surveillance reveals early detection and transition of d  cDEC  a118976-1189880 v303 a<p>
	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.</p>
10aBioinformatics pipeline10aCOVID-1910aEarly warning10aIndia10aNext-generation sequencing10aOmicron10aPublic health10aSARS-CoV-210awastewater10aWastewater-based epidemiology1 aRajput, Vinay1 aPramanik, Rinka1 aMalik, Vinita1 aYadav, Rakeshkumar1 aSamson, Rachel1 aKadam, Pradnya1 aBhalerao, Unnati1 aTupekar, Manisha1 aDeshpande, Dipti1 aShah, Priyanki1 aShashidhara, L., S.1 aBoargaonkar, Radhika1 aPatil, Dhawal1 aKale, Saurabh1 aBhalerao, Asim1 aJain, Nidhi1 aKamble, Sanjay1 aDastager, Syed1 aKarmodiya, Krishanpal1 aDharne, Mahesh  uhttps://library.ncl.res.in/content/genomic-surveillance-reveals-early-detection-and-transition-delta-omicron-lineages-sars-cov04148nas a2200589   4500008004100000022001400041245012400055210006900179260000800248300001400256490000700270520236200277653001302639653001002652653001202662653003602674653002302710653003402733100002102767700001702788700002102805700002102826700002102847700001902868700001602887700002302903700001702926700002702943700001902970700001902989700002103008700001803029700002003047700001903067700001903086700002103105700002203126700001903148700002203167700001903189700001803208700001903226700002303245700001803268700002003286700002403306700002603330700002803356700002103384700002603405856012703431       2023                        eng d  a1876-034100aTale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India0 aTale of two waves Delineating diverse genomic and transmission l  cAUG  a1290-13000 v163 a<p>
	Background: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.Methods: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a ``band of five'' outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).Results: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. Conclusions: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implica-tions for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.&amp; COPY; 2023 Published by Elsevier Ltd on behalf of King Saud Bin Abdulaziz University for Health Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).</p>
10aCOVID-1910aDelta10aOmicron10aSARS-CoV-2 genomic surveillance10aVariant of concern10aWhole Genome Sequencing (WGS)1 aNiveditha, Divya1 aKhan, Soumen1 aKhilari, Ajinkya1 aNadkarni, Sanica1 aBhalerao, Unnati1 aKadam, Pradnya1 aYadav, Ritu1 aKanekar, Jugal, B.1 aShah, Nikita1 aLikhitkar, Bhagyashree1 aSawant, Rutuja1 aThakur, Shikha1 aTupekar, Manisha1 aNagar, Dhriti1 aRao, Anjani, G.1 aJagtap, Rutuja1 aJogi, Shraddha1 aBelekar, Madhuri1 aPathak, Maitreyee1 aShah, Priyanki1 aRanade, Shatakshi1 aPhadke, Nikhil1 aDas, Rashmita1 aJoshi, Suvarna1 aKaryakarte, Rajesh1 aGhose, Aurnab1 aKadoo, Narendra1 aShashidhara, L., S.1 aMonteiro, Joy, Merwin1 aShanmugam, Dhanasekaran1 aRaghunathan, Anu1 aKarmodiya, Krishanpal  uhttps://library.ncl.res.in/content/tale-two-waves-delineating-diverse-genomic-and-transmission-landscapes-driving-covid-1901051nas a2200313   4500008004100000245011900041210006900160260000800229100001800237700001800255700002000273700002100293700001500314700001700329700001900346700002300365700002100388700001900409700002100428700002200449700001900471700001600490700001900506700001900525700002400544700002300568700001900591856012700610       2024                        eng d00aEarly detection of KP.2 SARS-CoV-2 variant using wastewater-based genomic surveillance in Pune, Maharashtra, India0 aEarly detection of KP2 SARSCoV2 variant using wastewaterbased ge  cJUL1 aRajput, Vinay1 aDas, Rashmita1 aPramanik, Rinka1 aNannaware, Kiran1 aSushma, Y.1 aTaji, Nyabom1 aRajput, Vishal1 aRajkhowa, Riyakshi1 aPacharne, Poonam1 aShah, Priyanki1 aGogate, Niharika1 aSangwar, Poornima1 aBhalerao, Asim1 aJain, Nidhi1 aKamble, Sanjay1 aDastager, Syed1 aShashidhara, L., S.1 aKaryakarte, Rajesh1 aDharne, Mahesh  uhttps://library.ncl.res.in/content/early-detection-kp2-sars-cov-2-variant-using-wastewater-based-genomic-surveillance-pune06441nas