Resting-State EEG Reveals Abnormal Microstate Characteristics of Depression with Insomnia.

Previous research revealed various aspects of resting-state EEG for depression and insomnia. However, the EEG characteristics of depressed subjects with insomnia are rarely studied, especially EEG microstates that capture the dynamic activities of the large-scale brain network. To fill these research gaps, the present study collected resting-state EEG data from 32 subclinical depression subjects with insomnia (SDI), 31 subclinical depression subjects without insomnia (SD), and 32 healthy controls (HCs). Four topographic maps were generated from clean EEG data after clustering and rearrangement. Temporal characteristics were obtained for statistical analysis, including cross-group variance analysis (ANOVA) and intra-group correlation analysis. In our study, the global clustering of all individuals in the EEG microstate analysis revealed the four previously discovered categories of microstates (A, B, C, and D). The occurrence of microstate B was lower in SDI than in SD and HC subjects. The correlation analysis showed that the total Pittsburgh Sleep Quality Index (PSQI) score negatively correlated with the occurrence of microstate C in SDI (r = - 0.415, p < 0.05). Conversely, there was a positive correlation between Self-rating Depression Scale (SDS) scores and the duration of microstate C in SD (r = 0.359, p < 0.05). These results indicate that microstates reflect altered large-scale brain network dynamics in subclinical populations. Abnormalities in the visual network corresponding to microstate B are an electrophysiological characteristic of subclinical individuals with symptoms of depressive insomnia. Further investigation is needed for microstate changes related to high arousal and emotional problems in people suffering from depression and insomnia.

Body Dissatisfaction and Disordered Eating Behaviors: The Mediation Role of Smartphone Addiction and Depression.

This study aimed to determine whether smartphone addiction and depression sequentially mediate the relationship between body dissatisfaction and disordered eating behaviors (e.g., restrained eating, emotional eating and external eating). A total of 5986 participants (54.1% females, average age = 19.8 years, age range = 17-32) completed the Satisfaction and Dissatisfaction with Body Parts Scale, the Three-Factor Eating Questionnaire, the Smartphone Addiction Scale and the Patient Health Questionnaire-9. Mediational analysis showed that, after controlling for age, sex and body mass index, body dissatisfaction was related to disordered eating behaviors through (a) the mediating effect of smartphone addiction, (b) the mediating effect of depression, and (c) the serial mediating effect of smartphone addiction and depression. In conclusion, our study showed for the first time that smartphone addiction and depression can be sequential mediator variables in the association between body dissatisfaction and disordered eating. However, this study is a cross-sectional study; future longitudinal studies could further test the causal associations between these study variables.

The detection of a transgenic soybean biochip using gold label silver stain technology.

A method for the rapid detection of transgenic soybean crops based on a combination of gene chip and "gold label silver stain" (GLSS) technologies has been established. To ensure the specificity of this method, the CaMV35S promoter and Nos terminator were selected as probes because they are both exogenous genes that are specific to transgenic soybean plants. The addition of biotin-modified dUTPs to a polymerase chain reaction (PCR) system can produce amplified nucleic acid segments containing biotin. These labeled PCR products then hybridize with specific probes on the chip and are subsequently bound by streptavidin-modified gold nanoparticles (GNPs). Due to the catalytic nature of the GNPs, silver staining can be used to visualize the hybridized probes, which appear as signals in varying shades of gray. The intensity value of the gray signals can be obtained using a general scanner. Silver staining for 10 min was determined to produce the optimal signal-to-noise ratio. In addition, this method was shown to be highly specific and had a detection sensitivity of 288.57 pg/µL.