11β-Hydroxysteroid Dehydrogenase Type 1(11β-HSD1) mediates insulin resistance through JNK activation in adipocytes

Glucocorticoids are used to treat a number of human diseases but often lead to insulin resistance and metabolic syndrome. 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) is a key enzyme that catalyzes the intracellular conversion of cortisone to physiologically active cortisol. Despite the known role of 11β-HSD1 and active glucocorticoid in causing insulin resistance, the molecular mechanisms by which insulin resistance is induced remain elusive. The aim of this study is to identify these mechanisms in high fat diet (HFD) experimental models. Mice on a HFD were treated with 11β-HSD1 inhibitor as well as a JNK inhibitor. We then treated 3T3-L1-derived adipocytes with prednisone, a synthetic glucocorticoid, and cells with 11β-HSD1 overexpression to study insulin resistance. Our results show that 11β-HSD1 and JNK inhibition mitigated insulin resistance in HFD mice. Prednisone stimulation or overexpression of 11β-HSD1 also caused JNK activation in cultured adipocytes. Inhibition of 11β-HSD1 blocked the activation of JNK in adipose tissue of HFD mice as well as in cultured adipocytes. Furthermore, prednisone significantly impaired the insulin signaling pathway, and these effects were reversed by 11β-HSD1 and JNK inhibition. Our study demonstrates that glucocorticoid-induced insulin resistance was dependent on 11β-HSD1, resulting in the critical activation of JNK signaling in adipocytes

The roles of risk perception, negative emotions and perceived efficacy in the association between COVID-19 infection cues and preventive behaviors: a moderated mediation model

Abstract Preventive behaviors during the COVID-19 pandemic are especially critical to the protection of individuals whose family members or acquaintances have been infected. However, limited research has explored the influence of infection cues on preventive behaviors. This study proposed an interaction model of environment-cognitive/affective-behavior to elucidate the mechanism by which infection cues influence preventive behaviors and the roles of risk perception, negative emotions, and perceived efficacy in that influence. To explore the relationships among these factors, we conducted a cross-sectional online survey in 34 provinces in China during the first wave of the COVID-19 pandemic. A total of 26,511 participants responded to the survey, and 20,205 valid responses (76.2%) were obtained for further analysis. The moderated mediation results show that infection cues positively predicted preventive behaviors in a manner mediated by risk perception and negative emotions. Moreover, perceived efficacy moderated the influence of infection cues not only on preventive behaviors but also on risk perception and negative emotions. The higher the perceived efficacy, the stronger these influences were. These findings validated our model, which elucidates the mechanisms underlying the promoting effect of infection cues on preventive behaviors during the initial stage of the COVID-19 pandemic. The implications of these results for the COVID-19 pandemic and beyond are discussed

Jointly Modeling Aspect Information and Ratings for Review Rating Prediction

Although matrix model-based approaches to collaborative filtering (CF), such as latent factor models, achieve good accuracy in review rating prediction, they still face data sparsity problems. Many recent studies have exploited review text information to improve the performance of predictions. The review content that they use, however, is usually on the coarse-grained text level or sentence level. In this paper, we propose a joint model that incorporates review text information with matrix factorization for review rating prediction. First, we adopt an aspect extraction method and propose a simple and practical algorithm to represent the review by aspects and sentiments. Then, we propose two similarity measures: aspect-based user similarity and aspect-based product similarity. Finally, aspect-based user and product similarity measures are incorporated into a matrix factorization to build a joint model for rating prediction. To this end, our model can alleviate the data sparsity problem and obtain interpretability for the recommendation. We conducted experiments on two datasets. The experimental results demonstrate the effectiveness of the proposed model

The mechanism of governments' and individuals' influence on protective behaviours during the second wave of COVID-19: a multiple mediation model

Background: The SARS-CoV-2 virus continues to spread and resurge globally with signs of a second wave, despite actions by governments to curb the COVID-19 pandemic. However, evidence-based strategies to combat COVID-19 recurrence are poorly documented. Objective: To reveal how governments and individuals should act to effectively cope with future waves, this study proposed a preventive model of COVID-19 resurgence. Method: A questionnaire survey was conducted among 1,137 residents of Beijing, where the epidemic reoccurred. Structural equation model was used to explore the mechanism among government intervention, perceived efficacy, positive emotions, posttraumatic growth (PTG) and protective behaviours. Results: Data analysis revealed that during COVID-19 resurgence, government intervention could directly and indirectly influence protective behaviours through individual factors (i.e. perceived efficacy, positive emotions), and PTG could mediate the indirect pathway to protective behaviours. Conclusions: These findings implied that government intervention needs to be integrated with individual factors to effectively control repeated COVID-19 outbreaks

