Carbapenem-resistant
is one of the major concerns in clinical settings impelling a great challenge to antimicrobial therapy for patients with infections caused by the pathogen. While membrane ...permeability, together with derepression of the intrinsic beta-lactamase gene, is the global prevailing mechanism of carbapenem resistance in
, the acquired genes for carbapenemases need special attention because horizontal gene transfer through mobile genetic elements, such as integrons, transposons, plasmids, and integrative and conjugative elements, could accelerate the dissemination of the carbapenem-resistant
. This review aimed to illustrate epidemiologically the carbapenem resistance in
, including the resistance rates worldwide and the carbapenemase-encoding genes along with the mobile genetic elements responsible for the horizontal dissemination of the drug resistance determinants. Moreover, the modular mobile elements including the carbapenemase-encoding gene, also known as the
resistance islands, are scrutinized mostly for their structures.
Power storage and conversion technologies are increasingly in demand for their energy efficiency and eco-friendliness, with capacitors being key in stabilizing and filtering voltage in these devices. ...However, during this process, thermal degradation phenomena often occur due to over-voltage and over-current. This degradation can lead to decreased performance, capacitor failure, and in severe cases, explosions. Thus, the precise monitoring and prediction of capacitor lifetime is paramount. In this study, we use accelerated life test data to create images using reference plots and compare the accuracy of deep neural network training through image fusion. This introduces a new methodology for monitoring the lifetime of capacitors. This approach involves collecting aging data through accelerated life tests and then generating images from time-series data composed of capacitor voltage, current, and resistance. These images are used to train the deep learning algorithm, extracting relevant features and predicting the remaining life of the capacitors. Our method demonstrates remarkable effectiveness, showing an impressive accuracy rate of 80% in the real-time monitoring of capacitors under various operating conditions. Ultimately, this deep neural network-based lifetime monitoring algorithm holds potential to be scaled and applied to diverse electronic systems, enhancing their reliability and safety.
•New method for capacitor life prediction using deep neural networks.•Created images from time-series data for algorithm training.•Lifespan classification of capacitors with image-based training.•Achieved 90% accuracy in real-time lifespan prediction.
At the end of 2015, a global action plan on antimicrobial resistance (AMR) was proposed by the World Health Organization, and the Global AMR Surveillance System (GLASS) was subsequently initiated. ...The Centers for Disease Control and Prevention of South Korea established a customized AMR surveillance system for South Korea, called Kor-GLASS, in early 2016. A pilot phase of Kor-GLASS was operated from May to December 2016 with six sentinel hospitals, and phase I of Kor-GLASS started in January 2017 with eight sentinel hospitals. Previous surveillance data for overestimated AMR due to duplicate isolation of drug-resistant pathogens were corrected and error-free AMR data were compared with those from other countries. One-half (53.2%, 377/708) of Staphylococcus aureus blood strains exhibited resistance to cefoxitin, indicating methicillin-resistant S. aureus. Resistance to ampicillin in Enterococcus faecalis blood strains was rare (0.6%, 1/175), while the resistance rate to penicillin was 26.3% (46/175). Resistance to vancomycin (34.0%, 98/288) and teicoplanin (18.8%, 98/288) was frequently observed in Enterococcus faecium strains. The resistance rate of Escherichia coli strains to cefotaxime was 32.4% (574/1772), and that of Klebsiella pneumoniae strains was 26.1% (181/693). The resistance rates of Pseudomonas aeruginosa strains to imipenem and meropenem were 19.5% (29/149) and 18.1% (27/149), respectively. And 92.1% (187/203) of Acinetobacter baumannii strains were resistant to both imipenem and meropenem. The high incidence of bacteremia caused by major AMR pathogens among hospitalized patients especially in intensive care units emphasized the importance of hospital infection control and the need to improve the crowded hospitalization system in South Korea. The isolation rate of the Salmonella spp. is decreasing, reflecting the current socio-economic status of South Korea. The proportions of bacterial species in the blood strains were similar to those in other Asian countries with similar lifestyles.
The COVID-19 pandemic in Korea has dynamically changed with the occurrence of more easily transmissible variants. A rapid and reliable diagnostic tool for detection of SARS-CoV-2 is needed. While ...RT-PCR is currently the gold standard for detecting SARS-CoV-2, the procedure is time-consuming and requires expert technicians. The rapid antigen detection test (RADT) was approved as a confirmatory test on 14 March 2022 due to rapid dissemination of the Omicron variant. The benefits of the RADT are speed, simplicity, and point-of-care feasibility. The aim of our study was to evaluate the clinical performance of RADT compared to RT-PCR in a single center over 15 months, fully covering the SARS-CoV-2 'Variants of Concern (VOC).' A total of 14,194 cases was simultaneously tested by RT-PCR and RADT from January 2021 to March 2022 in Gangnam Severance Hospital and were retrospectively reviewed. PowerChek SARS-CoV-2, Influenza A&B Multiplex Real-time PCR Kit, and STANDARD Q COVID-19 Ag Test were used. Positive rates, sensitivities, specificities, positive predictive values (PPV), and negative predictive values (NPV) were estimated for five periods (3 months/period). Receiver operator characteristic curve (ROC) analysis was performed, and Spearman's rank test assessed the correlation between RT-PCR Ct values and semi-quantitative RADT results. The overall positive rate of RT-PCR was 4.64%. The overall sensitivity and specificity were 0.577 95% confidence interval (CI) 0.539-0.614 and 0.991 95% CI 0.989-0.993, respectively. ROC analysis resulted in an area under the curve of 0.786 (P < 0.0001, Yuden's index = 0.568). The PCR positive rates were estimated as 0.11%, 0.71%, 4.51%, 2.02%, and 13.72%, and PPV was estimated as 0.045, 0.421, 0.951, 0.720, and 0.798 in Periods 1, 2, 3, 4, and 5, respectively. A significant and moderate negative correlation between PCR Ct values and semi-quantitative RADT results was observed (Spearman's ρ = - 0.646, P < 0.0001). The RADT exhibited good performance in specimens with low Ct values (Ct ≤ 25.00) by RT-PCR. The PPV was significantly higher in Periods 3 and 5, which corresponds to rapid dissemination of the Delta and Omicron variants. The high PPV implies that individuals with a positive RADT result are very likely infected with SARS-CoV-2 and would require prompt quarantine rather than additional RT-PCR testing. The sensitivity of 0.577 indicates that RADT should not replace RT-PCR. Nonetheless, given the high PPV and the ability to track infected persons through rapid results, our findings suggest that RADT could play a significant role in control strategies for further SARS-CoV-2 variants.
