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Abstract Cronobacter sakazakii clonal complex 4 (CC4) is strongly associated with neonatal meningitis. However, C. sakazakii CC4‐specific pathogenicity traits have not been determined. In this study, the comparative genomic analysis of 144 genomes of C. sakazakii CC4 strains and 376 non‐CC4 C. sakazakii strains was undertaken. Twenty‐four CC4 strains were previously undescribed clinical and nonclinical strains that had been collected from various regions in China (2006–2017). The remaining genomes were of multiple sequence types of C. sakazakii strains, which had been isolated worldwide (1973–2021). The pan‐genome of C. sakazakii comprised 32,332 genes, of which 2.58% (832 genes) constituted the core genome. More C. sakazakii CC4 strains have a complete cusABCFR efflux system with a significant difference compared with non‐CC4 strains, and the ibeB‐homologous cusC gene in the cusABCFR efflux system is probably associated with the invasion of human brain microvascular endothelial cells (BMEC). In addition, the isolates with K2:CA2 capsule or type IV pili‐associated genes associated with neonatal meningitis were statistically more present in CC4 strains than non‐CC4 strains (p

Scutellaria strigillosa Hemsl., known for its traditional use in Chinese herbal medicine, is valued for heat-clearing and detoxifying, promoting diuresis, reducing swelling, alleviating pain, and preventing miscarriage. Despite its historical use, comprehensive studies on pharmacophylogenetic analysis, including genetic and chemical profiles and the antimicrobial activity of S. strigillosa are still lacking. Understanding these aspects is crucial for fully realizing its therapeutic potential and ensuring sustainable use. This study aims to elucidate these aspects through comparative genomics, metabolomics, and antimicrobial assays with Scutellaria baicalensis Georgi and Scutellaria barbata D. Don. The chloroplast genome of S. strigillosa was assembled, measuring 152,533 bp, and revealing a high degree of conservation, especially in the protein-coding regions, and identified four regions trnK(UUU)-rps16, trnN(GUU)-trnR(ACG), accD-psaI, psbE-petL) of variability that could serve as phylogenetic markers. The phylogenetic analysis revealed a closer genetic relationship of S. strigillosa with S. tuberifera and S. scordifolia than traditionally classified, suggesting a need for taxonomic reevaluation within the genus. UPLC-Q-TOF-MS analysis in negative ion mode was used to explore the chemical diversity among these species, revealing distinct variations in their chemical compositions. S. strigillosa shared a closer chemical profile with S. barbata, aligning with phylogenetic findings. Metabolomic identification through Progenesis QI software resulted in the tentative identification of 112 metabolites, including a substantial number of flavonoids, diterpenoids, iridoid glycosides, phenylethanoid glycosides, and others. HPLC analysis further detailed the concentrations of 12 actives across the species, highlighting the variation in compound content. S. strigillosa shows antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa, similar to S. baicalensis root extracts. This research enhances the understanding of the phylogenetic and phytochemical profiles and the antibacterial activity of S. strigillosa, offering new insights into its medicinal properties. The findings suggest a need for taxonomic reevaluation within the genus and underscore the potential antibacterial activity of S. strigillosa for therapeutic applications. Further studies are encouraged to explore its full medicinal potential and contribute to the sustainable development of Scutellaria species.

Abstract Background Vibrio furnissii is an emerging human pathogen closely related to V. fluvialis that causes acute gastroenteritis. V. furnissii infection has been reported to be rarer than V. fluvialis, but a multi-drug resistance plasmid has recently been discovered in V. furnissii. Methods During daily monitoring at a general hospital in Beijing, China, seven V. furnissii strains were collected from patients aged over 14 years who presented with acute diarrhoea between April and October 2018. Genome analysis and comparison were performed for virulence and antimicrobial resistance genes, plasmids and transposon islands, together with phylogenetic analysis. Antimicrobial resistance to 19 antibiotics was investigated using the microbroth dilution method. Virulence phenotypes were investigated based on type VI secretion system (T6SS) expression and using a bacterial killing assay and a haemolysin assay. Results Phylogenetic analysis based on single-nucleotide polymorphisms revealed a closer relationship between V. furnissii and V. fluvialis than between other Vibrio spp. The seven V. furnissii isolates were in different monophyletic clades in the phylogenetic tree, suggesting that the seven cases of gastroenteritis were independent. High resistance to cefazolin, tetracycline and streptomycin was found in the V. furnissii isolates at respective rates of 100.0%, 57.1% and 42.9%, and intermediate resistance to ampicillin/sulbactam and imipenem was observed at respective rates of 85.7% and 85.7%. Of the tested strains, VFBJ02 was resistant to both imipenem and meropenem, while VFBJ01, VFBJ02, VFBJ05 and VFBJ07 were multi-drug resistant. Transposon islands containing antibiotic resistance genes were found on the multi-drug resistance plasmid in VFBJ05. Such transposon islands also occurred in VFBJ07 but were located on the chromosome. The virulence-related genes T6SS, vfh, hupO, vfp and ilpA were widespread in V. furnissii. The results of the virulence phenotype assays demonstrated that our isolated V. furnissii strains encoded an activated T6SS and grew in large colonies with strong beta-haemolysis on blood agar. Conclusion This study showed that diarrhoea associated with V. furnissii occurred sporadically and was more common than expected in the summer in Beijing, China. The antibiotic resistance of V. furnissii has unique characteristics compared with that of V. fluvialis. Fluoroquinolones and third-generation cephalosporins, such as ceftazidime and doxycycline, were effective at treating V. furnissii infection. Continua laboratory-based surveillance is needed for the prevention and control of V. furnissii infection, especially the dissemination of the antibiotic resistance genes in this pathogen.

