Background: The study describes the application of the multiplex high-resolution melting curve (MHRM) assay for the simultaneous detection of five common bacterial pathogens (Pseudomonas aeruginosa, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii and Escherichia coli) directly from bronchoalveolar lavage samples.
Results: Our MHRM assay successfully identified all five respiratory pathogens in less than 5 h, with five separate melting curves with specific melt peak temperatures (Tm). The different Tm were characterized by peaks of 78.1 ± 0.4 °C for S. aureus, 83.3 ± 0.1 °C for A. baumannii, 86.7 ± 0.2 °C for E. coli, 90.5 ± 0.1 °C for K. pneumoniae, 94.5 ± 0.2 °C for P. aeruginosa. The overall sensitivity and specificity of MHRM were 100% and 88.8-100%, respectively.
Conclusions: Our MHRM assay offers a simple and fast alternative to culture approach for simultaneous detection of five major bacterial lower respiratory tract infection pathogens. Utilization of this assay can help clinicians initiate prompt and appropriate antimicrobial treatment, towards reducing the morbidity and mortality of severe respiratory infections.
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http://dx.doi.org/10.1186/s12866-022-02558-2 | DOI Listing |
Br J Math Stat Psychol
February 2024
KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, China.
In this paper, we propose a novel Gibbs-INLA algorithm for the Bayesian inference of graded response models with ordinal response based on multidimensional item response theory. With the combination of the Gibbs sampling and the integrated nested Laplace approximation (INLA), the new framework avoids the cumbersome tuning which is inevitable in classical Markov chain Monte Carlo (MCMC) algorithm, and has low computing memory, high computational efficiency with much fewer iterations, and still achieve higher estimation accuracy. Therefore, it has the ability to handle large amount of multidimensional response data with different item responses.
View Article and Find Full Text PDFObjective: The present study aims to translate into Turkish and investigate the validity and reliability of the Mental Health Recovery Measure (MHRM).
Method: The sample consisted of 343 outpatients - and in-patients under treatment for a variety of psychiatric diagnoses at a state hospital and a university research hospital. The MHRM along with the Subjective Recovery Assessment Scale (SRAS), Psychological Well Being Scale (PWBS), Emotional Eating Scale (EES), and The Internalized Stigma of Mental Illness Scale (ISMI).
Behav Res Methods
December 2023
Department of Psychology, National Chengchi University, 64, Section 2, Zhi-Nan Road, Taipei City, Taiwan.
Item parameter estimation is a crucial step when conducting item factor analysis (IFA). From the view of frequentist estimation, marginal maximum likelihood (MML) seems to be the gold standard. However, fitting a high-dimensional IFA model by MML is still a challenging task.
View Article and Find Full Text PDFFront Microbiol
December 2022
Department of Microbiology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
The diagnosis of urinary tract infections (UTIs) is usually based on the results of urine culture, but it is time-consuming, labor-intensive and has a low sensitivity. The aim of this study was to develop multiplex high-resolution melting assay (MHRM) for the simultaneous detection of five common bacterial pathogens (, , , , and group B streptococci (GBS)) directly from urine samples. A total of 287 urine specimens were evaluated by HRM assay and the results were compared with the conventional culture method.
View Article and Find Full Text PDFSci Rep
November 2022
Department of Biology, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand.
Canine babesiosis is a tick-borne disease caused by Babesia spp., which infects and destroys healthy erythrocytes, leading to mortality and morbidity in dogs. The diagnosis of babesiosis is tedious and time-consuming, especially in latent and chronic infections.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!