87 research outputs found

    Amygdala's T1-weighted image radiomics outperforms volume for differentiation of anxiety disorder and its subtype

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    IntroductionAnxiety disorder is the most common psychiatric disorder among adolescents, with generalized anxiety disorder (GAD) being a common subtype of anxiety disorder. Current studies have revealed abnormal amygdala function in patients with anxiety compared with healthy people. However, the diagnosis of anxiety disorder and its subtypes still lack specific features of amygdala from T1-weighted structural magnetic resonance (MR) imaging. The purpose of our study was to investigate the feasibility of using radiomics approach to distinguish anxiety disorder and its subtype from healthy controls on T1-weighted images of the amygdala, and provide a basis for the clinical diagnosis of anxiety disorder.MethodsT1-weighted MR images of 200 patients with anxiety disorder (including 103 GAD patients) as well as 138 healthy controls were obtained in the Healthy Brain Network (HBN) dataset. We extracted 107 radiomics features for the left and right amygdala, respectively, and then performed feature selection using the 10-fold LASSO regression algorithm. For the selected features, we performed group-wise comparisons, and use different machine learning algorithms, including linear kernel support vector machine (SVM), to achieve the classification between the patients and healthy controls.ResultsFor the classification task of anxiety patients vs. healthy controls, 2 and 4 radiomics features were selected from left and right amygdala, respectively, and the area under receiver operating characteristic curve (AUC) of linear kernel SVM in cross-validation experiments was 0.6739±0.0708 for the left amygdala features and 0.6403±0.0519 for the right amygdala features; for classification task for GAD patients vs. healthy controls, 7 and 3 features were selected from left and right amygdala, respectively, and the cross-validation AUCs were 0.6755±0.0615 for the left amygdala features and 0.6966±0.0854 for the right amygdala features. In both classification tasks, the selected amygdala radiomics features had higher discriminatory significance and effect sizes compared with the amygdala volume.DiscussionOur study suggest that radiomics features of bilateral amygdala potentially could serve as a basis for the clinical diagnosis of anxiety disorder

    Behind the rainbow, "Tongqi" wives of men who have sex with men in China: a systematic review

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    open access articleBackground: Due to the restrictions and stigmatization of homosexuality in China, there has emerged the “Tongqi,” or the wives of men who have sex with men (MSM). There are around 14 million Tongqi wives whose needs for support are often overshadowed. This phenomenon has been largely under researched, this review is the first to address the current data on the Tongqi. The aim of this systematic review is to begin to provide insight into the pre-existing data and the further support that is needed for the wives of MSM. Methods: The researchers searched PubMed, Web of Science, EMBASE, PsycINFO, CNKI, Sinomed and WangFang databases from their inception date until June 7, 2019. Handsearching was also completed to provide a rich data set. Results: The articles were summarized and analyzed for thematic clusters. From the selected article, five themes emerged, including Sexual Health Issues, Intimate Partner Violence, Mental Health Status, Marriage Dissatisfaction, and Coping Strategies. These themes often intersected to provide a complex understanding of the current gaps in support provided to Tongqi. Conclusion: Tongqi wives remain a hidden population in Chinese mainstream society, who deserves a sensitive approach to support. The study revealed that the MSM wives suffer severe mental, physical, health, and life related harms. However, instead of situating them into the victim roles, many women take on an identity of empowerment and are working together, aiming to make social changes. In order to address the Tongqi phenomenon, it is also essential to reduce the discrimination toward homosexuality. Tongqi are a special group of Chinese women, they require further intensive research attention

    The relationship between childhood trauma and Internet gaming disorder among college students: A structural equation model