Introduction: FLT3 mutations are closely associated with the occurrence of hematological and solid malignancies, especially with acute myeloid leukemia. Currently, several FLT3 inhibitors are in clinical trials, and some have been applied in clinic. However, the safety, efficacy and pharmacodynamics of these FLT3 inhibitors have not been systemically analyzed before.Methods: We searched and reviewed clinical trial reports on the monotherapy of 13 FLT3 inhibitors, including sorafenib, lestaurtinib, midostaurin, gilteritinib, quizartinib, sunitinib, crenolanib, tandutinib, cabozantinib, pexidartinib, pacritinib, famitinib, and TAK-659 in patients with hematological and solid malignancies before May 31, 2023.Results: Our results showed the most common adverse events (AEs) were gastrointestinal adverse reactions, including diarrhea, hand-foot syndrome and nausea, while the most common hematological AEs were febrile neutropenia, anemia, and thrombocytopenia. Based on the published data, the mean overall survival (OS) and the mean progression-free survival (PFS) were 9.639 and 5.905 months, respectively. The incidence of overall response rate (ORR), complete remission (CR), partial response (PR), and stable disease (SD) for all these FLT3 inhibitors was 29.0%, 8.7%, 16.0%, and 42.3%, respectively. The ORRs of FLT3 inhibitors in hematologic malignancies and solid tumors were 40.8% and 18.8%, respectively, indicating FLT3 inhibitors were more effective for hematologic malignancies than for solid tumors. In addition, time to maximum plasma concentration (Tmax) in these FLT3 inhibitors ranged from 0.7-12.0 hours, but the elimination half-life (T1/2) range was highly variable, from 6.8 to 151.8 h.Discussion: FLT3 inhibitors monotherapy has shown significant anti-tumor effect in clinic, and the effectiveness may be further improved through combination medication.

The belief rule base is crucial in expert systems for intelligent diagnosis of equipment. However, in the belief rule base for fault diagnosis, multiple antecedent attributes are often initially determined by domain experts. Multiple fault symptoms related to multiple antecedent attributes are different when an actual fault occurs. This leads to multiple antecedent attributes matching with multiple fault symptoms non-simultaneously, thereby resulting in a fault diagnosis lacking timeliness and accuracy. To address this issue, this paper proposes a method for belief rule-based optimization based on Naive Bayes theory. First, a fault sample is taken in a long enough window and divided into several interval samples, making the analysis samples approximate the overall samples. Second, using Gaussian mixture clustering and Naive Bayes optimization, iteration is performed over the threshold and limit values of fault symptoms in the belief rule base based on the requirements of the timeliness and accuracy of fault diagnosis results. Finally, the belief rule base is optimized. Using fault samples from high-pressure heaters and condensers, the validation results show that there is a there is a significant improvement in the timeliness and accuracy of fault diagnosis with the optimal belief rule base.

Abstract We propose an autoregressive weighted network (ARWNet) time series forecasting model inspired by the idea of ensemble learning. The model adopts the classical autoregressive analysis to optimize weak learners. Meanwhile, the combined weight optimization method is used to construct an efficient, strong learner. With these methodological foundations, the scalability of the framework is greatly enhanced by the possibility of experimenting with other learners to assist in decision‐making. Machine learning can provide great utility and acceptable cost in the prediction process of electricity transformers. Over the years, many research papers on time series prediction have been reported. This work will focus on the analysis using the potential properties in the series: long‐term, continuity, periodicity, and delay. In our experiments, the ETT‐small dataset is used to compare the prediction accuracy of ARWNet and other mainstream models. All results suggest that the proposed ARWNet model demonstrates strong generalization ability and high predicting accuracy with delay characteristics, which outperform current popular time‐series prediction methods.

Summary: Emerging studies have demonstrated the link between RNA modifications and various cancers, while the predictive value and functional mechanisms of RNA modification-related genes (RMGs) in esophageal squamous cell carcinoma (ESCC) remain unclear. Here we established a prognostic signature for ESCC based on five RMGs. The analysis of ESCC clinical samples further verified the prognostic power of the prognostic signature. Moreover, we found that the knockdown of NSUN6 promotes ESCC progression in vitro and in vivo, whereas the overexpression of NSUN6 inhibits the malignant phenotype of ESCC cells. Mechanically, NSUN6 mediated tRNA m5C modifications selectively enhance the translation efficiency of CDH1 mRNA in a codon dependent manner. Rescue assays revealed that E-cadherin is an essential downstream target that mediates NSUN6’s function in the regulation of ESCC progression. These findings offer additional insights into the link between ESCC and RMGs, as well as provide potential strategies for ESCC management and therapy.

Choosing the appropriate antibiotics to treat bacterial infections has grown more challenging as a result of the emergence of antibiotic-resistant bacteria. Aminoglycosides, as broad-spectrum antibiotics, are increasingly being used clinically; however, for most effective employment of aminoglycosides, a comprehensive understanding of aminoglycoside resistance genes’ prevalence and dissemination is required. Therefore, to better understand the global resistance status of aminoglycoside antibiotics and the prevalence of antibiotic-resistance genes (ARGs) in various bacterial species, this systematic review gathered relevant data from multiple studies. Two primary resistance mechanisms—aminoglycoside enzymatic modification and 16S rRNA methylation—were assessed, and the prevalence of the corresponding ARGs was described. The coexistence of aminoglycoside ARGs with other ARGs was also demonstrated, as was the relationship between aminoglycoside ARGs and resistant phenotypes. The lack of effective therapeutic agents to combat resistant pathogens presents a real threat to public health. The combination of aminoglycosides with other antibiotics may provide a novel treatment strategy.

Microbial communities inhabiting sedimentary environments in river source regions serve as pivotal indicators of pristine river ecosystems. While the correlation between antibiotic resistome and pathogenicity with core gut bacteria in humans is well established, there exists a significant knowledge gap concerning the interaction of antibiotic resistance genes (ARGs) and human pathogenic bacteria (HPB) with specific microbes in river source basins, often referred to as “terrestrial gut”. Understanding the microbial composition, including bacteria and resident genetic elements such as ARGs, HPB, Mobile Genetic Elements (MGEs), and Virulence Factors (VFs), within natural habitats against the backdrop of global change, is imperative. To address this gap, an enrichment-based culturomics complementary along with metagenomics was conducted in this study to characterize the microbial biobank and provide preliminary ecological insights into profiling the dissemination of ARGs in the Lancang River Source Basin. Based on our findings, in the main stream of the Lancang River Source Basin, 674 strains of bacteria, comprising 540 strains under anaerobic conditions and 124 under aerobic conditions, were successfully isolated. Among these, 98 species were identified as known species, while 4 were potential novel species. Of these 98 species, 30 were HPB relevant to human health. Additionally, bacA and bacitracin emerged as the most abundant ARGs and antibiotics in this river, respectively. Furthermore, the risk assessment of ARGs predominantly indicated the lowest risk rank (Rank Ⅳ) in terms of endangering human health. In summary, enrichment-based culturomics proved effective in isolating rare and unknown bacteria, particularly under anaerobic conditions. The emergence of ARGs showed limited correlation with MGEs, indicating minimal threats to human health within the main stream of the Lancang River Source Basin.

