Search

BACKGROUND. Current methods for the detection and surveillance of bladder cancer (BCa) are often invasive and/or possess suboptimal sensitivity and specificity, especially in early-stage, minimal, and residual tumors. METHODS. We developed an efficient method, termed utMeMA, for the detection of urine tumor DNA methylation at multiple genomic regions by MassARRAY. We identified the BCa-specific methylation markers by combined analyses of cohorts from Sun Yat-sen Memorial Hospital (SYSMH), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) database. The BCa diagnostic model was built in a retrospective cohort (n = 313) and validated in a multicenter, prospective cohort (n = 175). The performance of this diagnostic assay was analyzed and compared with urine cytology and FISH. RESULTS. We first discovered 26 significant methylation markers of BCa in combined analyses. We built and validated a 2-marker-based diagnostic model that discriminated among patients with BCa with high accuracy (86.7%), sensitivity (90.0%), and specificity (83.1%). Furthermore, the utMeMA-based assay achieved a great improvement in sensitivity over urine cytology and FISH, especially in the detection of early-stage (stage Ta and low-grade tumor, 64.5% vs. 11.8%, 15.8%), minimal (81.0% vs. 14.8%, 37.9%), residual (93.3% vs. 27.3%, 64.3%), and recurrent (89.5% vs. 31.4%, 52.8%) tumors. The urine diagnostic score from this assay was better associated with tumor malignancy and burden. CONCLUSION. Urine tumor DNA methylation assessment for early diagnosis, minimal, residual tumor detection and surveillance in BCa is a rapid, high-throughput, noninvasive, and promising approach, which may reduce the burden of cystoscopy and blind second surgery. FUNDING. This study was supported by the National Key Research and Development Program of China and the National Natural Science Foundation of China., Introduction Bladder cancer (BCa) is the most common malignancy of the urinary system, with an estimated roughly 549,393 new cases and approximately 199,922 deaths worldwide each year (1). Approximately 75% [...]

As one of the crucial components of the gearbox in the car,the Shafting-Yoke’s fatigue life directly affects the performance of the gearbox. The Shafting-Yoke of the manual transmission is taken as the research object,which adopting finite element software to analysis its fatigue stress and employing the dynamic simulation software to obtain its load spectrum. A method combining based on GL code predicting material S-N curve and Goodman mean stress correction was developed to calculate the fatigue life of Shafting-Yoke. The fatigue test of Shafting-Yoke shows that the location of damage and the fatigue life of ShaftingYoke of computer simulation and protracted-test are basically same,which proves the reliability and practicability of method promoted in this paper,it can play a guiding role for structure design and optimization of Shafting-Yoke.

Highly active, durable, and cost‐effective electrodes for hydrogen evolution reaction (HER) at ultrahigh current densities (≥1 A cm−2) are extremely demanded for industrial high‐rate hydrogen production, but challenging. Here, a robust strongly coupled Ag(S)@NiO/nickel foam (NF) electrode is reported. Taking advantage of millisecond laser direct writing in liquid nitrogen technique, lattice‐matched and coherent interfaces are formed between Ag nanoparticles with stacking faults (denoted by Ag(S)) and NiO nanosheets, leading to strong interfacial electronic coupling, not only promoting H2O adsorption and dissociation on Ni2+ but also enhancing H* adsorption on intrinsically inactive but most electrically conductive Ag. Strong chemical bonding is established at NiO/NF interface, guaranteeing rapid electron transfer and excellent mechanical durability under high‐rate hydrogen evolution. The physicochemically stable electrode achieves record‐low alkaline HER overpotential of 167 and 180 mV at 1 and 1.5 A cm−2, respectively, along with negligible activity decay after 120 h test at ≈1.5 A cm−2, surpassing reported non‐platinum group metal electrocatalysts. [ABSTRACT FROM AUTHOR]

The gut microbiota play an important role in digestion, development, nutritional metabolism and detoxification in insects. The rice stem borer, Chilo suppressalis, is one of the most destructive rice pests and has caused serious economic losses to major rice‐producing areas of China. However, little is known about how its gut microbiota has adapted to different geographical environments. We investigated the gut microbiota of C. suppressalis populations collected from five sites in the typical areas of northern China using 16S rDNA gene sequencing on an Illumina MiSeq platform. In total, 453,853,707 reads and 1650 operational taxonomic units (OTUs) in 25 gut samples of C. suppressalis were obtained. We identified 697 bacterial genera from 30 phyla, and Proteobacteria and Firmicutes were the most dominant phyla. Gut bacterial richness and alpha‐diversity metrics revealed no significant differences among these populations. We detected the highest bacterial diversity in Beizhen, western Liaoning Province. Principal coordinates analysis (PCoA) and clustering analysis (UPGMA) showed no distinct gut microbial community structure of C. suppressalis in these regions. Linear discriminant analysis (LDA) effect size (LEfSe) indicated that the bacterial species exhibited significant differences among the middle, northern and western regions. Finally, PICRUSt analysis demonstrated that microbial functions closely associated with the gut microbiome mainly included membrane transport, amino acid metabolism and carbohydrate metabolism. Accordingly, our study provided important insights into the investigation of insect‐bacteria symbioses and evaluated gut microorganisms as biocontrol agents for this pest and other agricultural lepidopterans. [ABSTRACT FROM AUTHOR]