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Objectives: There are inconsistent findings about the relationship between impermanence and psychological health. In order to gain a deeper understanding of this relationship, the present study utilized a person-centered approach to investigate the interplay between awareness and acceptance of impermanence and its impact on mental health outcomes. Method: A total of 433 Chinese university students (73.2% female; age M = 19.73 years, SD = 1.90) completed a battery of measures on impermanence awareness and acceptance, anxiety, depression, everyday stress, posttraumatic stress disorder (PTSD), and life satisfaction. To identify profiles of impermanence, latent profile analysis was performed using the item scores from the Impermanence Awareness and Acceptance Scale. Results: Three profiles were identified: (1) Neutral Stance of Impermanence (NSI; 32.8%), (2) High Awareness and Acceptance (HAA; 16.9%), and (3) High Awareness Without Acceptance (HAWA; 50.3%). The HAWA profile had the highest levels of anxiety, depression, everyday stress, posttraumatic stress disorder among three profiles, followed by the NSI and HAA profile, respectively. In addition, the HAWA profile had lower levels of life satisfaction compared to the HAA profile, but the HAWA and HAA profiles did not have significant difference in life satisfaction when comparing with the NSI profile. Conclusions: The HAWA and HAA profiles had the highest and lowest risk of mental health problems, respectively. The findings of this study significantly enhance our understanding of the different group types among Chinese university students who embrace the perspective of impermanence, as well as their relationships with various psychological outcomes. [ABSTRACT FROM AUTHOR]

Although the negative impact of posttraumatic stress disorder (PTSD) on psychological distress is broadly consistent across the literature, the psychological mechanisms underpinning this relationship need further exploration. Pain paradox theory has postulated the important role of PTSD, avoidance strategies, mindfulness, and distress following trauma. However, a more comprehensive study is needed to understand their interactive effects over time. This current longitudinal study aimed to examine the associations between these factors. 201 participants completed the questionnaire survey (i.e., the PTSD Checklist for DSM-5, Toronto Alexithymia Scale, Mindfulness Attention Awareness Scale, and the General Health Questionnaire) at two time points nine months apart. An autoregressive cross-lagged panel with structural equation modelling was used for data analysis. Initial PTSD symptoms predicted subsequent psychological distress. Initial mindfulness was significantly negatively correlated with subsequent alexithymia, PTSD, and distress outcomes. Furthermore, initial alexithymia was significantly positively associated with subsequent PTSD and distress. Following trauma exposure, individuals may develop PTSD that impairs mental health. However, individuals with higher levels of mindfulness tend to experience less alexithymia and PTSD symptoms, which in turn may lead to lower levels of psychological distress over time. Meanwhile, individuals with lower levels of difficulty identifying and describing emotions are less likely to develop PTSD symptoms and experience psychological distress over time. [ABSTRACT FROM AUTHOR]

The thermal stability of proteins can be altered when they interact with small molecules, other biomolecules or are subject to post-translation modifications. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a highly multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on the thermal stability of a protein. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current robust statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose the application of Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets. Fang et al. develop a Bayesian data analysis approach that is better suited to the analysis of Thermal Proteome Profiling (TPP) data than existing data analysis approaches that have limitations with respect to deviations from the expected sigmoid data behaviour. Their approach, which is more comprehensive and sensitive than standard data analysis methods, identified new putative targets and off-targets from published TPP datasets. [ABSTRACT FROM AUTHOR]

Study engagement has been considered a key predictor of school performance among students. Although the potential contribution of positive psychology to education has been recognised, the research findings and implications related to primary school students remain largely unexplored. Given that authentic happiness theory and the broaden-and-build theory have posited the important roles of positive emotions, meaning, engagement and strengths use in education, a more comprehensive study is needed to understand their interactions across time. The current longitudinal study examined the interrelationships between these positive attributes among Chinese students in Hong Kong, China. A total of 786 primary school students from Grades 4 to 6 completed the questionnaire survey at two time points one year apart. An autoregressive cross-lagged panel (ARCL) with structural equation modelling was applied for the data analysis. The results revealed that positive emotions predicted positive meaning, strengths use and study engagement across time. Positive emotions and meaning were reciprocally correlated with each other. Moreover, the use of strengths mediated the association between positive emotions and study engagement. The implications and future directions are also discussed. [ABSTRACT FROM AUTHOR]