The aim of this paper is to study the evolutionary dynamic model for signed edges as observed in online signed social networks. We introduce the incremental mechanism of signed edges behind a simple random walk and explain how this relates to Brownian motion and the diffusive process. We prove how a one-dimensional thermal diffusion equation can be obtained to describe such edge-generating mechanism, and moreover obtain a macroscopic probability distribution of positive and negative edges. The result reveals that the signed edge growth dynamics process can be regarded as a thermodynamic diffusion process. Both empirically and theoretically, we validate that signed network links follow the classic statistic mechanism, i.e., local Brownian motion gives rise to the global emergence pattern of the Gaussian process. The investigation might discover a new and universal characteristic for signed networks, and shed light on some potential applications, such as information spreading, evolutionary games, trust transmission, and dynamic structural balance.

Objective When developing prediction models, researchers commonly employ a single model which uses all the available data (end-to-end approach). Alternatively, a similarity-based approach has been previously proposed, in which patients with similar clinical characteristics are first grouped into clusters, then prediction models are developed within each cluster. The potential advantage of the similarity-based approach is that it may better address heterogeneity in patient characteristics. However, it remains unclear whether it improves the overall predictive performance. We illustrate the similarity-based approach using data from people with depression and empirically compare its performance with the end-to-end approach.Methods We used primary care data collected in general practices in the UK. Using 31 predefined baseline variables, we aimed to predict the severity of depressive symptoms, measured by Patient Health Questionnaire-9, 60 days after initiation of antidepressant treatment. Following the similarity-based approach, we used k-means to cluster patients based on their baseline characteristics. We derived the optimal number of clusters using the Silhouette coefficient. We used ridge regression to build prediction models in both approaches. To compare the models’ performance, we calculated the mean absolute error (MAE) and the coefficient of determination (R2) using bootstrapping.Results We analysed data from 16 384 patients. The end-to-end approach resulted in an MAE of 4.64 and R2 of 0.20. The best-performing similarity-based model was for four clusters, with MAE of 4.65 and R2 of 0.19.Conclusions The end-to-end and the similarity-based model yielded comparable performance. Due to its simplicity, the end-to-end approach can be favoured when using demographic and clinical data to build prediction models on pharmacological treatments for depression.

Background: The decrease in physical function resulting from COVID-19 infection exerts a substantial negative influence on the quality of life of individuals. Physical activity plays a crucial and irreplaceable role in hastening the elimination of adverse effects on the body caused by acute and chronic diseases. Nevertheless, there have been reports of unfavorable events following physical activity post-COVID-19 infection, sparking debate regarding the efficacy of physical activity as a rehabilitation method to enhance the physical function of COVID-19 patients. Objective: The aim of this study is to investigate the impact of physical activity on promoting the restoration of physical function among individuals with COVID-19, and to offer guidance for the advancement and consideration of physical activity in the rehabilitation treatment of COVID-19 patients. Methods: A search was conducted on the PubMed and Web of Science core collection databases, with the search period set from January 1, 2020, to February 6, 2023. The included literature was assessed for risk of bias and methodological quality according to the Cochrane Handbook for Systematic Reviews of Interventions, utilizing Review Manager 5.1 software. The outcome measures from the included studies were analyzed, and the quality of evidence for the outcome measures was graded using the GRADE classification criteria. Results: The effect of physical activity intervention on improving the 6-Minute Walk Test score in COVID-19 patients was better than that of conventional treatment [WMD = 69.19(95%CI = 39.38, 98.99), I2 = 57%(p = 0.03)]. The effect of physical activity on improving the 30-Second Sit-to-Stand Test score was better than that of conventional treatment [WMD = 2.98(95%CI = 1.91, 4.04), I2 = 0%(p = 0.56)]. There was no significant difference between physical activity and conventional treatment in improving Grip strength in COVID-19 patients [WMD = 2.35(95%CI = −0.49, 5.20), I2 = 0%(p = 0.80)]. The effect of physical activity on improving the Timed Up and Go test score in COVID-19 patients was better than that of conventional treatment [WMD = −1.16(95%CI = −1.98, −0.34), I2 = 4%(p = 0.35)]. The effect of physical activity on improving Forced Vital Capacity in COVID-19 patients was better than that of conventional treatment [WMD = 0.14(95%CI = 0.08, 0.21), I2 = 0%(p = 0.45)]. The effect of physical activity on improving Forced Expiratory Volume in the first second in COVID-19 patients was better than that of conventional treatment [WMD = 0.08(95%CI = 0.02, 0.15), I2 = 52%(p = 0.10)]. Conclusions: Physical activity plays a crucial role in facilitating the recovery of exercise capacity and pulmonary function in COVID-19 patients, helping to expedite the restoration of overall physical health. It is crucial for COVID-19 patients to undergo an accurate assessment of their physical condition before engaging in any physical activity.

Distributed electricity generation technologies, like solar photovoltaic (PV), have achieved rapid development in recent years, but are constrained by some problems such as low marketization and lag in public services. The peer-to-peer (P2P) electricity trading, which allows direct electricity transactions between local consumers and prosumers, has the potential to efficiently distribute the profits coming from self-consumption of PV electricity among all participants. This study proposes a three-layer P2P electricity trading system for communities with high penetration of household distributed PV. The trading system includes a physical layer based on the power grid, an information layer based on a virtual agent network, and a market layer based on a continuous double auction (CDA) mechanism combined with market clearing. By using simulation of trading experiments, a community with 60 houses and 50% PV occupancy is studied as a case. Results show that in one day, 62.5% of the surplus PV electricity of all prosumers actually can be consumed within the community. Through P2P electricity trading of this part of electricity, total incomes of prosumers can increase by 11.5%, and total expense of all users decrease by 7.5%, resulting in that the net expenses of the whole community decrease by 13.8%. It is concluded that P2P electricity trading can unite the whole PV community as a bigger prosumer, and make every residential house in the community share the profits from local PV consumption, which could promote the subsidy-free development and grid parity of household distributed PV in the future.

