Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1070536 | ENA |
REPOSITORIES: ENA
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Project description:The spread of carbapenemase-producing Enterobacterales (CPE) is emerging as a significant clinical concern in tertiary hospitals and in particular, long-term care facilities with deficiencies in infection control. This study aims to evaluate an advanced matrix-assisted laser desorption/ionization mass spectrometry (A-MALDI) method for the identification of carbapenemases and further discrimination of their subtypes in clinical isolates. The A-MALDI method was employed to detect CPE target proteins. Enhancements were made to improve detectability and mass accuracy through the optimization of MALDI-TOF settings and internal mass calibration. A total of 581 clinical isolates were analyzed, including 469 CPE isolates (388 KPC, 51 NDM, 40 OXA, and 2 GES) and 112 carbapenemase-negative isolates. Clinical evaluation of the A-MALDI demonstrated 100% accuracy and precision in identifying all the collected CPE isolates. Additionally, A-MALDI successfully discriminated individual carbapenemase subtypes (KPC-2 or KPC-3/4; OXA-48 or OXA-181 or OXA-232; GES-5 or GES-24) and also differentiated co-producing carbapenemase strains (KPC & NDM; KPC & OXA; KPC & GES; NDM & OXA), attributed to its high mass accuracy and simultaneous detection capability. A-MALDI is considered a valuable diagnostic tool for accurately identifying CPE and carbapenemase’s subtypes in clinical isolates. It may also aid in selecting appropriate antibiotics for each carbapenemase subtype. Ultimately, we expect that the A-MALDI method will contribute to preventing the spread of antibiotic resistance and improving human public health.
2024-11-26 | PXD058284 | Pride
Project description:The spread of carbapenemase-producing Enterobacterales (CPE) is emerging as a significant clinical concern in tertiary hospitals and in particular, long-term care facilities with deficiencies in infection control. This study aims to evaluate an advanced matrix-assisted laser desorption/ionization mass spectrometry (A-MALDI) method for the identification of carbapenemases and further discrimination of their subtypes in clinical isolates. The A-MALDI method was employed to detect CPE target proteins. Enhancements were made to improve detectability and mass accuracy through the optimization of MALDI-TOF settings and internal mass calibration. A total of 581 clinical isolates were analyzed, including 469 CPE isolates (388 KPC, 51 NDM, 40 OXA, and 2 GES) and 112 carbapenemase-negative isolates. Clinical evaluation of the A-MALDI demonstrated 100% accuracy and precision in identifying all the collected CPE isolates. Additionally, A-MALDI successfully discriminated individual carbapenemase subtypes (KPC-2 or KPC-3/4; OXA-48 or OXA-181 or OXA-232; GES-5 or GES-24) and also differentiated co-producing carbapenemase strains (KPC & NDM; KPC & OXA; KPC & GES; NDM & OXA), attributed to its high mass accuracy and simultaneous detection capability. A-MALDI is considered a valuable diagnostic tool for accurately identifying CPE and carbapenemase’s subtypes in clinical isolates. It may also aid in selecting appropriate antibiotics for each carbapenemase subtype. Ultimately, we expect that the A-MALDI method will contribute to preventing the spread of antibiotic resistance and improving human public health.
2024-11-25 | PXD046179 | Pride
Project description:This study aims to determine the epidemiology of Enterobacteriaceae resistant to antibiotics of last resort in pregnant women in labour at a tertiary hospital, Pretoria, South Africa. Rectal swabs shall be used to screen for colonisation with CRE and colistin-resistant Enterobacteriales in pregnant women during labour. Carbapenem and colistin-resistant Enterobacterales can cause the following infections: bacteraemia; nosocomial pneumonia; urinary tract infections, and intra-abdominal infections. Due to limited treatment options, infections caused by these multidrug-resistant organisms are associated with a mortality rate of 40-50%. Screening for colonisation of carbapenem-resistant Enterobacteriaceae (CRE) and colistin-resistant Enterobacteriaceae will help implement infection and prevention measures to limit the spread of these multidrug-resistant organisms.
2022-07-20 | GSE208573 | GEO
Project description:Using the parameterized susceptible‐exposed‐infectious‐recovered model, we simulated the spread dynamics of coronavirus disease 2019 (COVID‐19) outbreak and impact of different control measures, conducted the sensitivity analysis to identify the key factor, plotted the trend curve of effective reproductive number (R), and performed data fitting after the simulation. By simulation and data fitting, the model showed the peak existing confirmed cases of 59 769 arriving on 15 February 2020, with the coefficient of determination close to 1 and the fitting bias 3.02%, suggesting high precision of the datafitting results. More rigorous government control policies were associated with a slower increase in the infected population. Isolation and protective procedures would be less effective as more cases accrue, so the optimization of the treatment plan and the development of specific drugs would be of more importance. There was an upward trend of R in the beginning, followed by a downward trend, a temporary rebound, and another continuous decline. The feature of high infectiousness for severe acute respiratory syndrome coronavirus 2(SARS‐CoV‐2) led to an upward trend, and government measures contributed to the temporary rebound and declines. The declines of R could be exploited as strong evidence for the effectiveness of the interventions. Evidence from the fourphase stringent measures showed that it was significant to ensure early detection, early isolation, early treatment, adequate medical supplies, patients’ being admitted to designated hospitals, and comprehensive therapeutic strategy. Collaborative efforts are required to combat the novel coronavirus, focusing on both persistent strict domestic interventions and vigilance against exogenous imported cases.
2024-09-02 | BIOMD0000000984 | BioModels
Project description:The coronavirus disease 2019 (COVID-19) pandemic has placed epidemic modeling at the forefront of worldwide public policy making. Nonetheless, modeling and forecasting the spread of COVID-19 remains a challenge. Here, we detail three regional scale models for forecasting and assessing the course of the pandemic. This work demonstrates the utility of parsimonious models for early-time data and provides an accessible framework for generating policy-relevant insights into its course. We show how these models can be connected to each other and to time series data for a particular region. Capable of measuring and forecasting the impacts of social distancing, these models highlight the dangers of relaxing nonpharmaceutical public health interventions in the absence of a vaccine or antiviral therapies.
2024-09-02 | BIOMD0000000956 | BioModels
Project description:RNAseq of CD14 cells from 60 female RA patients activated with LPS for 2 hours. Patients were collected crossectionally from the Rheumatology clinic during 2019-2020. Age md 64, range 23-76 years, Disease duration md 10, range 1-45 years.
2022-09-27 | GSE201670 | GEO