Thermal-Enhanced bri1-301 Instability Reveals a Plasma Membrane Protein Quality Control System in Plants

Brassinosteroids (BRs) are essential phytohormones mainly perceived by a single-pass transmembrane receptor-like protein kinase (RLK), BRASSINOSTEROID INSENSITIVE 1 (BRI1). bri1-5 and bri1-9, two distinct mutants with point mutations in the extracellular domain of BRI1, show weak defective phenotypes. Previous studies indicated that bri1-5 and bri1-9 mutated proteins can be recognized and eliminated via an endoplasmic reticulum quality control (ERQC) mechanism. Most of these two proteins, therefore, cannot reach their destination, plasma membrane. Here, we report our functional characterization of bri1-301, another BRI1 mutant protein with an amino acid substitution in the cytoplasmic kinase domain. bri1-301 is a partially functional BR receptor with significantly decreased protein abundance. Interestingly, protein stability and subcellular localization of bri1-301 are temperature-sensitive. At 22°C, an optimal temperature for indoor Arabidopsis growth, bri1-301 shows a weak defective phenotype. At a lower temperature condition such as 18°C, bri1-301 exhibits subtle morphological defects. At a higher temperature condition such as 28°C, on the other hand, bri1-301 displays an extremely severe phenotype reminiscent to that of a null bri1 mutant due to greatly increased bri1-301 internalization and degradation. Our detailed analyses suggest that bri1-301 stability is controlled by ERQC and plasma membrane quality control (PMQC) systems. Since PMQC has not been well studied in plants, bri1-301 can be used as a model mutant for future genetic dissection of this critical process

INFLUENCE OF INTERNALIZING PROBLEMS ON ACADEMIC ACHIEVEMENT IN CHINESE ADOLESCENTS: THE MEDIATING EFFECT OF ATTENTION PROBLEMS

Adolescent mental health has become a public concern, and it is necessary to know how problem behaviors affect academic achievement. The current study surveyed 12,672 adolescents in eastern China, and results indicated clinical cut-offs on each problem behavior. We then examined how internalizing problems lead to negative academic results. Findings suggest Attention problems are a key factor. Anxiety/depression and somatic complaints have no direct effect on academic performance but are mediated by attention problems. This study can serve practice of schooling and parenting, and provide basis for developing clinical intervention strategy in [email protected]

Creating a Chinese suicide dictionary for identifying suicide risk on social media

Introduction. Suicide has become a serious worldwide epidemic. Early detection of individual suicide risk in population is important for reducing suicide rates. Traditional methods are ineffective in identifying suicide risk in time, suggesting a need for novel techniques. This paper proposes to detect suicide risk on social media using a Chinese suicide dictionary.Methods. To build the Chinese suicide dictionary, eight researchers were recruited to select initial words from 4,653 posts published on Sina Weibo (the largest social media service provider in China) and two Chinese sentiment dictionaries (HowNet and NTUSD). Then, another three researchers were recruited to filter out irrelevant words. Finally, remaining words were further expanded using a corpus-based method. After building the Chinese suicide dictionary, we tested its performance in identifying suicide risk on Weibo. First, we made a comparison of the performance in both detecting suicidal expression in Weibo posts and evaluating individual levels of suicide risk between the dictionary-based identifications and the expert ratings. Second, to differentiate between individuals with high and non-high scores on self-rating measure of suicide risk (Suicidal Possibility Scale, SPS), we built Support Vector Machines (SVM) models on the Chinese suicide dictionary and the Simplified Chinese Linguistic Inquiry and Word Count (SCLIWC) program, respectively. After that, we made a comparison of the classification performance between two types of SVM models.Results and Discussion. Dictionary-based identifications were significantly correlated with expert ratings in terms of both detecting suicidal expression (r = 0.507) and evaluating individual suicide risk (r = 0.455). For the differentiation between individuals with high and non-high scores on SPS, the Chinese suicide dictionary (t1: F1 = 0.48; t2: F1 = 0.56) produced a more accurate identification than SCLIWC (t1: F1 = 0.41; t2: F1 = 0.48) on different observation windows.Conclusions. This paper confirms that, using social media, it is possible to implement real-time monitoring individual suicide risk in population. Results of this study may be useful to improve Chinese suicide prevention programs and may be insightful for other countries

Degradation of Methylene Blue via Dielectric Barrier Discharge Plasma Treatment

The degradation of methylene blue (MB) using an upgraded dielectric barrier discharge (DBD) plasma reactor was investigated in this paper. Air plasma was generated in the glass bead packed bed in the reactor, which was propagated into MB solution through a microporous diffuser plate. Microdischarge phenomenon can be observed on the interface of MB solution and the diffuser plate, where plasma active species were generated. The effects of air flow rate, initial solution concentration, initial solution pH, and initial solution conductivity on MB degradation were examined. Experimental results indicated that the proposed plasma reactor was effective for MB degradation. No obvious change in MB degradation efficiency was obtained for solution with various initial pH and conductivities, which suggested the potential of the reactor in actual wastewater treatment. The possible mechanism of the generation of plasma active species for MB degradation was proposed. In addition, the total organic carbon removal and chemical oxidation demand removal after 30 min treatment were 38.5% and 48.3%, which was higher than that obtained by ozone. The energy yield for MB degradation reached up to 9.3 g/kWh. Finally, a possible degradation pathway of MB solution was proposed

Suicidal ideation detection via social media analytics

Suicide is one of the increasingly serious public health problems in modern society. Traditional suicidal ideation detection using questionnaires or patients&rsquo; self-report about their feelings and experiences is normally considered insufficient, passive, and untimely. With the advancement of Internet technology, social networking platforms are becoming increasingly popular. In this paper, we propose a suicidal ideation detection method based on multi-feature weighted fusion. We extracted linguistic features set that related to suicide by three different dictionaries, which are data-driven dictionary, Chinese suicide dictionary, and Language Inquiry and Word Count (LIWC). Two machine learning algorithms are utilized to build weak classification model with these three feature sets separately to generate six detection results. And after logistic regression, to get the final weighted results. In such a scheme, the results of model evaluation reveal that the proposed detection method achieves significantly better performance than that use existing feature selection methods.</p