IntroductionGenome-based analysis is crucial in monitoring antibiotic-resistant bacteria (ARB)and antibiotic-resistance genes (ARGs). Short-read sequencing is typically used to obtain incomplete draft genomes, while long-read sequencing can obtain genomes of multidrug resistance (MDR) plasmids and track the transmission of plasmid-borne antimicrobial resistance genes in bacteria. However, long-read sequencing suffers from low-accuracy base calling, and short-read sequencing is often required to improve genome accuracy. This increases costs and turnaround time.MethodsIn this study, a novel ONT sequencing method is described, which uses the latest ONT chemistry with improved accuracy to assemble genomes of MDR strains and plasmids from long-read sequencing data only. Three strains of Salmonella carrying MDR plasmids were sequenced using the ONT SQK-LSK114 kit with flow cell R10.4.1, and de novo genome assembly was performed with average read accuracy (Q > 10) of 98.9%.Results and DiscussionFor a 5-Mb-long bacterial genome, finished genome sequences with accuracy of >99.99% could be obtained at 75× sequencing coverage depth using Flye and Medaka software. Thus, this new ONT method greatly improves base-calling accuracy, allowing for the de novo assembly of high-quality finished bacterial or plasmid genomes without the need for short-read sequencing. This saves both money and time and supports the application of ONT data in critical genome-based epidemiological analyses. The novel ONT approach described in this study can take the place of traditional combination genome assembly based on short- and long-read sequencing, enabling pangenomic analyses based on high-quality complete bacterial and plasmid genomes to monitor the spread of antibiotic-resistant bacteria and antibiotic resistance genes.

BackgroundTuberculosis (TB) is the deadliest communicable disease in the world with the exception of the ongoing COVID-19 pandemic. Programmed cell death (PCD) patterns play key roles in the development and progression of many disease states such that they may offer value as effective biomarkers or therapeutic targets that can aid in identifying and treating TB patients.Materials and methodsThe Gene Expression Omnibus (GEO) was used to gather TB-related datasets after which immune cell profiles in these data were analyzed to examine the potential TB-related loss of immune homeostasis. Profiling of differentially expressed PCD-related genes was performed, after which candidate hub PCD-associated genes were selected via a machine learning approach. TB patients were then stratified into two subsets based on the expression of PCD-related genes via consensus clustering. The potential roles of these PCD-associated genes in other TB-related diseases were further examined.ResultsIn total, 14 PCD-related differentially expressed genes (DEGs) were identified and highly expressed in TB patient samples and significantly correlated with the abundance of many immune cell types. Machine learning algorithms enabled the selection of seven hub PCD-related genes that were used to establish PCD-associated patient subgroups, followed by the validation of these subgroups in independent datasets. These findings, together with GSVA results, indicated that immune-related pathways were significantly enriched in TB patients exhibiting high levels of PCD-related gene expression, whereas metabolic pathways were significantly enriched in the other patient group. Single cell RNA-seq (scRNA-seq) further highlighted significant differences in the immune status of these different TB patient samples. Furthermore, we used CMap to predict five potential drugs for TB-related diseases.ConclusionThese results highlight clear enrichment of PCD-related gene expression in TB patients and suggest that this PCD activity is closely associated with immune cell abundance. This thus indicates that PCD may play a role in TB progression through the induction or dysregulation of an immune response. These findings provide a foundation for further research aimed at clarifying the molecular drivers of TB, the selection of appropriate diagnostic biomarkers, and the design of novel therapeutic interventions aimed at treating this deadly infectious disease.

Abstract Background Leptospirosis is a significant emerging infectious disease worldwide. Rodents are considered to be the most critical hosts of Leptospira spp. Fujian Province is a region highly endemic for leptospirosis in China. However, the genetic diversity of leptospires circulating among rodents in Fujian is limited. Results The carrier status of rodents for Leptospira spp. was investigated by culture and serological detection in Fujian during 2018–2020. A total of 710 rodents, including 11 species, were trapped, with Rattus losea being the dominant trapped species (50.56%). Fourteen pathogenic Leptospira strains were obtained. Seven L. borgpetersenii serogroup Javanica strains belonging to ST143, 4 L. interrogans serogroup Icterohaemorrhagiae strains belonging to ST1 and ST17, 2 L. interrogans serogroup Bataviae strains belonging to ST96 and ST333, and 1 L. interrogans serogroup Pyrogenes strains belonging to ST332 were identified using 16S rDNA gene sequencing, microscopic agglutination test (MAT) and Multilocus sequence typing (MLST). L. borgpetersenii serogroup Javanica belonging to ST143 was the dominant type (50.00%). A total of 387 rodent serum samples were tested by MAT. Serum were considered positive for seroreactivity at a titer ≥ 1:160 against at least one serovar. A total of 90 (23.26%) serum samples tested positive, and four serogroups were identified, with Javanica being the dominant serogroup (87.78%), which was similar to the dominant serogroup isolated from rodents. This study demonstrates a high prevalence of leptospirosis in rodents and public health education among high-risk workers is highly recommended. Conclusions R. losea was the dominant trapped rodent, and L. borgpetersenii serogroup Javanica ST143 was widely distributed among rodents in Fujian from 2018 to 2020. Despite the low number of isolates obtained from rodents, this study suggests that continuous epidemiological surveillance of the aetiological characteristics of pathogenic Leptospira in wild animal reservoirs may help reduce the possible risk of disease transmission.

Abstract Background The debate of whether machine learning models offer advantages over standard statistical methods when making predictions is ongoing. We discuss the use of a meta-learner model combining both approaches as an alternative. Methods To illustrate the development of a meta-learner, we used a dataset of 187,757 people with depression. Using 31 variables, we aimed to predict two outcomes measured 60 days after initiation of antidepressant treatment: severity of depressive symptoms (continuous) and all-cause dropouts (binary). We fitted a ridge regression and a multi-layer perceptron (MLP) deep neural network as two separate prediction models (“base-learners”). We then developed two “meta-learners”, combining predictions from the two base-learners. To compare the performance across the different methods, we calculated mean absolute error (MAE, for continuous outcome) and the area under the receiver operating characteristic curve (AUC, for binary outcome) using bootstrapping. Results Compared to the best performing base-learner (MLP base-learner, MAE at 4.63, AUC at 0.59), the best performing meta-learner showed a 2.49% decrease in MAE at 4.52 for the continuous outcome and a 6.47% increase in AUC at 0.60 for the binary outcome. Conclusions A meta-learner approach may effectively combine multiple prediction models. Choosing between statistical and machine learning models may not be necessary in practice.

