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e., viral pneumonia). The major advantage of our approach over binary classification is that we avoid modeling individual viral pneumonia classes explicitly and treat all known viral pneumonia cases as anomalies to improve the one-class model. The proposed model outperforms binary classification models on the clinical X-VIRAL dataset that contains 5,977 viral pneumonia (no COVID-19) cases, 37,393 non-viral pneumonia or healthy cases. Moreover, when directly testing on the X-COVID dataset that contains 106 COVID-19 cases and 107 normal controls without any fine-tuning, our model achieves an AUC of 83.61% and sensitivity of 71.70%, which is comparable to the performance of radiologists reported in the literature.

an innovative non-thermal plasma (NTP) system constituted by a radiofrequency (RF) power generator directly coupled to a treatment probe is described and characterized. This system is intended to be applied as a medical device for therapeutic treatments.

electrical characterization of the radiofrequency power generator supplying the treatment probe was performed. Meanwhile, generated NTP was optically analyzed. Obtained data were studied to establish the safety profile of plasma application on heat sensitive matter.

the NTP system was validated through bacterial deactivation trials, as well as, of being capable of deactivating carcinogenic cells. Besides promoting and accelerating wound closure in vivo performed in mice, demonstrating faster healing than that done with conventional treatments.

the NTP system's characterization is an essential stage to determine the adequate application of the generated plasma over organic media. The therapeutic benefits of the NTP system were proved by the development of in vivo experiences involving laboratory mice.

the generated NTP interacts with surrounding air particles producing reactive oxygen and nitrogen species, which, exhibit bactericidal and antiseptic effects due to their strong biochemical reactivity; functioning like critical mediators in animal physiology and promoting wound healing processes. These properties make the NTP system a feasible technology intended for therapeutic treatments.

the generated NTP interacts with surrounding air particles producing reactive oxygen and nitrogen species, which, exhibit bactericidal and antiseptic effects due to their strong biochemical reactivity; functioning like critical mediators in animal physiology and promoting wound healing processes. These properties make the NTP system a feasible technology intended for therapeutic treatments.Non-classically secreted proteins (NCSPs) are proteins that are located in the extracellular environment, although there is a lack of known signal peptides or secretion motifs. They usually perform different biological functions in intracellular and extracellular environments, and several of their biological functions are linked to bacterial virulence and cell defence. Accurate protein localization is essential for all living organisms, however, the performance of existing methods developed for NCSP identification has been unsatisfactory and in particular suffer from data deficiency and possible overfitting problems. Further improvement is desirable, especially to address the lack of informative features and mining subset-specific features in imbalanced datasets. In the present study, a new computational predictor was developed for NCSP prediction of gram-positive bacteria. First, to address the possible prediction bias caused by the data imbalance problem, ten balanced subdatasets were generated for ensemble model construction. Then, the F-score algorithm combined with sequential forward search was used to strengthen the feature representation ability for each of the training subdatasets. Third, the subset-specific optimal feature combination process was adopted to characterize the original data from different aspects, and all subdataset-based models were integrated into a unified model, NonClasGP-Pred, which achieved an excellent performance with an accuracy of 93.23 %, a sensitivity of 100 %, a specificity of 89.01 %, a Matthew's correlation coefficient of 87.68 % and an area under the curve value of 0.9975 for ten-fold cross-validation. Based on assessment on the independent test dataset, the proposed model outperformed state-of-the-art available toolkits. For availability and implementation, see http//lab.malab.cn/~wangchao/softwares/NonClasGP/.The major human pathogen Streptococcus pyogenes shares an intimate evolutionary history with mobile genetic elements, which in many cases carry genes encoding bacterial virulence factors. During recent whole-genome sequencing of a longitudinal sample of S. pyogenes isolates in England, we identified a lineage within emm4 that clustered with the reference genome MEW427. Like MEW427, this lineage was characterized by substantial gene loss within all three prophage regions, compared to MGAS10750 and isolates outside of the MEW427-like lineage. Gene loss primarily affected lysogeny, replicative and regulatory modules, and to a lesser and more variable extent, structural genes. Importantly, prophage-encoded superantigen and DNase genes were retained in all isolates. In isolates where the prophage elements were complete, like MGAS10750, they could be induced experimentally, but not in MEW427-like isolates with degraded prophages. We also found gene loss within the chromosomal island SpyCIM4 of MEW427-like isolates, although surprisingly, the SpyCIM4 element could not be experimentally induced in either MGAS10750-like or MEW427-like isolates. This did not, however, appear to abolish expression of the mismatch repair operon, within which this element resides. The inclusion of further emm4 genomes in our analyses ratified our observations and revealed an international emm4 lineage characterized by prophage degradation. Intriguingly, the USA population of emm4 S. pyogenes appeared to constitute predominantly MEW427-like isolates, whereas the UK population comprised both MEW427-like and MGAS10750-like isolates. The degraded and cryptic nature of these elements may have important phenotypic and fitness ramifications for emm4 S. selleck kinase inhibitor pyogenes, and the geographical distribution of this lineage raises interesting questions on the population dynamics of the genotype.