How social distance affects the intention and behavior of collaborative consumption: a study based on online car-hailing service

In recent years, advances in mobile communications technology have enabled collaborative consumption or product sharing between consumers on a large scale. Unlike traditional consumption, collaborative consumption is based on collaboration among individuals, so that the decision-making mechanisms of individual consumers may be different from those in traditional consumption scenarios. The current study focuses on how the social distance between consumers and drivers affects collaborative consumption intention in the case of online car-hailing services. In this study, the theory of planned behavior (TPB) is used as the foundational framework, and we innovatively add the concept of social distance to the TPB to form a new, and integrated model. We test the model based on data collected from 315 online car-hailing users. The results shows that behavioral attitudes, subjective norms, and perceived behavioral control, positively influence collaborative consumption intention and behavior. More interestingly, we find that social distance has both direct and indirect impacts on collaborative consumption intention: The greater the social distance, the lower the collaborative consumption intention. Moreover, social distance also moderates the influence of subjective norms and perceived behavioral control on collaborative consumption intention. To be specific, the influence of subjective norms and perceived behavioral control on collaborative consumption intention is weakened when consumers perceive less social distance. The results suggest that the integrated model has a stronger explanatory power on collaborative consumption behavior. This study enhances the traditional TPB model and offers insight into promoting collaborative consumption in the context of the sharing economy

Epidemiology of atrial fibrillation and risk of CVD mortality among hypertensive population: A prospective cohort study in Northeast China

BackgroundDetermining risk factors of cardiovascular disease (CVD)-related mortality and evaluating their influence are important for effectively reducing corresponding mortality. However, few research findings have estimated the relationship between atrial fibrillation (AF) and CVD-related mortality among hypertension individuals.ObjectiveThe objective of this study was to investigate the epidemiology of AF in a hypertension population and determine the relationship between AF and CVD-related mortality.MethodsUsing a multistage, stratified, and cluster random sampling method, the prospective cohort study with a median follow-up of 3.51 years enrolled 10,678 hypertensive participants at baseline. The prevalence, awareness, and anticoagulation data of AF in this focal population were carefully assessed. Stepwise logistic regression and Cox regression analysis were respectively performed to evaluate the determinants of AF and the association between AF and CVD-related mortality.ResultsThe overall prevalence of AF was 1.3% (95% CI, 1.1%−1.6%) in the hypertensive population, and it was higher in men than in women (1.8% vs. 1.0%, respectively; p=0.001). The awareness of AF was 53.1%, and the rate of oral anticoagulant (OAC) therapy was only 4.2%, although all AF participants should have required according to the European Society of Cardiology guidelines. The determinants of AF included elder, male, and history of coronary heart disease in the hypertensive population. Besides, compared with individuals without AF, the risk of CVD-related mortality significantly increased in the hypertensive population with AF (HR 3.37, 95% CI 2.10–5.40).ConclusionOur results indicated a huge burden of AF and underuse of OAC therapy for them in a community-based hypertensive population. Considering that most of the risk factors of AF were unmodifiable in hypertensive individuals, as well as its high risk of mortality, long-term interventions including AF education, timely screening, and widespread use of OACs should be emphasized in the focal populations

Amide proton transfer-weighted imaging of pediatric brainstem glioma and its predicted value for H3 K27 alteration

BACKGROUND: Non-invasive determination of H3 K27 alteration of pediatric brainstem glioma (pedBSG) remains a clinical challenge. PURPOSE: To predict H3 K27-altered pedBSG using amide proton transfer-weighted (APTw) imaging. MATERIAL AND METHODS: This retrospective study included patients with pedBSG who underwent APTw imaging and had the H3 K27 alteration status determined by immunohistochemical staining. The presence or absence of foci of markedly increased APTw signal in the lesion was visually assessed. Quantitative APTw histogram parameters within the entire solid portion of tumors were extracted and compared between H3 K27-altered and wild-type groups using Student's t-test. The ability of APTw for differential diagnosis was evaluated using logistic regression. RESULTS: Sixty pedBSG patients included 48 patients with H3 K27-altered tumor (aged 2-48 years) and 12 patients with wild-type tumor (aged 3-53 years). Visual assessment showed that the foci of markedly increased APTw signal intensity were more common in the H3 K27-altered group than in wild-type group (60% vs. 16%, P = 0.007). Histogram parameters of APTw signal intensity in the H3 K27-altered group were significantly higher than those in the wild-type group (median, 2.74% vs. 2.22%, P = 0.02). The maximum (area under the receiver operating characteristic curve [AUC] = 0.72, P = 0.01) showed the highest diagnostic performance among histogram analysis. A combination of age, median and maximum APTw signal intensity could predict H3 K27 alteration with a sensitivity of 81%, specificity of 75% and AUC of 0.80. CONCLUSION: APTw imaging may serve as an imaging biomarker for H3 K27 alteration of pedBSGs