ABSTRACT Corynebacterium striatum has recently received increasing attention due to its multiple antimicrobial resistances and its role as an invasive infection/outbreak agent. Recently, whole-genome sequencing (WGS)-based core genome multilocus sequence typing (cgMLST) has been used in epidemiological studies of specific human pathogens. However, this method has not been reported in studies of C. striatum. In this work, we aim to propose a cgMLST scheme for C. striatum. All publicly available C. striatum genomes, 30 C. striatum strains isolated from the same hospital, and 1 epidemiologically unrelated outgroup C. striatum strain were used to establish a cgMLST scheme targeting 1,795 genes (hereinafter referred to as 1,795-cgMLST). The genotyping results of cgMLST showed good congruence with core genome-based single-nucleotide polymorphism typing in terms of tree topology. In addition, the cgMLST provided a greater discrimination than the MLST method based on 6 housekeeping genes (gyrA, gyrB, hsp65, rpoB, secA1, and sodA). We established a clonal group (CG) threshold based on 104 allelic differences; a total of 56 CGs were identified from among 263 C. striatum strains. We also defined an outbreak threshold based on seven allelic differences that is capable of identifying closely related isolates that could give clues on hospital transmission. According to the results of analysis of drug-resistant genes and virulence genes, we identified CG4, CG5, CG26, CG28, and CG55 as potentially hypervirulent and multidrug-resistant CGs of C. striatum. This study provides valuable genomic epidemiological data on the diversity, resistance, and virulence profiles of this potentially pathogenic microorganism. IMPORTANCE Recently, WGS of many human and animal pathogens has been successfully used to investigate microbial outbreaks. The cgMLST schema are powerful genotyping tools that can be used to investigate potential epidemics and provide classification of the strains precise and reliable. In this study, we proposed the development of a cgMLST typing scheme for C. striatum, and then we evaluated this scheme for its applicability to hospital transmission investigations. This report describes the first cgMLST schema for C. striatum. The analysis of hospital transmission of C. striatum based on cgMLST methods has important clinical epidemiological significance for improving nosocomial infection monitoring of C. striatum and in-depth understanding of its nosocomial transmission routes.

Abstract Background Donepezil, galantamine, rivastigmine and memantine are potentially effective interventions for cognitive impairment in dementia, but the use of these drugs has not been personalised to individual patients yet. We examined whether artificial intelligence-based recommendations can identify the best treatment using routinely collected patient-level information. Methods Six thousand eight hundred four patients aged 59–102 years with a diagnosis of dementia from two National Health Service (NHS) Foundation Trusts in the UK were used for model training/internal validation and external validation, respectively. A personalised prescription model based on the Recurrent Neural Network machine learning architecture was developed to predict the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores post-drug initiation. The drug that resulted in the smallest decline in cognitive scores between prescription and the next visit was selected as the treatment of choice. Change of cognitive scores up to 2 years after treatment initiation was compared for model evaluation. Results Overall, 1343 patients with MMSE scores were identified for internal validation and 285 [21.22%] took the drug recommended. After 2 years, the reduction of mean [standard deviation] MMSE score in this group was significantly smaller than the remaining 1058 [78.78%] patients (0.60 [0.26] vs 2.80 [0.28]; P = 0.02). In the external validation cohort (N = 1772), 222 [12.53%] patients took the drug recommended and reported a smaller MMSE reduction compared to the 1550 [87.47%] patients who did not (1.01 [0.49] vs 4.23 [0.60]; P = 0.01). A similar performance gap was seen when testing the model on patients prescribed with AChEIs only. Conclusions It was possible to identify the most effective drug for the real-world treatment of cognitive impairment in dementia at an individual patient level. Routine care patients whose prescribed medications were the best fit according to the model had better cognitive performance after 2 years.

Some serovars of Salmonella are not or rare found to cause salmonellosis in human. In our clinic-based surveillance, three rare Salmonella 4,5,12:a:- strains were recovered from three patients with diarrhea. To explore their genetic and epidemiological characteristics and pathogenesis, we conducted whole-genome sequencing, in vitro invasion assays in mammalian cells, and in vivo virulence assays in an animal model. The three isolates had indistinguishable molecular patterns and similar genome sequences, and clustered together with an isolate from edible fish traded among countries. The isolates had biochemical reactions identical with those of Salmonella subspecies enterica but belonged to subspecies salamae according to genome phylogeny, revealing a new serovar, S. enterica subsp. II serovar 4,5,12:a:-. The strains contained multiple virulence genes, elicited temporary bacteremia and enteritidis and caused cell damage in the mouse liver and cecum. This study provides evidence that this new Salmonella salamae serovar can infect humans and cause clusters of cases, and whole-genome sequencing detection and surveillance of Salmonella can help to accurately define Salmonella classification and clonality, improve diagnosis, facilitate outbreak detection and aid in the source tracing of salmonellosis epidemics.