a2200865   4500008004100000245020100041210007000242260000800312490000700320520376100327100003104088700002604119700001804145700001804163700002504181700002604206700002004232700001904252700001604271700002104287700002704308700001904335700002204354700001904376700002604395700001904421700002004440700002104460700002004481700002004501700002304521700002404544700002204568700002504590700002704615700001804642700002004660700002104680700001604701700002004717700001504737700002904752700002104781700002104802700001904823700002704842700002904869700001804898700001804916700002604934700003204960700001904992700001905011700002005030700002305050700001605073700002205089700001905111700002005130700001605150700003105166700001605197700001805213700002505231700002105256700001505277700001905292700002005311700002405331700002805355700001705383700002005400700002005420856013505440       2024                        eng d00aImmunogenicity of SARS-CoV-2 vaccines BBV152 (COVAXIN®) and ChAdOx1 nCoV-19 (COVISHIELD™) in seronegative and seropositive individuals in India: a multicentre, nonrandomised observational study0 aImmunogenicity of SARSCoV2 vaccines BBV152 COVAXIN® and ChAdOx1   cMAR0 v223 a<p style="box-sizing: inherit; line-height: 1.5; margin: 1.2rem 0px; color: rgb(33, 33, 33); font-family: BlinkMacSystemFont, -apple-system, &quot;Segoe UI&quot;, Roboto, Oxygen, Ubuntu, Cantarell, &quot;Fira Sans&quot;, &quot;Droid Sans&quot;, &quot;Helvetica Neue&quot;, sans-serif; font-size: 16px;">
	<strong class="sub-title" style="box-sizing: inherit;">Background:&nbsp;</strong>There are limited global data on head-to-head comparisons of vaccine platforms assessing both humoral and cellular immune responses, stratified by pre-vaccination serostatus. The COVID-19 vaccination drive for the Indian population in the age group 18-45 years began in April 2021 when seropositivity rates in the general population were rising due to the delta wave of COVID-19 pandemic during April-May 2021.</p>
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	<strong class="sub-title" style="box-sizing: inherit;">Methods:&nbsp;</strong>Between June 30, 2021, and Jan 28, 2022, we enrolled 691 participants in the age group 18-45 years across four clinical sites in India. In this non-randomised and laboratory blinded study, participants received either two doses of Covaxin® (4 weeks apart) or two doses of Covishield™ (12 weeks apart) as per the national vaccination policy. The primary outcome was the seroconversion rate and the geometric mean titre (GMT) of antibodies against the SARS-CoV-2 spike and nucleocapsid proteins post two doses. The secondary outcome was the frequency of cellular immune responses pre- and post-vaccination.</p>
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	<strong class="sub-title" style="box-sizing: inherit;">Findings:&nbsp;</strong>When compared to pre-vaccination baseline, both vaccines elicited statistically significant seroconversion and binding antibody levels in both seronegative and seropositive individuals. In the per-protocol cohort, Covishield™ elicited higher antibody responses than Covaxin® as measured by seroconversion rate (98.3% vs 74.4%, p &lt; 0.0001 in seronegative individuals; 91.7% vs 66.9%, p &lt; 0.0001 in seropositive individuals) as well as by anti-spike antibody levels against the ancestral strain (GMT 1272.1 vs 75.4 binding antibody units/ml [BAU/ml], p &lt; 0.0001 in seronegative individuals; 2089.07 vs 585.7 BAU/ml, p &lt; 0.0001 in seropositive individuals). As participants at all clinical sites were not recruited at the same time, site-specific immunogenicity was impacted by the timing of vaccination relative to the delta and omicron waves. Surrogate neutralising antibody responses against variants-of-concern including delta and omicron was higher in Covishield™ recipients than in Covaxin® recipients; and in seropositive than in seronegative individuals after both vaccination and asymptomatic infection (omicron variant). T cell responses are reported from only one of the four site cohorts where the vaccination schedule preceded the omicron wave. In seronegative individuals, Covishield™ elicited both CD4+ and CD8+ spike-specific cytokine-producing T cells whereas Covaxin® elicited mainly CD4+ spike-specific T cells. Neither vaccine showed significant post-vaccination expansion of spike-specific T cells in seropositive individuals.</p>