Fairness decision-making of opportunity equity in gain and loss contexts

Social equity consists of opportunity equity and outcome equity. Although numerous studies have used ultimatum games to examine individuals' decision-making behavior in outcome distributions, few studies have explored this behavior in opportunity distributions. Our study used a modified version of the ultimatum game to explore fairness decision-making behavior and the underlying psychological mechanisms of opportunity equity in gain and loss contexts. We found that opportunity equity had a similar influence as outcome equity on people's fairness perception and decision-making behavior, even though the number of opportunities had nothing to do with the outcome. However, we also found that there were some differences between opportunity equity and outcome equity in the behavior pattern of evaluation and reaction processes. Our results provide evidence of inequity aversion for inequality of opportunity and expand inequity aversion theory. These findings may contribute to the reduction of social inequity and promote the development of a more harmonious society

Social comparisons differentially affect fair and unfair processing in ultimatum bargaining

Several theoretical frameworks have attempted to illustrate the influence of social contexts on decision-making and well-being. Traditional economic models assume that absolute income is the crucial determinant of one???s well-being, while the comparative models state that social comparisons influence and even determine well-being and decisions. Here we investigated the impact of social comparisons on decision-making using a modified three -player Ultimatum Game and ERP technique. We found two independent effects: First, social comparisons did not affect decision-making when a fair norm was enforced. Second, social comparisons affected fairness consideration for unfair offers only???responders were less likely to accept unfair offers in upward comparisons but more likely to accept unfair offers in downward comparisons. These results revealed that people were envy -free of fair offers while affected mainly by social comparisons when the equality norm was broken. Event-related brain potentials showed that in the early time window (260???320 ms), compared to fair offers, unfair offers elicited a larger negative-going medial frontal negativity (MFN) in upward than parallel and downward com-parisons, and in the late stage (320???650 ms), compared to fair offers, unfair offers led to equally less positive -going P300 in upward and downward comparisons relative to parallel comparison. Although partly consistent with the relative standing assumption, both traditional economic models and comparative models require revision to account for the results

Neural substrates of deficient cognitive control in individuals with severe internet gaming disorder

Background and aims: Internet gaming disorder (IGD) is rapidly becoming a worldwide health concern. The prefrontal-subcortical model of self-regulation emphasizes that an impaired prefrontal cognitive control system and an overwhelming subcortical reward-seeking system are both crucial factors in health problems, including addiction. This study focused on the cognitive control system of IGD, aiming to investigate whether cognitive control is altered and the underlying neural correlates in college students with IGD. Methods: Thirty college students with IGD and twenty-five matched healthy controls were asked to complete a stop-signal task that measures cognitive control while being monitored by functional magnetic resonance imaging (fMRI). Results: Compared to the controls, only the college students with severe IGD, rather than those with mild IGD, had deficient brain activity involved in inhibitory control and response execution (specifically, the inferior frontal gyrus, anterior cingulate cortex and primary motor cortex); this result implies that cognitive control deficits are closely linked to addiction severity in individuals with IGD. Regarding performance monitoring function, college students with IGD exhibited unabated behavioral and brain activity, as did the control group. Conclusions: Combined with our previous finding that the subcortical reward system was enhanced in individuals with IGD, the present findings extend the prefrontal-subcortical model of self-regulation from the perspective of IGD in a college student population and thus provide useful insight for the effective prevention and treatment of IGD.</p

The association between intolerance of uncertainty and Internet addiction during the second wave of the coronavirus disease 2019 pandemic: A multiple mediation model considering depression and risk perception

Repeated outbreaks of coronavirus disease 2019 (COVID-19) have forced people to shift most of their work and life activities from offline to online, leading to a growing problem of Internet dependence and even Internet addiction. However, the mechanism of the association between COVID-19-related intolerance of uncertainty (COVID-19 IU) and Internet addiction during the second wave of COVID-19 is still unclear. The current study explored the association between COVID-19 IU and Internet addiction as mediated by depression and risk perception based on the Uncertainty-Depression-Perception-Addiction model (UDPA). A total of 1,137 adult participants were recruited, and COVID-19 IU, depression, risk perception, Internet addiction, and demographic variables were analyzed. The results showed that COVID-19 IU was significantly and positively associated with Internet addiction and that this relationship was mediated in parallel by depression and risk perception. Our findings further extend the Interaction of Person-Affect-Cognition-Execution (I-PACE) model from the perspective of applicability in the unique context of COVID-19. Furthermore, the study suggests that individuals could decrease their dependence on the Internet to prevent Internet addiction during the second wave of the pandemic through effective interventions that include lowering COVID-19 IU, improving emotion regulation, and developing reasonable perceptions of risk