Vibrio fluvialis is a halophilic Gram-negative bacterium regarded as an emerging unusual enteric pathogen of increasing public health concern. Our previous work has identified two type VI secretion systems (T6SSs) in V. fluvialis, VflT6SS1, and VflT6SS2, and the latter is functional in mediating interbacterial competitiveness. However, its antibacterial effectors remain to be clarified. In this work, we focused on a new potential effector/immunity pair TssI2/TsiI2. Bioinformatics analysis revealed that the C-terminal domain of TssI2 belongs to a widespread family of pesticin, and its antibacterial toxicity and corresponding protection by TsiI2 were proved via bacterial killing assays, and their action sites were localized to the periplasm of bacterial cells. The interaction of TssI2 and TsiI2 was demonstrated by the bacterial adenylate cyclase two-hybrid, protein pull-down and isothermal titration calorimetry assays. Site-directed mutagenesis demonstrated that, in addition to Glu-844, Thr-863, and Asp-869, which correspond to three reported residues in pesticin of Yersinia pestis, additional residues including Phe-837, Gly-845, Tyr-851, Gly-867, Gln-963, Trp-975, and Arg-1000 were also proved to be crucial to the bactericidal activity of TssI2. Muramidase/lysozyme-related peptidoglycan (PG) hydrolase activities of TssI2 and its variants were validated with permeabilized Escherichia coli cells and purified PG substrate. Based on sequence homologies at C-terminals in various V. fluvialis isolates, TssI2 was subdivided into five clusters (12–22% identity among them), and the antibacterial activities of representative effectors from other four Clusters were also confirmed through periplasmic over-expression in E. coli host. Two selected cognate immunities were proved to confer protection against the toxicities of their effectors. Additionally, TsiI2, which belongs to Cluster I, exhibited cross-protection to effector from Cluster V. Together, current findings expand our knowledge of the diversity and consistency of evolved VgrG effectors in V. fluvialis and on how VflT6SS2 mediates a competitive advantage to gain a better survival.

The structures of social networks with power laws have been widely investigated. People have a great interest in the scale-invariant generating mechanism. We address this problem by introducing a simple model, i.e., a heuristic probabilistic explanation for the occurrence of a power law. In particular, the proposed model can be used to explain the generative mechanism that leads to the scale-invariant of the degree distribution with a power exponent of τ>2. Furthermore, a stochastic model (the pure birth points process) is used to describe the cumulative growth trend of edges of a temporal social network. We applied our model to online temporal social networks and found that both the degree distribution scaling behaviors and the growth law of edges can be quantitatively reproduced. We gained further insight into the evolution nature of scale-invariant temporal social networks from the empirical observation that the power exponent τ gradually decreases and approaches 2 or less than 2 over evolutionary time.

We consider the problem of scheduling jobs on a single machine subject to an uncertain breakdown to minimize the flowtime. Assuming the machine is unavailable during the breakdown, the starting time of the breakdown is a random variable s with distribution function D(s) and the terminating time of the breakdown has no any other information; jobs are non-resumable. Under these assumptions and starting from the perspective of statistical optimization, we first establish the scheduling problem HSONRP, which contains deterministic information, stochastic information, and online information and then define the expected competitive ratio of an algorithm to find the optimized solution of the problem HSONRP. In addition, then, we propose and prove certain results on the expected competitive ratio of the SPT rule. In particular, we prove the expected competitive ratio of SPT rule is less than 1+max{pi}2P when s is the uniform distribution on interval (0,P], where pi is the processing time of job i, P=∑i=1npi, and show that it is no more than 54 under a quite loose condition. Meanwhile, we also make some discussions about our studies. What we have performed will enrich and improve the research results on the area of scheduling to minimize flowtime and advance the development of online optimization and stochastic optimization.

ABSTRACT Nocardia cyriacigeorgica is a common etiological agent of nocardiosis that has increasingly been implicated in serious pulmonary infections, especially in immunocompromised individuals. However, the evolution, diversity, and pathogenesis of N. cyriacigeorgica have remained unclear. Here, we performed a comparative genomic analysis using 91 N. cyriacigeorgica strains, 45 of which were newly sequenced in this study. Phylogenetic and average nucleotide identity (ANI) analyses revealed that N. cyriacigeorgica contained five species-level clades (8.6 to 14.6% interclade genetic divergence), namely, the N. cyriacigeorgica complex (NCC). Further pan-genome analysis revealed extensive differences among the five clades in nine functional categories, such as energy production, lipid metabolism, secondary metabolites, and signal transduction mechanisms. All 2,935 single-copy core genes undergoing purifying selection were highly conserved across NCC. However, clades D and E exhibited reduced selective constraints, compared to clades A to C. Horizontal gene transfer (HGT) and mobile genetic elements contributed to genomic plasticity, and clades A and B had experienced a higher level of HGT events than other clades. A total of 129 virulence factors were ubiquitous across NCC, such as the mce operon, hemolysin, and type VII secretion system (T7SS). However, different distributions of three toxin-coding genes and two new types of mce operons were detected, which might contribute to pathogenicity differences among the members of the NCC. Overall, our study provides comprehensive insights into the evolution, genetic diversity, and pathogenicity of NCC, facilitating the prevention of infections. IMPORTANCE Nocardia species are opportunistic bacterial pathogens that can affect all organ systems, primarily the skin, lungs, and brain. N. cyriacigeorgica is the most prevalent species within the genus, exhibits clinical significance, and can cause severe infections when disseminated throughout the body. However, the evolution, diversity, and pathogenicity of N. cyriacigeorgica remain unclear. Here, we have conducted a comparative genomic analysis of 91 N. cyriacigeorgica strains and revealed that N. cyriacigeorgica is not a single species but is composed of five closely related species. In addition, we discovered that these five species differ in many ways, involving selection pressure, horizontal gene transfer, functional capacity, pathogenicity, and antibiotic resistance. Overall, our work provides important clues in dissecting the evolution, genetic diversity, and pathogenicity of NCC, thereby advancing prevention measures against these infections.

