Search

To investigate the comorbidity of adolescent depression and Internet gaming disorder (IGD) and their shared and unique cognitive-behavioral factors (i.e., self-esteem, dysfunctional attitudes, hopelessness, and coping), a large-scale school-based survey was conducted among 3147 Chinese secondary school students in Hong Kong. Probable depression and IGD were screened using the Centre for Epidemiological Studies-Depression Scale and DSM-5 IGD checklist, respectively. Multinomial logistic regression was performed to identify the associations between different condition statuses and cognitive-behavioral factors. Four groups were identified, including comorbidity group (having probable depression and IGD), IGD group (having probable IGD alone), depression group (probable depression alone), and healthy group (neither condition). Comorbidity group showed the worst cognitive-behavioral statuses, followed by depression group and then IGD group. Compared with healthy group, those with lower self-esteem and higher hopelessness and dysfunctional attitudes were more likely to be classified into depression group and comorbidity group, while maladaptive coping was positively associated with all three disorder groups. The results suggest that depression and IGD may share common cognitive-behavioral mechanisms (e.g., maladaptive coping) but also own their uniqueness regarding specific factors (e.g., hopelessness and self-esteem). A transdiagnostic intervention approach targeting the common factors may effectively address the comorbidity. [ABSTRACT FROM AUTHOR]

Background and purpose: Stroke may cause extensive after-effects such as motor function impairments and disorder of consciousness (DoC). Detecting these after-effects of stroke and monitoring their changes are challenging jobs currently undertaken via traditional clinical examinations. These behavioural examinations often take a great deal of manpower and time, thus consuming significant resources. Computer-aided examinations of the electroencephalogram (EEG) microstates derived from bedside EEG monitoring may provide an alternative way to assist medical practitioners in a quick assessment of the after-effects of stroke. Methods: In this study, we designed a framework to extract microstate maps and calculate their statistical parameters to input to classifiers to identify DoC in ischemic stroke patients automatically. As the dataset is imbalanced with the minority of patients being DoC, an ensemble of support vector machines (EOSVM) is designed to solve the problem that classifiers always tend to be the majority classes in the classification on an imbalanced dataset. Results: The experimental results show EOSVM get better performance (with accuracy and F1-Score both higher than 89%), improving sensitivity the most, from lower than 60% (SVM and AdaBoost) to higher than 80%. This highlighted the usefulness of the EOSVM-aided DoC detection based on microstates parameters. Conclusion: Therefore, the classifier EOSVM classification based on features of EEG microstates is helpful to medical practitioners in DoC detection with saved resources that would otherwise be consumed in traditional clinic checks. [ABSTRACT FROM AUTHOR]

Background: M-type phospholipase A2 receptor (PLA2R) is the major autoantigen in adult idiopathic membranous nephropathy (IMN). Although reactive epitopes in the PLA2R domains have been identified, the clinical value of these domains recognized by anti-PLA2R antibodies remains controversial. Accordingly, this study aimed to quantitatively detect changes in the concentrations of different antibodies against epitopes of PLA2R in patients with IMN before and after treatment to evaluate the clinical value of epitope spreading. Methods: Highly sensitive time-resolved fluorescence immunoassay was used to quantitatively analyze the concentrations of specific IgG and IgG4 antibodies against PLA2R and its epitopes (CysR, CTLD1, CTLD6-7-8) in a cohort of 25 patients with PLA2R-associated membranous nephropathy (13 and 12 in the remission and non-remission groups, respectively) before and after treatment, and the results were analyzed in conjunction with clinical biochemical indicators. Results: The concentration of specific IgG (IgG4) antibodies against PLA2R and its epitopes (CysR, CTLD1 and CTLD6-7-8) in non-remission group was higher than that in remission group. The multipliers of elevation of IgG (IgG4) antibody were 5.6(6.2) fold, 3.0(24.3) fold, 1.6(9.0) fold, and 4.2(2.6) fold in the non-remission/remission group, respectively. However, the difference in antibody concentrations between the two groups at the end of follow-up was 5.6 (85.2), 1.7 (13.1), 1.0 (5.1), and 1.5 (22.3) times higher, respectively. When detecting concentrations of specific IgG antibodies against PLA2R and its different epitopes, the remission rate was 66.67% for only one epitope at M0 and 36.36% for three epitopes at M0. When detecting concentrations of specific IgG4 antibodies against PLA2R and its different epitopes, the remission rate was 100.00% for only one epitope at M0 and 50.00% for three epitopes at M0. A trivariate logistic regression model for the combined detection of eGFR, anti-CTLD678 IgG4, and urinary protein had an AUC of 100.00%. Conclusion: Low concentrations of anti-CysR-IgG4, anti-CTLD1-IgG4, and anti-CTLD6-7-8-IgG4 at initial diagnosis predict rapid remission after treatment. The use of specific IgG4 against PLA2R and its different epitopes combined with eGFR and urinary protein provides a better assessment of the prognostic outcome of IMN. [ABSTRACT FROM AUTHOR]

Objective: This study tested the mediation effect of maladaptive cognition of internet gaming and moderation effect of internet gaming history in the relationship between internet gaming engagement and internet gaming disorder in adolescents. Method: A total of 2,902 secondary school students were surveyed in Hong Kong from February 2021 to December 2021. The proposed moderated mediation model was tested by PROCESS. Results: Internet gaming engagement, internet gaming history and maladaptive cognition were positively associated with internet gaming disorder symptoms. Maladaptive cognition significantly mediated the association between internet gaming engagement and internet gaming disorder symptoms in both males and females. In addition, a significant interaction between internet gaming engagement and internet gaming history was detected among females but not for males, namely, the positive relationships of internet gaming engagement with maladaptive cognition and internet gaming disorder symptoms were weaker with the increased years of internet gaming. Conclusions: Our study provides a better understanding of the underlying mechanism and boundary condition in the association between internet gaming engagement and internet gaming disorder among adolescents. Preventing interventions should aim to reduce maladaptive cognition and internet gaming engagement. Interventions targeting internet gaming engagement maybe more effective among female gamers who are beginners and all male gamers. [ABSTRACT FROM AUTHOR]