Prevalence of the metabolic syndrome in Chinese adolescents

Since national figures on the occurrence of metabolic syndrome among Chinese adolescents are lacking, this study aims to estimate its prevalence and distribution among Chinese youngsters. The 2002 China National Nutrition and Health Survey is a nationally representative cross-sectional study. Applying the criteria for US adolescents, we estimated the prevalence of metabolic syndrome among 2761 adolescents aged 15 to 19 years. The prevalence of metabolic syndrome among Chinese adolescents overall was 3·7% (10% in US adolescents). It was 35·2 %, 23·4% and 2·3% among adolescents who were overweight (BMI $95th percentile), at risk of overweight (BMI between 85th and 95th percentile) and normal weight (BMI below the 85th percentile), respectively. Urban boys had the highest rate (5·8$85th percentile and one or two parent(s) with metabolic syndrome, the prevalence was 46·4 %. A total of 96% of overweight adolescents had at least one and 74·1% overweight adolescents had at least two abnormalities of metabolic syndrome. Based on these figures, it is estimated that more than three million Chinese adolescents have metabolic syndrome. Both overweight and metabolic syndrome prevalence among adolescents are still relatively low in China, but the prevalence of metabolic syndrome among Chinese overweight adolescents is similar to those living in the USA

Improved Draft Genome Sequence of Microbacterium sp. Strain LKL04, a Bacterial Endophyte Associated with Switchgrass Plants.

We report here the genome assembly and analysis of Microbacterium strain sp. LKL04, a Gram-positive bacterial endophyte isolated from switchgrass plants (Panicum virgatum) grown on a reclaimed coal-mining site. The 2.9-Mbp genome of this bacterium was assembled into a single contig encoding 2,806 protein coding genes

Probing higher-spin particles with gravitational waves from compact binary inspirals

Under the framework of gravitational effective field theory, we propose a theory agnostic strategy of searching for higher-spin particles with gravitational waves from compact binary inspirals. Using this strategy, we analyze gravitational wave signals from the binary black hole merger events GW151226 and GW170608, as well as the binary neutron star merger event GW170817. We find that the existence of higher-spin particles with mass ranged from $10^{-12} {\rm eV}$ to $10^{-11} {\rm eV}$ is strongly disfavored by these events unless the particles precisely combine within a supersymmetric supermultiplet. We argue that the gravitational effective field theory also provides a framework to search for signals beyond GR from other GW observations, such as extreme-mass-ratio-inspirals.Comment: 6 pages, 2 figure

Compact Dual-Band Planar Inverted-e-Shaped Antenna Using Defected Ground Structure

This paper presents a novel dual-band planar inverted-e-shaped antenna (PIEA) using defected ground structure (DGS) for Bluetooth and wireless local area network (WLAN) applications. The PIEA can reduce electromagnetic interferences (EMIs) and it is constructed on a compact printed circuit board (PCB) size of 10 × 5 × 4 mm3. Experimental results indicate that the antenna with a compact meandered slit can improve the operating impedance matching and bandwidths at 2.4 and 5.5 GHz. The measured power gains at 2.4 and 5.5 GHz band are 1.99 and 3.71 dBi; antenna efficiencies are about 49.33% and 55.23%, respectively. Finally, the good performances of the proposed antenna can highly promote for mobile device applications

An on-line sample pretreatment technique for the HPLC analysis of plant samples.

A continuous-flow, on-line sample pretreatment technique using a silica gel microsyringe extractor has been developed. All steps including extraction, separation, clean-up, and concentration occur in the microsyringe. The overall sample pretreatment process takes 0.99. Complex plant samples of Sambucus Mandshurica Kitag have been tested using this method. Fluorene, phenanthrene, pyrene, and plant hormones were detected in all the samples, and concentrations ranged from 24.2–34.9, 43.8–67.1, 25.9–29.2, and 14.5∼110.8 ng/g, respectively

Gas-Purged Headspace Liquid Phase Microextraction System for Determination of Volatile and Semivolatile Analytes

In order to achieve rapid, automatic, and efficient extraction for trace chemicals from samples, a system of gas-purged headspace liquid phase microextraction (GP-HS-LPME) has been researched and developed based on the original HS-LPME technique. In this system, semiconductor condenser and heater, whose refrigerating and heating temperatures were controlled by microcontroller, were designed to cool the extraction solvent and to heat the sample, respectively. Besides, inert gas, whose gas flow rate was adjusted by mass flow controller, was continuously introduced into and discharged from the system. Under optimized parameters, extraction experiments were performed, respectively, using GP-HS-LPME system and original HS-LPME technique for enriching volatile and semivolatile target compounds from the same kind of sample of 15 PAHs standard mixture. GC-MS analysis results for the two experiments indicated that a higher enrichment factor was obtained from GP-HS-LPME. The enrichment results demonstrate that GP-HS-LPME system is potential in determination of volatile and semivolatile analytes from various kinds of samples