ABSTRACT Cefiderocol has been approved in the United States and Europe but not in China. We aim to evaluate carbapenem-resistant Enterobacterales (CRE) susceptibility to cefiderocol to provide baseline data and investigate the resistance mechanism. From 2018 to 2019, 1,158 CRE isolates were collected from 23 provinces and municipalities across China. The MICs of antimicrobials were determined via the agar dilution and broth microdilution methods. Whole-genome sequencing was performed for 26 cefiderocol-resistant Escherichia coli isolates to investigate the resistance mechanism. Clone transformations were used to explore the function of cirA, pbp3, and blaNDM-5 in resistance. Among the 21 antimicrobials tested, aztreonam-avibactam had the highest antibacterial activity (98.3%), followed by cefiderocol (97.3%) and colistin (95.3%). A total of 26 E. coli isolates harboring New Delhi metallo-beta-lactamase 5 (NDM-5) showed high levels of cefiderocol resistance, of which sequence type 167 (ST167) accounted for 76.9% (20/26). We found 4 amino-acid insertions (YRIN/YRIK) at position 333 of penicillin-binding protein 3 (PBP3) in the 26 E. coli isolates, and 22 isolates had a siderophore receptor cirA premature stop codon. After obtaining the wild-type cirA supplementation, the MIC of the transformants decreased by 8 to 16 times in two cefiderocol-resistant isolates. A cefiderocol-susceptible isolate harboring NDM-5 has an MIC increased from 1 μg/mL to 64 μg/mL after cirA deletion, and the MIC decreased from 64 μg/mL to 0.5 μg/mL after blaNDM-5 deletion. The MIC of the E. coli DH5α, from which the pbp3 mutant was obtained, increased from 0.064 μg/mL to 0.25 μg/mL. Cefiderocol showed activity against most CRE in China. The resistance of ST167 E. coli to cefiderocol is a combination of the premature stop codon of cirA, pbp3 mutation, and blaNDM-5 existence. IMPORTANCE Cefiderocol, a new siderophore cephalosporin, has been approved in the United States and Europe but not in China. At present, there are almost no antimicrobial susceptibility evaluation data on cefiderocol in China. We evaluated the in vitro susceptibility of 1,158 strains of carbapenem-resistant Enterobacterales to cefiderocol and other antibiotics. We found that a high proportion of Escherichia coli showed high-level resistance to cefiderocol. Whole-genome sequencing (WGS) and molecular cloning experiments confirmed that the synergistic effect of the cirA gene premature stop codon, blaNDM-5 existence, and the pbp3 mutation is associated with high levels of cefiderocol resistance.

There is a growing demand for rapid, sensitive, field-deployable nucleic acid tests for cholera, which usually occurs in rural areas. In this study, we developed a Cas12a-assisted rapid isothermal detection (CARID) system for the detection of toxigenic V. cholerae serogroups O1 and O139 by combining recombinase-aided amplification and CRISPR-Cas (clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins). The results can be determined by fluorescence signal and visualized by lateral flow dipstick. We identified 154 V. cholerae strains and 129 strains of other intestinal diarrheagenic bacteria with a 100% coincidence rate. The limit of detection of CARID was 20 copies/reaction of V. cholerae genomic DNA, which is comparable to that of polymerase chain reaction (PCR) and qPCR. Multiple-CARID was also established for efficiency and economic considerations with an acceptable decrease in sensitivity. Simulated sample tests showed that CARID is suitable for complex samples. In conclusion, CARID is a rapid, sensitive, economically efficient, and portable method for the detection of V. cholerae, which makes it suitable for field responses to cholera.

ABSTRACT The opportunistic pathogen Pseudomonas aeruginosa often adapts to its host environment and causes recurrent nosocomial infections. The extracytoplasmic function (ECF) sigma factor enables bacteria to alter their gene expression in response to host environmental stimuli. Here, we report an ECF sigma factor, HxuI, which is rapidly induced once P. aeruginosa encounters the host. Host stresses such as iron limitation, oxidative stress, low oxygen, and nitric oxide induce the expression of hxuI. By combining RNA-seq and promoter-lacZ reporter fusion analysis, we reveal that HxuI can activate the expression of diverse metabolic and virulence pathways which are critical to P. aeruginosa infections, including iron acquisition, denitrification, pyocyanin synthesis, and bacteriocin production. Most importantly, overexpression of the hxuI in the laboratory strain PAO1 promotes its colonization in both murine lung and subcutaneous infections. Together, our findings show that HxuI, a key player in host stress-response, controls the in vivo adaptability and virulence of P. aeruginosa during infection. IMPORTANCE P. aeruginosa has a strong ability to adapt to diverse environments, making it capable of causing recurrent and multisite infections in clinics. Understanding host adaptive mechanisms plays an important guiding role in the development of new anti-infective agents. Here, we demonstrate that an ECFσ factor of P. aeruginosa response to the host-inflicted stresses, which promotes the bacterial in vivo fitness and pathogenicity. Furthermore, our findings may help explain the emergence of highly transmissible strains of P. aeruginosa and the acute exacerbations during chronic infections.

A case of Rickettsia sibirica subspecies sibirica BJ-90 infection in China was identified by metagenomic analysis of an eschar biopsy specimen and confirmed by nested PCR. Seroprevalence of spotted fever group Rickettsia was ≈17.4% among the local population. This report highlights the threat of rickettsioses to public health in the Qinghai–Tibet Plateau.

Abstract Background Members of the genus Proteus are mostly opportunistic pathogens that cause a variety of infections in humans. The molecular evolutionary characteristics and genetic relationships among Proteus species have not been elucidated to date. In this study, we developed a multilocus sequence analysis (MLSA) approach based on five housekeeping genes (HKGs) to delineate phylogenetic relationships of species within the genus Proteus. Results Of all 223 Proteus strains collected in the current study, the phylogenetic tree of five concatenated HKGs (dnaJ, mdh, pyrC, recA and rpoD) divided 223 strains into eleven clusters, which were representative of 11 species of Proteus. Meanwhile, the phylogenetic trees of the five individual HKGs also corresponded to that of the concatenated tree, except for recA, which clustered four strains at an independent cluster. The evaluation of inter- and intraspecies distances of HKG concatenation indicated that all interspecies distances were significantly different from intraspecies distances, which revealed that these HKG concatenations can be used as gene markers to distinguish different Proteus species. Further web-based DNA-DNA hybridization estimated by genome of type strains confirmed the validity of the MLSA, and each of eleven clusters was congruent with the most abundant Proteus species. In addition, we used the established MLSA method to identify the randomly collected Proteus and found that P. mirabilis is the most abundant species. However, the second most abundant species is P. terrae but not P. vulgaris. Combined with the genetic, genomic and phenotypic characteristics, these findings indicate that three species, P. terrae, P. cibarius and Proteus genospecies 5, should be regarded as heterotypic synonyms, and the species should be renamed P. terrae, while Proteus genospecies 5 has not been named to date. Conclusions This study suggested that MLSA is a powerful method for the discrimination and classification of Proteus at the species level. The MLSA scheme provides a rapid and inexpensive means of identifying Proteus strains. The identification of Proteus species determined by the MLSA approach plays an important role in the clinical diagnosis and treatment of Proteus infection.

