Associations between Leisure Activities and HIV Risk Behaviors among Rural Migrants in Urban China

Although much has been documented on factors affecting HIV risk behavior among rural-to-urban migrants in China, data are lacking on the impact of leisure activities. In this study, we examined the association between leisure activities and HIV risk behavior among a sample of rural-to-urban migrants from two large cities (Beijing and Nanjing) in China. Cross-sectional data were analyzed for a sample of 4,085 participants aged 18 to 30 years (40.5% females). Findings from the analysis indicated that although the migrants worked long hours, they engaged in a number of activities when they did not work, including watching television (60.2%), reading (59.1%), sleeping (55.6%), and chatting with friends and co-workers (45.0%). Multiple regression analysis indicated that reading, doing chores (females only), listening to radio programs/audio CDs (male only) were associated with reduced likelihood of HIV risk behavior while playing cards in groups, visiting entertaining installments, watching videos (including Xrated, males only), and wondering around (females only) were associated with increased likelihood of HIV risk behavior. Findings of this study suggest that constructive and individualized activities (e.g., reading, listening to radios, and doing chores) may prevent migrants from engage in HIV risk behaviors while group and entertaining activities related to drugs and sex may increase the odds for migrants to engage in HIV risk behaviors. Prevention research should consider leisure activities as both an influential factor (including time trends and gender differences) for program development and an important venue for program delivery

Optical biopsy identification and grading of gliomas using label-free visible resonance Raman spectroscopy.

Glioma is one of the most refractory types of brain tumor. Accurate tumor boundary identification and complete resection of the tumor are essential for glioma removal during brain surgery. We present a method based on visible resonance Raman (VRR) spectroscopy to identify glioma margins and grades. A set of diagnostic spectral biomarkers features are presented based on tissue composition changes revealed by VRR. The Raman spectra include molecular vibrational fingerprints of carotenoids, tryptophan, amide I/II/III, proteins, and lipids. These basic in situ spectral biomarkers are used to identify the tissue from the interface between brain cancer and normal tissue and to evaluate glioma grades. The VRR spectra are also analyzed using principal component analysis for dimension reduction and feature detection and support vector machine for classification. The cross-validated sensitivity, specificity, and accuracy are found to be 100%, 96.3%, and 99.6% to distinguish glioma tissues from normal brain tissues, respectively. The area under the receiver operating characteristic curve for the classification is about 1.0. The accuracies to distinguish normal, low grade (grades I and II), and high grade (grades III and IV) gliomas are found to be 96.3%, 53.7%, and 84.1% for the three groups, respectively, along with a total accuracy of 75.1%. A set of criteria for differentiating normal human brain tissues from normal control tissues is proposed and used to identify brain cancer margins, yielding a diagnostic sensitivity of 100% and specificity of 71%. Our study demonstrates the potential of VRR as a label-free optical molecular histopathology method used for in situ boundary line judgment for brain surgery in the margins

Design and processing test of eel automatic filleting machine

Objective: A special cutting mechanism for slicing elongated fish with smooth surface was designed. Methods: Taking the slimy eel as the research object, the mechanism of clamping and cutting operation was analyzed. Taking cutting quality and cutting time as test indexes, the influence of main parameters such as clamping wheel speed, cutting tool speed and clamping wheel surface geometry on cutting quality and cutting time were investigated. Results: The main factors affecting cutting quality were blade speed and clamping wheel limit height, and the most important factors affecting cutting time were clamping wheel speed. When the clamping wheel limit height was 5 mm, the blade speed was 1 350 r/min, and the clamping wheel speed wwas 167 r/min, the higher cutting quality score and cutting time could be obtained. Conclusion: The eel can be effectively transported by using the gripper wheel, and efficient and high-speed laparotomy can be achieved by adjusting the speed of the gripper wheel, the speed of the blade and the height of the limit

Performance and emission characteristics of a diesel engine running on optimized ethyl levulinate–biodiesel–diesel blends

Copyright © 2015 Elsevier Ltd. All rights reserved.In this study, biomass-based EL (ethyl levulinate) was evaluated as an additional fuel to biodiesel and diesel. Physical and chemical properties, including intersolubility, cold flow properties, spray evaporation, oxidation stability, anti-corrosive property, cleanliness, fire reliability and heating value of twelve different EL–biodiesel–diesel blends were analyzed. The results show that the fuel blends that were in line with China's national standard for biodiesel blend fuel (B5) have similar physical and chemical properties to pure diesel with improved cold flow properties. Optimized fuel blends based on grey relational analysis and analytic hierarchy process were selected to evaluate engine performance and emissions using an unmodified diesel engine test bench. The results show that engine power and torque with the fuel blends were in general similar to those with diesel (less than 3% differences). Both brake specific fuel and energy consumption were lower with the fuel blends than with diesel, suggesting higher fuel conversion efficiencies for the fuel blends. HC (Hydrocarbon) and CO (carbon monoxide) emissions and smoke opacity reduced significantly with the fuel blends compared with diesel while NOx (nitrogen oxides) and CO2 (carbon dioxide) emissions increased. Our study suggests that EL produced from lignocellulosic biomass could be used as a blending component with biodiesel and diesel for use in unmodified diesel engines and could potentially be a promising environment-friendly fuel