Heparin Alters Viral Serpin, Serp-1, Anti-Thrombolytic Activity to Anti-Thrombotic Activity

Serine protease inhibitors (serpins) regulate coagulation and inflammation. Heparin, a glycosaminoglycan, is an important cofactor for modulation of the inhibitory function of mammalian serpins. The secreted myxoma viral serpin, Serp-1 exerts profound anti-inflammatory activity in a wide range of animal models. Serp-1 anti-inflammatory and anti-atherogenic activity is dependent upon inhibition of the uPA / uPA receptor thrombolytic complex. We demonstrate here that heparin binds to Serp-1 and enhances Serp-1 inhibition of thrombin, a human pro-thrombotic serine protease, in vitro, altering inhibitory activity to a more predominant anti-thrombotic activity. Heparin also facilitates the simultaneous thrombin-mediated cleavage of Serp-1 and prevents formation of a serpin-typical SDS-resistant complex, implying mutual neutralization of Serp-1 and thrombin. In a cell-based assay, heparin facilitates Serp-1 reversal of cellular activation by stabilizing cellular membrane fluidity in thrombin-activated monocytes. In conclusion, heparin and other GAGs serve as cofactors enhancing Serp-1 regulation of local thrombotic and inflammatory pathway

A Survey on Evolutionary Algorithm Based Hybrid Intelligence in Bioinformatics

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks

Design of Large-Displacement Compliant Mechanisms by Topology Optimization Incorporating Modified Additive Hyperelasticity Technique

This paper is focused on the topology design of compliant mechanisms undergoing large displacement (over 20% of the structural dimension). Based on the artificial spring model and the geometrically nonlinear finite element analysis, the optimization problem is formulated so as to maximize the output displacement under a given material volume constraint. A modified additive hyperelasticity technique is proposed to circumvent numerical instabilities that occurred in the low-density or intermediate-density elements during the optimization process. Compared to the previous method, the modified technique is very effective and can provide more accurate response analysis for the large-displacement compliant mechanism. The whole optimization process is carried out by the gradient-based mathematical programming method. Numerical examples of a force-inverting mechanism and a microgripping mechanism are presented. The obtained optimal solutions verify the applicability of the proposed numerical techniques and show the necessity of considering large displacement in the design problem

Potential Role of Gene Regulator NFAT5 in the Pathogenesis of Diabetes Mellitus

Nuclear factor of activated T cells 5 (NFAT5), a Rel/nuclear factor- (NF-) κB family member, is the only known gene regulator of the mammalian adaptive response to osmotic stress. Exposure to elevated glucose increases the expression and nuclear translocation of NFAT5, as well as NFAT5-driven transcriptional activity in vivo and in vitro. Increased expression of NFAT5 is closely correlated with the progression of diabetes in patients. The distinct structure of NFAT5 governs its physiological and pathogenic roles, indicating its opposing functions. The ability of NFAT5 to maintain cell homeostasis and proliferation is impaired in patients with diabetes. NFAT5 promotes the formation of aldose reductase, pathogenesis of diabetic vascular complications, and insulin resistance. Additionally, NFAT5 activates inflammation at a very early stage of diabetes and induces persistent inflammation. Recent studies revealed that NFAT5 is an effective therapeutic target for diabetes. Here, we describe the current knowledge about NFAT5 and its relationship with diabetes, focusing on its diverse regulatory functions, and highlight the importance of this protein as a potential therapeutic target in patients with diabetes