Displaying publications 21 - 22 of 22 in total

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  1. Fulltext Delineating the Plausible Molecular Vaccine Candidates and Drug Targets of Multidrug-Resistant Acinetobacter baumannii
    Mujawar S, Mishra R, Pawar S, Gatherer D, Lahiri C
    Front Cell Infect Microbiol, 2019;9:203.
    PMID: 31281799 DOI: 10.3389/fcimb.2019.00203
    Nosocomial infections have become alarming with the increase of multidrug-resistant bacterial strains of Acinetobacter baumannii. Being the causative agent in ~80% of the cases, these pathogenic gram-negative species could be deadly for hospitalized patients, especially in intensive care units utilizing ventilators, urinary catheters, and nasogastric tubes. Primarily infecting an immuno-compromised system, they are resistant to most antibiotics and are the root cause of various types of opportunistic infections including but not limited to septicemia, endocarditis, meningitis, pneumonia, skin, and wound sepsis and even urinary tract infections. Conventional experimental methods including typing, computational methods encompassing comparative genomics, and combined methods of reverse vaccinology and proteomics had been proposed to differentiate and develop vaccines and/or drugs for several outbreak strains. However, identifying proteins suitable enough to be posed as drug targets and/or molecular vaccines against the multidrug-resistant pathogenic bacterial strains has probably remained an open issue to address. In these cases of novel protein identification, the targets either are uncharacterized or have been unable to confer the most coveted protection either in the form of molecular vaccine candidates or as drug targets. Here, we report a strategic approach with the 3,766 proteins from the whole genome of A. baumannii ATCC19606 (AB) to rationally identify plausible candidates and propose them as future molecular vaccine candidates and/or drug targets. Essentially, we started with mapping the vaccine candidates (VaC) and virulence factors (ViF) of A. baumannii strain AYE onto strain ATCC19606 to identify them in the latter. We move on to build small networks of VaC and ViF to conceptualize their position in the network space of the whole genomic protein interactome (GPIN) and rationalize their candidature for drugs and/or molecular vaccines. To this end, we propose new sets of known proteins unearthed from interactome built using key factors, KeF, potent enough to compete with VaC and ViF. Our method is the first of its kind to propose, albeit theoretically, a rational approach to identify crucial proteins and pose them for candidates of vaccines and/or drugs effective enough to combat the deadly pathogenic threats of A. baumannii.
    Matched MeSH terms: Drug Resistance, Multiple, Bacterial/drug effects*
  2. Fulltext The burden of typhoid fever in Klang Valley, Malaysia, 2011-2015
    Muhammad EN, Abdul Mutalip MH, Hasim MH, Paiwai F, Pan S, Mahmud MAF, et al.
    BMC Infect Dis, 2020 Nov 16;20(1):843.
    PMID: 33198646 DOI: 10.1186/s12879-020-05500-x
    BACKGROUND: Typhoid fever causes global morbidity and mortality and is a significant health burden, particularly in low- and middle-income countries. The direct fecal-oral route is the main transmission mode, but indirect environmental transmission could occur, particularly in urban settings. This study aimed to investigate the burden and trend of typhoid fever, reporting the coverage system between government and private practice and pattern of multidrug-resistant (MDR) typhoid cases in the urban Klang Valley area from 2011 to 2015.

    METHODS: The data from a cross-sectional study retrieved from the e-Notifikasi System, a national reporting system for communicable diseases provided by the Disease Control Division, Ministry of Health Malaysia and secondary data of all the typhoid cases were obtained from the public and private hospitals and laboratories in Klang Valley. Descriptive analysis was performed to examine the sociodemographic characteristics, spatial mapping was conducted to examine trends, and the crude incidence rates of confirmed typhoid cases and percentage of reporting coverage were calculated. Significant differences between MDR and non-MDR Salmonella typhi were determined in the patient's sociodemographic characteristics, which were analyzed using χ2 test. P values

    Matched MeSH terms: Drug Resistance, Multiple, Bacterial/drug effects
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