Huangjiu is a national alcoholic beverage in China. Millet has congenital advantages in development and utilization of nutrient. Brewing Huangjiu with millet can increase the value of millet. Microbial community plays crucial roles in millet Huangjiu fermentation. Flavor compounds reflect the quality and health function of Huangjiu. The flavor compounds of Huangjiu are complex and their formation is closely associated with microorganisms, but the relationship between them during fermentation has been unknown. In this research, this relationship during millet Huangjiu fermentation were deeply investigated. Totally 86 volatile compounds were detected. Bacillus, Weissella, Paenibacillus, Klebsiella, Prevotella was investigated as the dominant microbes through high-throughput sequencing. 537 correlations between major flavor compounds and microbes were established to reflect the dynamic change during millet Huangjiu fermentation. The top five dominant genus of flavor producing microbes were Chryseobacterium, Sporolactobacillus, Psychrobacter, Sphingobium and Anoxybacillus. The content of malic acid and citric acid was gradually improved all through the millet Huangjiu fermentation. Malic acid and citric acid generated from millet Huangjiu fermentation shows healthy properties as liver protection and eliminating fatigue. Our research provides essential information on microbial community succession and the flavor formation during millet Huangjiu fermentation, and beneficial for development of Huangjiu products.

Objective. This study aimed to evaluate whether the site of C7 neurotomy affects spinal cord glial cell activation and pain-related behavior on the paralyzed side in a rat stroke model. Methods. After middle cerebral artery occlusion (MCAO) was induced in male Sprague-Dawley rats, they underwent C7 neurotomy 0, 2, and 4 mm distal to the intervertebral foramen on the paralyzed side. Pain-related behavior and immunofluorescence examination of spinal cord glial cell activation in the ipsilateral C7 dorsal horn were evaluated. Results. Mechanical paw withdrawal threshold (MPWT) was lower, and the number of microglia and astrocytes (/mm2) was higher as the distance between the site of C7 neurotomy and the intervertebral foramen decreased from 4 mm to 0. Conclusion. The site of C7 neurotomy affects MPWT and spinal cord glial proliferation in rats with MCAO. Nerve division closer to intervertebral foramen resulted in lower MPWT and higher degree of glial proliferation in the spinal cord.

Objective: To summarize our experiences with drainage methods after laparoscopic pyeloplasty with a 14-year study.Methods: We reviewed the data of the 838 children operated on for hydronephrosis due to congenital ureteropelvic junction obstruction (UPJO) between July 2007 and July 2020. Patients' demographics, perioperative details, postoperative drainage stents [including double-J stent, percutaneous trans-anastomotic (PU) stent, and trans-uretero-cystic external urethral stent (TEUS)], complications, hospital stay, and long-term follow-up outcomes were analyzed. Long-term follow-up was performed by outpatient visits and telephone follow-up. Moreover, we reviewed the details of nine cases of recurrence after laparoscopic pyeloplasty.Results: Comparison of preoperative general data among the three groups indicated that there was no statistical difference in age, gender, and surgical side of the three groups. Statistical differences were found in the incidence of postoperative complications from the three postoperative drainage method groups, especially the incidence of reoperations (p < 0.01): there were six cases (3.19%) of recurrences in the TEUS group, two cases (0.36%) in the DJ group, and one case (0.93%) in the PU group. In the six recurrent cases from the TEUS group, four cases (44.4%) were found to have stenosis, and two cases (22.2%) have iatrogenic valvular formation.Conclusion: Not all three types of drainage methods are suitable for drainage after pyeloplasty. Based on our findings, TEUS is not recommended.

Remarkable clinical benefits in several advanced cancers are observed under the treatment of immune checkpoint inhibitor (ICI) agents. However, only a smaller proportion of patients respond to the treatments. Reelin (RELN) is frequently mutated in the cancer genome. In this study, the RELN mutation association with ICI treatment efficacy in melanoma and non-small cell lung cancer (NSCLC) was elucidated. Data from 631 melanoma and 109 NSCLC patients with both ICI treatment data and pre-treatment mutational profiles were collected. In addition, from the Cancer Genome Atlas (TCGA) project, we also obtained both tumors to explore the immunologic features behind RELN mutations. Melanoma patients with RELN mutations exhibited a favorable ICI survival benefit when compared with wild-type patients (HR: 0.66, 95% CI: 0.51–0.87, p = 0.003). A higher response rate was also noticed in RELN-mutated patients (38.9% vs. 28.3%, p = 0.017). The association of RELN mutations with a preferable immunotherapy outcome and response was further confirmed in NSCLC. Further exploration demonstrated that favorable immunocyte infiltration and immune response signaling pathways were found in patients with RELN mutations. In this study, RELN mutations were identified to connect with a better immune microenvironment and an improved ICI efficacy in melanoma and NSCLC, which provides a potential biomarker for immunological feature evaluation and immunotherapeutic outcome prediction at the molecular level.

Nocardia is a complex and diverse genus of aerobic actinomycetes that cause complex clinical presentations, which are difficult to diagnose due to being misunderstood. To date, the genetic diversity, evolution, and taxonomic structure of the genus Nocardia are still unclear. In this study, we investigated the pan-genome of 86 Nocardia type strains to clarify their genetic diversity. Our study revealed an open pan-genome for Nocardia containing 265,836 gene families, with about 99.7% of the pan-genome being variable. Horizontal gene transfer appears to have been an important evolutionary driver of genetic diversity shaping the Nocardia genome and may have caused historical taxonomic confusion from other taxa (primarily Rhodococcus, Skermania, Aldersonia, and Mycobacterium). Based on single-copy gene families, we established a high-accuracy phylogenomic approach for Nocardia using 229 genome sequences. Furthermore, we found 28 potentially new species and reclassified 16 strains. Finally, by comparing the topology between a phylogenomic tree and 384 phylogenetic trees (from 384 single-copy genes from the core genome), we identified a novel locus for inferring the phylogeny of this genus. The dapb1 gene, which encodes dipeptidyl aminopeptidase BI, was far superior to commonly used markers for Nocardia and yielded a topology almost identical to that of genome-based phylogeny. In conclusion, the present study provides insights into the genetic diversity, contributes a robust framework for the taxonomic classification, and elucidates the evolutionary relationships of Nocardia. This framework should facilitate the development of rapid tests for the species identification of highly variable species and has given new insight into the behavior of this genus.