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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.

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.