FABP4-mediated lipid droplet formation in Streptococcus uberis-infected macrophages supports host defence

Foamy macrophages containing prominent cytoplasmic lipid droplets (LDs) are found in a variety of infectious diseases. However, their role in Streptococcus uberis-induced mastitis is unknown. Herein, we report that S. uberis infection enhances the fatty acid synthesis pathway in macrophages, resulting in a sharp increase in LD levels, accompanied by a significantly enhanced inflammatory response. This process is mediated by the involvement of fatty acid binding protein 4 (FABP4), a subtype of the fatty acid-binding protein family that plays critical roles in metabolism and inflammation. In addition, FABP4 siRNA inhibitor cell models showed that the deposition of LDs decreased, and the mRNA expression of Tnf, Il1b and Il6 was significantly downregulated after gene silencing. As a result, the bacterial load in macrophages increased. Taken together, these data demonstrate that macrophage LD formation is a host-driven component of the immune response to S. uberis. FABP4 contributes to promoting inflammation via LDs, which should be considered a new target for drug development to treat infections

Taurine reprograms mammary-gland metabolism and alleviates inflammation induced by Streptococcus uberis in mice

Streptococcus uberis (S. uberis) is an important pathogen causing mastitis, which causes continuous inflammation and dysfunction of mammary glands and leads to enormous economic losses. Most research on infection continues to be microbial metabolism-centric, and many overlook the fact that pathogens require energy from host. Mouse is a common animal model for studying bovine mastitis. In this perspective, we uncover metabolic reprogramming during host immune responses is associated with infection-driven inflammation, particularly when caused by intracellular bacteria. Taurine, a metabolic regulator, has been shown to effectively ameliorate metabolic diseases. We evaluated the role of taurine in the metabolic regulation of S. uberis-induced mastitis. Metabolic profiling indicates that S. uberis exposure triggers inflammation and metabolic dysfunction of mammary glands and mammary epithelial cells (the main functional cells in mammary glands). Challenge with S. uberis upregulates glycolysis and oxidative phosphorylation in MECs. Pretreatment with taurine restores metabolic homeostasis, reverses metabolic dysfunction by decrease of lipid, amino acid and especially energy disturbance in the infectious context, and alleviates excessive inflammatory responses. These outcomes depend on taurine-mediated activation of the AMPK–mTOR pathway, which inhibits the over activation of inflammatory responses and alleviates cellular damage. Thus, metabolic homeostasis is essential for reducing inflammation. Metabolic modulation can be used as a prophylactic strategy against mastitis

The convergence analysis and error estimation for unique solution of a p-Laplacian fractional differential equation with singular decreasing nonlinearity

© 2018, The Author(s). In this paper, we focus on the convergence analysis and error estimation for the unique solution of a p-Laplacian fractional differential equation with singular decreasing nonlinearity. By introducing a double iterative technique, in the case of the nonlinearity with singularity at time and space variables, the unique positive solution to the problem is established. Then, from the developed iterative technique, the sequences converging uniformly to the unique solution are formulated, and the estimates of the error and the convergence rate are derived

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Sinophobia was popular in Chinese language communities on Twitter during the early COVID-19 pandemic

Abstract The COVID-19 pandemic has led to a global surge in Sinophobia. We examine how Chinese language users responded to COVID-19 on Western social media by compiling a unique database (CNTweets) with over 25 million Chinese tweets mentioning any Chinese characters related to China, the Chinese Communist Party (CCP), Chinese, and Asians from December 2019 to April 2021. Our analysis of Twitter users’ self-reported geographic information shows that most Chinese language users on Twitter originated from Mainland China, Hong Kong, Taiwan, and the United States. We then adopt the Robustly Optimized Bidirectional Encoder Representations from Transformers (RoBERTa) and structural topic modeling to further analyze the sentiments, content, and topics of Chinese tweets during the COVID-19 pandemic. Our results suggest that 61.8% of tweets in our database were contributed by only 1% of Twitter users and 62.2% of tweets were negative toward China. Despite the prevalence of anti-China sentiments, the target entity analysis shows that these negative sentiments were more likely to target the Chinese government and CCP than the Chinese people. Our findings also show that the most popular topics were politics (e.g., Hong Kong protests and Taiwan issues), COVID-19, and the United States (e.g., the US-China relations and domestic issues). Anti-China users focused relatively more on political issues such as democracy and freedom, while pro-China users mentioned cultural and economic topics more. Our social network analysis reveals that these pro-China and anti-China Twitter users lacked in-depth engagement in China-related conversations and were highly segregated from each other. We conclude by discussing our contributions to China and social media studies and possible policy implications