Genomic profiling and immune landscape of olfactory neuroblastoma in China

BackgroundOlfactory neuroblastoma (ONB) is a rare malignant neoplasm of the olfactory mucosa. The paucity of genomic data has prevented the development of individualized ONB treatments. Here, we investigated the genomic and immune landscape of ONB in Chinese patients.MethodsWhole exome sequencing (WES) and multiplex immunofluorescence (MIF) analysis were performed on tissue samples from 19 Chinese ONB patients. Patients were divided into low- and high-grade groups.ResultsOverall, 929 nonsynonymous alterations were identified in 18 (94.74%) ONB cases. The most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one case expressed PD-L1 (> 1%) in the tumor region. The percentage of CD8+ tumor-infiltrating lymphocytes (TILs) in the tumor region ranged from 0.03% to 84.9%, with a median of 1.08%. No significant differences were observed between the low- and high-grade groups for clinicopathological features, mutant genes, mutant pathways, TMB, tumor neoantigen burden (TNB), mutant-allele tumor heterogeneity (MATH), PD-L1 expression levels, or CD8+ TIL percentage. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. Notably, CD68+CD163- macrophages accounted for an average of 80.5% of CD68+ macrophages.ConclusionThis study presents data on the genomic and immune landscape of ONB cases in China. CTNNB1 and ZNRF3 were the most prevalent altered cancer-related genes. The results of TMB, PD-L1, and CD8+ Tils suggest that ONB may be insensitive to immunotherapy. M1 macrophages may be positively associated with the prognosis of ONB.Implications for PracticeIn this study, the most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one (1/15) case expressed PD-L1 (> 1%) in the tumor region. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. The higher level of CD68-related macrophages indicates that M1 macrophages potentially play an important role in ONB development that is possibly associated with prognosis

A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks

Deep Neural Networks (DNNs) are widely used for computer vision tasks. However, it has been shown that deep models are vulnerable to adversarial attacks, i.e., their performances drop when imperceptible perturbations are made to the original inputs, which may further degrade the following visual tasks or introduce new problems such as data and privacy security. Hence, metrics for evaluating the robustness of deep models against adversarial attacks are desired. However, previous metrics are mainly proposed for evaluating the adversarial robustness of shallow networks on the small-scale datasets. Although the Cross Lipschitz Extreme Value for nEtwork Robustness (CLEVER) metric has been proposed for large-scale datasets (e.g., the ImageNet dataset), it is computationally expensive and its performance relies on a tractable number of samples. In this paper, we propose the Adversarial Converging Time Score (ACTS), an attack-dependent metric that quantifies the adversarial robustness of a DNN on a specific input. Our key observation is that local neighborhoods on a DNN's output surface would have different shapes given different inputs. Hence, given different inputs, it requires different time for converging to an adversarial sample. Based on this geometry meaning, ACTS measures the converging time as an adversarial robustness metric. We validate the effectiveness and generalization of the proposed ACTS metric against different adversarial attacks on the large-scale ImageNet dataset using state-of-the-art deep networks. Extensive experiments show that our ACTS metric is an efficient and effective adversarial metric over the previous CLEVER metric.Comment: ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMM

A rapid preconcentration method using modified GP-MSE for sensitive determination of trace semivolatile organic pollutants in the gas phase of ambient air

A sensitive concentration method utilising modified gas-purge microsyringe extraction (GP-MSE) was developed. Concentration (reduction in volume) to a microlitre volume was achieved. PAHs were utilised as semivolatile analytes to optimise the various parameters that affect the concentration efficiency. The injection rate and temperature were the key factors that affected the concentration efficiency. An efficient concentration (75.0−96.1%) of PAHs was obtained under the optimised conditions. The method exhibited good reproducibility (RSD values that ranged from 1.5 to 9.0%). The GP-MSE concentration method enhances the volume reduction (concentration factor), leading to a low method detection limit (0.5−15 ng L–1). Furthermore, this method offers the advantage of small-volume sampling, enabling even the detection of diurnal hourly changes in the concentration of PAHs in ambient air. Utilising this method in combination with GC−MS, the diurnal hourly flux of PAHs from the gas phase of ambient air was measured. Indeed, the proposed technique is a simple, fast, low-cost and environmentally friendly