1 aAsokan, Mangaiarkarasi, S.1 aJoan, Roshni, Florina1 aBabji, Sudhir1 aDayma, Girish1 aNadukkandy, Prajitha1 aSubrahmanyam, Vinutha1 aPandey, Archana1 aMalagi, Girish1 aArya, Pooja1 aMahajan, Vibhuti1 aBhavikatti, Jayateerth1 aPawar, Ketakee1 aThorat, Aishwarya1 aShah, Priyanki1 aGoud, Ramakrishna, B.1 aRoy, Bishnudeo1 aRajukutty, Shon1 aImmanuel, Sushil1 aAgarwal, Dhiraj1 aSaha, Sankhanil1 aShivaraj, Akshatha1 aPanikulam, Patricia1 aShome, Rajeshwari1 aGulzar, Shah-E-Jahan1 aSharma, Anusmrithi, U.1 aNaik, Ajinkya1 aTalashi, Shruti1 aBelekar, Madhuri1 aYadav, Ritu1 aKhude, Poornima1 aV, Mamatha1 aShivalingaiah, Sudarshan1 aDeshmukh, Urmila1 aBhise, Chinmayee1 aJoshi, Manjiri1 aInbaraj, Leeberk, Raja1 aChandrasingh, Sindhulina1 aGhose, Aurnab1 aJamora, Colin1 aKarumbati, Anandi, S.1 aSundaramurthy, Varadharajan1 aJohnson, Avita1 aRamesh, Naveen1 aChetan, Nirutha1 aParthiban, Chaitra1 aAhmed, Asma1 aRakshit, Srabanti1 aAdiga, Vasista1 aD'souza, George1 aRale, Vinay1 aGeorge, Carolin, Elizabeth1 aJohn, Jacob1 aKawade, Anand1 aChaturvedi, Akanksha1 aRaghunathan, Anu1 aDias, Mary1 aBhosale, Anand1 aRaghu, Padinjat1 aShashidhara, L., S.1 ayakarnam, Annapurna, V.1 aBal, Vineeta1 aKang, Gagandeep1 aMayor, Satyajit  uhttps://library.ncl.res.in/content/immunogenicity-sars-cov-2-vaccines-bbv152-covaxin%C2%AE-and-chadox1-ncov-19-covishield%E2%84%A202225nas a2200373   4500008004100000022001400041245018900055210006900244260000800313300000600321490000700327520095400334653001601288653004301304653002401347653001501371653003401386100002001420700002101440700001801461700001901479700002301498700002101521700002401542700002501566700001801591700001801609700001901627700001601646700001901662700001901681700001901700856013201719       2025                        eng d  a1867-033400aMonitoring influenza A (H1N1, H3N2), RSV, and SARS-CoV-2 using wastewater-based epidemiology: A 2-year longitudinal study in an Indian megacity covering omicron and post-omicron phases0 aMonitoring influenza A H1N1 H3N2 RSV and SARSCoV2 using wastewat  cMAR  a30 v173 a<p>
	{The bourgeoning field of wastewater-based epidemiology (WBE) for the surveillance of several respiratory viruses which includes Influenza A, H1N1pdm09, H3N2, respiratory syncytial viruses (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of interest for public health concerns. However, there are few long-term monitoring studies globally. In this study, respiratory viruses were detected and quantified from 11 sewer sheds by utilizing reverse transcription-quantitative polymerase chain reaction analysis in Pune city, India, from Jan 2022 to Dec 2023. The RNA fragments of respiratory viruses were detected in sewage samples before clinical cases were reported, underscoring the potential of WBE for early detection and monitoring within the population. The Spearman correlation of wastewater viral copies was positively and significantly correlated with the clinically positive case of H1N1pdm09 (rho = 0.55</p>
10aInfluenza A10aQuantitative reverse transcription-PCR10aRespiratory viruses10aSARS-CoV-210aWastewater-based epidemiology1 aPramanik, Rinka1 aNannaware, Kiran1 aMalik, Vinita1 aShah, Priyanki1 aSangewar, Poornima1 aGogate, Niharika1 aShashidhara, L., S.1 aBoargaonkar, Radhika1 aPatil, Dhawal1 aKale, Saurabh1 aBhalerao, Asim1 aJain, Nidhi1 aKamble, Sanjay1 aDastager, Syed1 aDharne, Mahesh  uhttps://library.ncl.res.in/content/monitoring-influenza-h1n1-h3n2-rsv-and-sars-cov-2-using-wastewater-based-epidemiology-2-year