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Background: Adolescents' psychological stress has become an important problem. Mindfulness-based interventions (MBIs) are proven to be effective in school settings in the Western world, and so expanding MBIs further is a particularly important consideration. Objective: This study addresses the effectiveness of MBI in reducing psychological stress in Chinese school settings and the mediating role of resilience between trait mindfulness and psychological stress. Methods: This study conducts a cluster randomized controlled trial. Ninety-two middle school students in the experimental group received 10 weeks of MBI, with 10 sessions of a mindfulness course, while 97 students in the control group followed their regular school program without intervention. Results: Psychological stress, trait mindfulness, and psychological resilience were measured by the Psycho-Somatic-Tension-Relaxation Inventory (PSTRI), Five Facet Mindfulness Questionnaire (FFMQ), and Resilience Scale for Chinese Adolescents (RSCA). The results showed that (1) compared with the pretest scores of the experimental group, and the pre- and post-test scores of the control group, the post-test scores of trait mindfulness and psychological resilience in the experimental group were significantly increased, while psychological stress was significantly decreased. (2) Trait mindfulness was positively associated with psychological resilience. Trait mindfulness and psychological resilience were negatively associated with psychological stress. (3) The mediating effect of psychological resilience accounted for 43.58% of the overall effect of trait mindfulness on psychological stress. Conclusions: These findings provide encouraging evidence for MBI's effectiveness in reducing adolescents' psychological stress and the possible mediating role of psychological resilience; thus, MBI is worthy of expanding to Chinese school settings.

College students are most susceptible to highest-risk of health risk behaviors (HRBs) in China. Mindfulness-based interventions (MBIs) have shown significant benefit in specific HRB; however, evidence of its effectiveness in multiple HRBs in college students is limited. The current study aimed to address the effectiveness of the Mindfulness-Based Cognitive Therapy (MBCT) on trait mindfulness and multiple HRBs among general Chinese undergraduates, and the relationship between trait mindfulness and HRBs. A randomized controlled trial (RCT) was conducted in a Chinese university from April to June 2016. A total of 164 enrolled participants were randomized to no intervention (n = 82), or MBCT (n = 82). The outcomes were measured by the Adolescent Health Related Risky Behavior Inventory (AHRBI) and the Five Facet Mindfulness Questionnaire (FFMQ). Data were analyzed with intent-to-treat analysis and per-protocol analysis.The results yielded significant group by pre-post interaction terms for the trait mindfulness facets (P < 0.01) and the HRBs (P < 0.05), the MBCT group changed more than the control group. The five types of HRB measures had significant inverse correlation with the five facets of the trait mindfulness measures (r = -0.50 ~ -0.16, P < 0.05). The structural model of the intervention effect of MBCT on HRBs mediated by trait mindfulness was well-fitted (P < 0.01).The findings suggests that MBI has beneficial effects in both improving trait mindfulness and reducing multiple HRBs, and the improvement of trait mindfulness can effectively decreases the risks of HRBs., Author(s): Xianhua Liu [sup.1] , Rulan Xiao [sup.1] , Fanggui Tang [sup.1] , Siwei Wu [sup.1] Author Affiliations: (1) grid.412101.7, 0000 0001 0377 7868, College of Educational Science, Hengyang Normal [...]

BackgroundThraustochytrids are unicellular fungal-like marine protists with ubiquitous existence in marine environments. They are well-known for their ability to produce high-valued omega-3 polyunsaturated fatty acids (ω-3-PUFAs) (e.g., docosahexaenoic acid (DHA)) and hydrolytic enzymes. Thraustochytrid biomass has been estimated to surpass that of bacterioplankton in both coastal and oceanic waters indicating they have an important role in microbial food-web. Nevertheless, the molecular pathway and regulatory network for PUFAs production and the molecular mechanisms underlying ecological functions of thraustochytrids remain largely unknown.ResultsThe genomes of two thraustochytrids strains (Mn4 and SW8) with ability to produce DHA were sequenced and assembled with a hybrid sequencing approach utilizing Illumina short paired-end reads and Pacific Biosciences long reads to generate a highly accurate genome assembly. Phylogenomic and comparative genomic analyses found that DHA-producing thraustochytrid strains were highly similar and possessed similar gene content. Analysis of the conventional fatty acid synthesis (FAS) and the polyketide synthase (PKS) systems for PUFAs production only detected incomplete and fragmentary pathways in the genome of these two strains. Surprisingly, secreted carbohydrate active enzymes (CAZymes) were found to be significantly depleted in the genomes of these 2 strains as compared to other sequenced relatives. Furthermore, these two strains possess an expanded gene repertoire for signal transduction and self-propelled movement, which could be important for their adaptations to dynamic marine environments.ConclusionsOur results demonstrate the possibility of a third PUFAs synthesis pathway besides previously described FAS and PKS pathways encoded in the genome of these two thraustochytrid strains. Moreover, lack of a complete set of hydrolytic enzymatic machinery for degrading plant-derived organic materials suggests that these two DHA-producing strains play an important role as a nutritional source rather than a nutrient-producer in marine microbial-food web. Results of this study suggest the existence of two types of saprobic thraustochytrids in the world's ocean. The first group, which does not produce cellulosic enzymes and live as 'left-over' scavenger of bacterioplankton, serves as a dietary source for the plankton of higher trophic levels and the other possesses capacity to live on detrital organic matters in the marine ecosystems.

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed. [ABSTRACT FROM AUTHOR]

The clinical heterogeneity of early-stage endometrial cancer (EC) is worthy of further study to identify high-quality prognostic markers and their potential role in aggressive tumor behavior. Mutation of TP53 was considered as an important primary triage in modified molecular typing for EC, it still cannot precisely predict the prognosis of EC. After proteomic analysis of cancer and para-cancerous tissues from 24 early-stage endometrioid EC patients with different survival outcomes, 13 differentially expressed proteins were screen out while 2 proteins enriched in p53 signaling pathway were further identified by single-cell transcriptome (scRNA-seq). Interestingly, tumor necrosis factor type-1 receptor-associated protein (TRAP1) and calmodulin-regulated spectrin-associated protein family member 3 (CAMSAP3) were found to be significantly downregulated in the specific cell cluster. Expectedly, the signature genes of TRAP1low/CAMSAP3low cluster included classical oncogenes. Moreover, close cellular interactions were observed between myeloid cells and the TRAP1low/CAMSAP3low cluster after systematically elucidating their relationship with tumor microenvironment (TME). The expression of TRAP1 and CAMSAP3 was verified by immunohistochemistry. Thus, a novel prediction model combining TRAP1, CAMSAP3 and TP53 was construct by multi-omics. Compared with the area under the curve, it demonstrated a significantly improvemrnt in the diagnostic efficacy in EC patients from TCGA bank. In conclusion, this work improved the current knowledge regarding the prognosis of early-stage EC through proteomics and scRNA-seq. These findings may lead to improvements in precise risk stratification of early-stage EC patients. [ABSTRACT FROM AUTHOR]