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Background & Aims:  Adverse Drug Reactions (ADRs) are common with drug treatment. They can be collected by active and passive methods. The aim of the study was to compare active and passive ADR monitoring methods in terms of yield and lag period in category I tuberculosis patients.
Materials & Methods: A prospective observational analytical study was done in a directly observed therapy short-course (DOTS) center and pharmacovigilance center of SMS hospital, Jaipur, Rajasthan, India from 1.1.2019 to 31.12.2019. A total of 303 category I tubercular patients on DOTS were divided into groups A (150) and B (153). Group A (active) patients were interviewed personally or telephonically for ADRs on 0,3,7,15,30, 90,180 days of therapy as per pre-structured & pre-validated questionnaire. Group B (passive) patients were asked to report ADRs themselves to pharmacovigilance center directly or through a drop box. Collected ADRs were compared statistically using software Minitab 14, Pennsylvania, USA.
Results: The yield of ADRs in active method was 4.5 times higher than the passive method. GIT related ADRs were similar in both groups, cutaneous were higher in active and CNS concerned were higher in passive method. However, consistency of ADR reporting was more in passive method. Mean lag period between onset and reporting of ADRs by active and passive methods were 5.72 and 22.4 days, respectively.
Conclusion: Active method initially and numerically facilitates ADR  reporting together with decreased lag period  but passive method gives consistent yield in chronic diseases like TB, hence, an integrated approach to identify and manage ADRs will be most beneficial for patients.

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Background & Aims: Chronic obstructive pulmonary disease (COPD) is an important cause of mortality and morbidity globally. COPD, if associated with multiple comorbidities, has a greater impact on treatment outcome and hospital stay, hence effective control of COPD is crucial for enhancing quality of life. Our study assesses the effect of comorbidities on management outcomes in acute exacerbations of COPD patients.
Materials & Methods: An analytical cross-sectional study was planned on 630 patients. Patients with acute exacerbations of COPD who were admitted to pulmonary ward and ICU were enrolled in the study. Data analysis was done using MS Excel and SPSS version 21.0. Unpaired students’t-test was used and p < 0.05 was taken to be statistically significant.
Results: 61.9% of patients had at least one associated comorbidity e.g. CAD (37.2%), hypertension (28.2%), diabetes mellitus (24.3%), and CVD (10.3%). We found that acute exacerbation of COPD patients with comorbidities had prolonged hospital stay, greater ICU admissions, and need for invasive ventilation as compared to those without comorbidities. Presence of comorbidities with COPD was significantly associated with duration of hospital stay.
Conclusion: Comorbidities associated with acute exacerbations of COPD increase the hospital stay, need for ICU admission and more invasive ventilation, and reduce the impact of treatments.

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Background & Aims: There is inadequate information available about the genomics and proteomics characterization of SARS-CoV-2 isolates reported from India and other part of the globe. This characterization is important for the in-silico drug designing, as there are no approved medications available to treat SARS-CoV-2 infection. The present study based on the characterization of SARS-CoV-2 (MZ558159) isolate reported from India using homology modeling, validation, and in silico drug designing methods.
Materials & Methods: Genome sequence of SARS-CoV-2 (MZ558159) was retrieved from NCBI, and four protein sequences e.g., QXN18496, QXN18498, QXN18504, and QXN18497 were selected for the homology modeling, validation, and in silico drug designing. SWISS-MODEL and UCLA-DOE server were used for homology modeling. Validation for structure model performed using PROCHECK and molecular docking using MCULE-1-Click server.
Results: The surface glycoprotein (QXN18496) model corresponding to probability conformation with 93.6%, envelope protein (QXN18498) with 88.9%, nucleocapsid phosphoprotein (QXN18504) with 93.6%, and ORF3a protein (QXN18497) with 91.8% residues in core section of φ-ψ plot that specifies accuracy of prediction models. The corresponding ProSA Z-score score -12.67, -0.01, -4.4, and -2.87 indicates the good quality of the models. Molecular dynamic simulation and docking studies revealed that inhibitor binds effectively at the SARS-CoV-2 (MZ558159) proteins. Predicted inhibitor 2-acetamido-2-deoxy-beta-D-glucopyranose exhibited effective binding affinity against surface glycoprotein (QXN18496).
Conclusion: The results of this study established inhibitor 2-Acetamido-2-deoxy-beta-D-glucopyranose as valuable lead molecule with great potential for surface glycoprotein (QXN18496).
 

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Background & Aims:  The active site of RdRp-CoV is highly conserved, with two successive and surface-accessible aspartates in a beta-turn structure. Antiviral drugs Remdesivir, Galidesivir, Tenofovir, Sofosbuvir, and Ribavirin are known as inhibitors of RdRps, while lopinavir and rotinavir are known inhibitors of main protease (MPro) of coronavirus. The aim of the present study was to in silico test of the effectiveness of anti-polymerase drugs against SARS-CoV-2 RdRp, including 5 FDA-approved antiviral medications.
Materials & Methods:  RdRp-CoV (nsp12) plays an important role in virus replication; therefore, it serves as a target to development of antiviral drugs. In this study, the RdRp is modeled, validated, and then targeted using different anti-polymerase drugs that approved for use against various viruses.
Results:  The five approved drugs (Galidesivir, Remdesivir, Tenofovir, Sofosbuvir, and Ribavirin) were able to bind the SARS-CoV-2 RdRp with binding energies of 42.6, 1.7, 38.4, -1.4, and -3.9 kcal/mol, respectively. For the drug ribavirin, the only interactions established upon docking were the 11 H-bonds with F165, N459, R624, P677, N791, L460, N791, T462, N628, and T462 of the SARS-CoV-2 RdRp.
Conclusion:  The results suggest the effectiveness of Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir as potent drugs against RdRp-CoV since they tightly bind to RdRp. The availability of FDA-approved anti-RdRp drugs can help treat the infection of new variant of SARS-CoV-2 strain specifically.

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Background & Aims:  Citrobacter, a member of the Enterobacteriaceae family known to be a normal intestinal flora and an opportunistic pathogen is now increasingly found to cause a variety of infections in community as well as hospital settings. It was initially considered a low virulence pathogen but is now found to cause multi-drug resistant infections with high morbidity and mortality. To determine the prevalence of infections caused by Citrobacter spp. and theirAntibiotic sensitivity pattern.
Material & Methods: A Laboratory records-based Cross-sectional study was undertaken retrospectively wherein the laboratory data about 50 Citrobacter spp. isolates obtained from 1628 clinical samples processed over 18 months were retrieved and analyzed at Department of Microbiology, Government Medical College-Datia, Central India in January 2024.
Result: Out of the 1628 samples processed, significant bacterial growth was reported in 770 samples out of which 50 were found to be positive for Citrobacter spp. (6.4%). Isolation rate for Citrobacter spp. was reported to be 3.1 %.The majority of isolates were obtained from Urine (49%) and pus (45%) samples with C. koseri being dominant in urine and C. freundii in pus. Amongst these isolates, 52% were C.koseri, 46% were C.freundii and 4% were other species.
Conclusion: The findings of the study conducted in January 2024 at Datia (Madhya Pradesh) indicate a change in susceptibility trends of emerging pathogens like Citrobacter spp. exhibiting resistance to routinely prescribed antimicrobials, stressing the need for an appropriate action plan involving periodic surveillance, antimicrobial stewardship, and strict implementation of infection control practices.