This study proposes an event detection technique for acoustic surveillance that detects emergency situations by using acoustic sensors. Most surveillance systems have widely depended on visual data ...recorded by closed-circuit television (CCTV) cameras, but more intelligent systems are now beginning to use audio information for more reliable detection of emergency situations. Most of the conventional studies on acoustic event detection adopt limited types of acoustic data and are based on simple algorithms, such as energy-based determination. Thus, these approaches are easily realized, but may induce serious detection errors in real-world applications. In this study, we propose an event detection technique based on a sound-learning algorithm to be adopted by real-time acoustic surveillance systems. One main process of this technique is to construct acoustic models via learning algorithms from sound data collected according to types of acoustic events. The models are used to determine whether audio streams entering an acoustic sensor refer to the events or not. In event detection experiments performed in an outdoor environment, the proposed approach outperformed conventional approaches in the real-time detection of acoustic events.
Molecular-based diagnostic techniques can compensate for the inherent limitations of culture-based microbiology and provide a more comprehensive description of an entire community of bacteria at a ...particular anatomical site. Using culture-independent DNA-based molecular techniques, the aim of the present study was to characterize, differentiate, and compare the composition of lower airway bacterial microbiome between clinically stable and acutely infected patients with bronchiectasis experiencing exacerbation.
Patients with clinically stable bronchiectasis and those experiencing acutely exacerbated bronchiectasis were recruited. All patients underwent bronchoscopy. Paired sputum and bronchoalveolar lavage (BAL) samples were collected for microbiological tests. Molecular analysis was performed for BAL samples using 16S ribosomal RNA (rRNA) gene sequencing.
The mean age of the 14 recruited patients was 60 years (range 42 to 78 years), and nine (64%) were female. Using quantitative culture and 16S rRNA sequencing, the common organisms identified from 14 BAL samples were Haemophilus influenzae, Pseudomonas aeruginosa and Moraxella catarrhalis, and Prevotella. Molecular techniques revealed Prevotella and Veillonella as potentially pathogenic anaerobic species. 16S rRNA gene sequencing yielded similar relative abundances and distributions of taxa in the stable and exacerbated bronchiectasis groups. Alpha diversity with richness, Simpson's and Shannon indices, and beta diversity using principal coordinate analysis revealed no significant differences in lung microbiome between patients with clinically stable and exacerbated bronchiectasis.
Culture-based microbiological and molecular-based techniques did not reveal significant differences in the lung microbiome of patients who were clinically stable and those experiencing exacerbated bronchiectasis. Patient-specific microbial communities were dominated by one or several genera, regardless of clinical status. DNA sequencing could identify potentially pathogenic organisms unable to be identified using microbiological methods.
Species identification by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a routine diagnostic process for infectious diseases in current clinical ...settings. The rapid, low-cost, and simple to conduct methodology is expanding its application in clinical microbiology laboratories to diagnose the antimicrobial resistance (AMR) in microorganisms. Primarily, antimicrobial susceptibility testing is able to be carried out either by comparing the area under curve of MALDI spectra of bacteria grown in media with antimicrobial drugs or by identifying the shift peaks of bacteria grown in media including 13C isotope with antimicrobial drugs. Secondly, the antimicrobial resistance is able to be determined through identifying (i) the antimicrobial-resistant clonal groups based on the fingerprints of the clone, (ii) the shift peak of the modified antimicrobial drug, which is inactivated by the resistance determinant, (iii) the shift peak of the modified antimicrobial target, (iv) the peak specific for the antimicrobial determinant, and (v) the biomarkers that are coproduced proteins with AMR determinants. This review aims to present the current usage of the MALDI-TOF MS technique for diagnosing antimicrobial resistance in bacteria, varied approaches for AMR diagnostics using the methodology, and the future applications of the methods for the accurate and rapid identification of AMR in infection-causing bacterial pathogens.
To investigate the association between the results of urinalysis and those of concurrent urine cultures, and to construct a prediction model for the results of urine culture. A total of 42,713 ...patients were included in this study. Patients were divided into two independent groups including training and test datasets. A novel prediction algorithm, designated the UTOPIA value, was constructed with the training dataset, based on an association between the results of urinalysis and those of concurrent urine culture. The diagnostic performance of the UTOPIA value was validated with the test dataset. Six variables were selected for the equation of the UTOPIA value: age of higher UTI risk odds ratio (OR), 2.069125, female (OR, 1.400648), nitrite (per 1 grade; OR, 3.765457), leukocyte esterase (per 1 grade; OR, 1.701586), the number of WBCs (per 1 × 10
/L; OR, 1.000121), and the number of bacteria (per 1 × 10
/L; OR, 1.004195). The UTOPIA value exhibited an area under the curve value of 0.837 when validated with the independent test dataset. The UTOPIA value displayed good diagnostic performance for predicting urine culture results, which would help to reduce unnecessary culture. Different cutoffs can be used according to the clinical indication.
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