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    open access journalBackground The aim of this study was to investigate the mechanisms of Internet gaming disorder (IGD) and the associated interaction effects of childhood trauma, depression and anxiety in college students. Methods Participants were enrolled full-time as freshmen at a University in the Hunan province, China. All participants reported their socio-demographic characteristics and undertook a standardized assessment on childhood trauma, anxiety, depression and IGD. The effect of childhood trauma on university students' internet gaming behaviour mediated by anxiety and depression was analysed using structural equation modelling (SEM) using R 3.6.1. Results In total, 922 freshmen participated in the study, with an approximately even male-to-female ratio. A mediation model with anxiety and depression as the mediators between childhood trauma and internet gaming behaviour allowing anxiety and depression to be correlated was tested using SEM. The SEM analysis revealed that a standardised total effect of childhood trauma on Internet gaming was 0.18, (Z = 5.60, 95% CI [0.02, 0.05], P < 0.001), with the direct effects of childhood trauma on Internet gaming being 0.11 (Z = 3.41, 95% CI [0.01, 0.03], P = 0.001), and the indirect effects being 0.02 (Z = 2.32, 95% CI [0.00, 0.01], P = 0.020) in the pathway of childhood trauma-depression-internet gaming; and 0.05 (Z = 3.67, 95% CI [0.00, 0.02], P < 0.001) in the pathway of childhood trauma-anxiety-Internet gaming. In addition, the two mediators anxiety and depression were significantly correlated (r = 0.50, Z = 13.54, 95% CI [3.50, 5.05], P < 0.001). Conclusions The study revealed that childhood trauma had a significant impact on adolescents' Internet gaming behaviours among college students. Anxiety and depression both significantly mediated the relationship between childhood trauma and internet gaming and augmented its negative influence. Discussion of the need to understand the subtypes of childhood traumatic experience in relationship to addictive behaviours is included

    Scheduling IDK classifiers with arbitrary dependences to minimize the expected time to successful classification

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    This paper introduces and evaluates a general construct for trading off accuracy and overall execution duration in classification-based machine perception problems—namely, the generalized IDK classifier cascade. The aim is to select the optimal sequence of classifiers required to minimize the expected (i.e. average) execution duration needed to achieve successful classification, subject to a constraint on quality, and optionally a latency constraint on the worst-case execution duration. An IDK classifier is a software component that attempts to categorize each input provided to it into one of a fixed set of classes, returning “I Don’t Know” (IDK) if it is unable to do so with the required level of confidence. An ensemble of several different IDK classifiers may be available for the same classification problem, offering different trade-offs between effectiveness (i.e. the probability of successful classification) and timeliness (i.e. execution duration). A model for representing such characteristics is defined, and a method is proposed for determining the values of the model parameters for a given ensemble of IDK classifiers. Optimal algorithms are developed for sequentially ordering IDK classifiers into an IDK cascade, such that the expected duration to successfully classify an input is minimized, optionally subject to a latency constraint on the worst-case overall execution duration of the IDK cascade. The entire methodology is applied to two real-world case studies. In contrast to prior work, the methodology developed in this paper caters for arbitrary dependences between the probabilities of successful classification for different IDK classifiers. Effective practical solutions are developed considering both single and multiple processors

    Efficient Depolymerization of Cellulosic Paper Towel Waste Using Organic Carbonate Solvents

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    Efficient depolymerization of lignocellulosic biomass is a prerequisite for sugar production and its subsequent upgradation to fuels and chemicals. Organic carbonate solvents, i.e., propylene carbonate (PC), ethylene carbonate (EC), and dimethyl carbonate (DMC), which are low in toxicity and biodegradable, were investigated as "green"co-solvents (PC/H2O, EC/H2O, DMC/H2O, solvent ratio 1:1) for depolymerization of cellulosic paper towel waste. PC/H2O and EC/H2O enhanced the depolymerization of paper towel waste and improved the total sugar yield (up to ∼25 C mol %) compared to H2O only (up to ∼11 C mol %) under mild reaction conditions (130 °C, 20 min). The higher performance of PC/H2O and EC/H2O can be attributed to higher availability of reactive protons in the catalytic system that facilitates efficient acid hydrolysis of recalcitrant cellulosic fibers. Moreover, a substantial buildup of in-vessel pressure by CO2 release during the microwave-assisted reaction because of decomposition of PC or EC might have accelerated the conversion of paper towel wastes. PC and EC are prospective solvents for lignocellulosic biomass conversion considering their green features and notable catalytic performance, which have a good potential for substituting conventional organic solvents such as dimethyl sulfoxide (DMSO) and tetrahydrofuran (THF) that are often considered hazardous in terms of health, safety, and environmental implications

    Review of the ecohydrological processes and feedback mechanisms controlling sand-binding vegetation systems in sandy desert regions of China

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