The pursuit of high energy density in lithium batteries has driven the development of efficient electrodes with low levels of inactive components. Herein, a facile approach involving the use of π-π stacked nigrosine@carbon nanotube nanocomposites as an all-in-one additive for a LiFePO
Impulse-radio(IR)-based Ultra-wide band (UWB) technology has great potential in the fields of positioning, target detection and data transfer due to its significant advantages. In this paper, the ability of UWB to perceive different transmission environment is discussed. Four scenarios are simulated using finite-difference time-domain (FDTD) method. There are three NLOS(obstacle are concrete wall, glass wall, wood wall respectively)scenarios and one LOS scenario. Representative parameters are extracted from the UWB's channel models, and are sent into a support vector machine(SVM) to classify those scenarios. The results show that these scenarios can be classified with proper SVM parameters.
Abstract Background Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity, mortality, and sequelae in childhood. Metagenomic next-generation sequencing (mNGS) can potentially improve IM outcomes by sequencing both pathogen and host responses and increasing the diagnosis accuracy. Methods Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL). Results Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM. Conclusions This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.
Tumors are driven by a sequence of genetic and epigenetic alterations. Previous studies have mostly focused on the roles of somatic mutations in tumorigenesis, but how germline variants act is largely unknown. In this study, we screened Single Nucleotide Polymorphisms (SNPs) as a representative of germline mutations. By using RNA sequencing data of lung cancer and paired normal tissues, we analyzed the effects of SNP types, functions and conservativeness on genes with Allele expression imbalance (AEI). We found that natural selection can act on AEI. Functional adaptability of high frequency AEI genes and correlation of AEI incidence with conservativeness were observed in both adjacent tissues and tumor tissues. Moreover, we observed higher AEI incidence of genes with nonsynonymous SNP than those with synonymous SNP. However, we also found that AEI was affected by the allele expression noise, especially in tumor tissues, which led to increased AEI proportion, weakened role of natural selection and disappearance of the influence of SNP types on AEI. We unveiled a previously unknown adaptive regulatory mechanism that natural selection on SNPs can be reflected in allelic expression, which provides insight into better understanding of cancer evolution.
Objective
To understand the epidemiological characteristics, genomic variations and macrolide resistance of Bordetella pertussis (B.pertussis)strains circulating in Shenzhen with clinical data analysis, genotype profiling, phylogenetic analysis and antimicrobial susceptibility test.
Methods
Clinical data of patients with pertussis in Shenzhen Children′s Hospital were collected from the electronic medical record system. Genome sequences of 31 B. pertussis isolates were analyzed with next-generation sequencing and de novo assembled. Multilocus sequence typing (MLST) was performed to identify their sequences types. Sequence alignment by BLASTn was used to identify virulence genotypes and mutations in 23S rRNA gene. A phylogenetic tree was constructed to analyze the relationships among them. E-test was used to identify macrolide resistance.
Results
All of the 31 B. pertussis strains were identified as sequence type-2 (ST-2) by MLST with diverse virulence genotypes. Two were prn-deficient strains. Based on the phylogenetic tree, all of the isolates were distant from vaccine strains. Nineteen isolates were resistant to erythromycin with A2047G mutation in 23S rRNA.
Conclusions
The virulence genotypes of B. pertussis strains in Shenzhen were diverse with increasing non-vaccine genotypes. Macrolide-resistant strains were prevalent. This study might provide reference for improving the prevention, management and vaccination strategy of pertussis.
Key words:
Bordetella pertussis; Next-generation sequencing; Genotype; Macrolide resistance
In China, conventional genetic testing methods can only detect common thalassemia variants. Accurate detection of rare thalassemia is crucial for clinical diagnosis, especially for children that need long-term blood transfusion. This study aims to explore the application value of third-generation sequencing (TGS) in the diagnosis of rare thalassemia in children with anemia.We enrolled 20 children with anemia, excluding from iron deficiency anemia (IDA). TGS was employed to identify both known and novel thalassemia genotypes, while sanger sequencing was used to confirm the novel mutation detected.Among the 20 samples, we identified 5 cases of rare thalassemia. These included β-4.9 (hg38,Chr11:5226187-5231089) at HBB gene, α-91(HBA2:c.*91delT), αCD30(HBA2:c.91-93delGAG), Chinese Gγ+(Aγδβ)0(NG_000007.3: g .48795-127698 del 78904) and delta - 77(T > C)(HBD:c.-127T>C). Notably, the -SEA/α-91α genotype associated with severe non-deletional hemoglobin H disease (HbH disease) has not been previously reported. Patients with genotypes β654/β-4.9 and -SEA/α-91α necessitate long-term blood transfusions, and those with the -SEA/αCD30α, Chinese Gγ+(Aγδβ)0 and delta thalassemia demonstrate mild anemia.TGS demonstrates promising potential as a diagnostic tool for suspected cases of rare thalassemia in children, especially those suspected to have transfusion-dependent thalassemia (TDT).
2D COFs with kagome-topology are synthesized using 4-connected D 2h -symmetric and 2-connected non-centrosymmetric C 2 -symmetric building blocks, showcasing remarkable photothermal imaging performance.
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