Investigating Emotion EEG Patterns for Depression Detection with Attentive Simple Graph Convolutional Network.

Depression severely limits daily functioning, diminishes quality of life and possibly leads to self-harm and suicide. Noninvasive electroencephalography (EEG) has been shown effective as biomarkers for objective depression diagnose and treatment response prediction, and dry EEG electrodes further extend its availability for clinical use. Even though many efforts have been made to identify depression biomarkers, searching reliable EEG biomarkers for depression detection remains challenging. This work presents a systematic investigation of capabilities of emotion EEG patterns for depression detection using a dry EEG electrode system. We design an emotion elicitation paradigm with happy, neutral and sad emotions and collect EEG signals during film watching from 33 depressed patients and 40 healthy controls. The mean activation levels at frontal and temporal sites in the alpha, beta and gamma bands of the depressed group are different to those of the healthy group, indicating the impacts of depressive symptoms on the emotion experiences. To leverage the topology information among EEG channels for emotion recognition and depression detection, an Attentive Simple Graph Convolutional network is built. The deep depression-health classifier achieves a sensitivity of 81.93% and a specificity of 91.69% on the happy emotions, suggesting the promising use of the emotion neural patterns for distinguishing the depressed patients from the healthy controls.

Dynamic effect of economic growth on the persistence of suicide rates.

Positive and negative economic growth is closely related to the suicide rate. To answer the question whether economic development has a dynamic impact on this rate, we used a panel smooth transition autoregressive model to evaluate the threshold effect of economic growth rate on the persistence of suicide. The research period was from 1994 to 2020, and the results show that the suicide rate had a persistent effect, which varied over time depending on the transition variable within different threshold intervals. However, the persistent effect was manifested in different degrees with the change in the economic growth rate and as the lag period of the suicide rate increased, the effect of the influence gradually decreased. We investigated different lag periods and noted that the impact on the suicide rate was the strongest in the first year after an economic change and then reduced to be only marginal after three years. This means that the growth momentum of the suicide rate within the first two years after a change in the economic growth rate, should be included in policy considerations of how to prevent suicides.

Gelation and the Self-Healing Behavior of the Chitosan-Catechol Hydrogel.

Mussel-inspired adhesive hydrogels have been developed in biomedical fields due to their strong adhesive property, cohesive capability, biocompatibility, and hemostatic ability. Catechol-functionalized chitosan is a potential polymer used to prepare adhesive hydrogels. However, the unique gelation mechanism and self-healing properties of catechol-grafted chitosan alone have not yet been explored. Herein, catechol-grafted chitosan (CC) was synthesized and further concentrated to obtain the self-healing CC hydrogels. The gelation mechanism of CC hydrogels may be attributed to the formation of hydrogen bonding, cation-π interactions, Michael addition, or Schiff base reactions during concentration phases. Rheological studies showed that the CC hydrogel owned self-healing properties in repeated damage-healing cycles. Coherent small-angle X-ray scattering (SAXS) analyses revealed the formation of a mesoscale structure (~9 nm) as the solid content of the hydrogel increased. In situ SAXS combined with rheometry verified the strain-dependent behavior of the CC hydrogel. The CC hydrogel displayed the osmotic-responsive behavior and enhanced adhesive strength (0.38 N/cm2) after immersion in the physiological saline. The CC scaffold prepared by lyophilizing the CC hydrogel revealed a macroporous structure (~200 µm), a high swelling ratio (9656%), good compressibility, and durability. This work provides an insight into the design of using chitosan-catechol alone to produce hydrogels or scaffolds with tunable mechanical properties for further applications in biomedical fields.

Multimodal Emotion Recognition in Response to Oil Paintings.

Most previous affective studies use facial expression pictures, music or movie clips as emotional stimuli, which are either too simplified without contexts or too dynamic for emotion annotations. In this work, we evaluate the effectiveness of oil paintings as stimuli. We develop an emotion stimuli dataset with 114 oil paintings selected from subject ratings to evoke three emotional states (i.e., negative, neutral and positive), and acquire both EEG and eye tracking data from 20 subjects while watching the oil paintings. Furthermore, we propose a novel affective model for multimodal emotion recognition by 1) extracting informative features of EEG signals from both the time domain and the frequency domain, 2) exploring topological information embedded in EEG channels with graph neural networks (GNNs), and 3) combining EEG and eye tracking data with a deep autoencoder neural network. From the exper-iments, our model obtains an averaged classification accuracy of 94.72 % ± 1.47 %, which demonstrates the feasibility of using oil paintings as emotion elicitation material.

PEP-sNASP Peptide Alleviates LPS-Induced Acute Lung Injury Through the TLR4/TRAF6 Axis.

Acute lung injury (ALI) is a severe inflammatory lung disease associated with macrophages. Somatic nuclear autoantigenic sperm protein (sNASP) is a negative regulator of Toll-like receptor (TLR) signaling that targets tumor necrosis factor (TNF) receptor-associated factor 6 (TRAF6) in macrophages, which is required to maintain homeostasis of the innate immune response. In the present study, we generated a cell permeable PEP-sNASP peptide using the sNASP protein N-terminal domain, and examined its potential therapeutic effect in a mouse model of ALI induced by the intranasal administration of lipopolysaccharide (LPS) and elucidated the underlying molecular mechanisms in RAW 264.7 cells. In vivo, PEP-sNASP peptide treatment markedly ameliorated pathological injury, reduced the wet/dry (W/D) weight ratio of the lungs and the production of proinflammatory cytokines (interleukin (IL)-1ß, IL-6, and TNF-α). In vitro, we demonstrated that when the PEP-sNASP peptide was transduced into RAW 264.7 cells, it bound to TRAF6, which markedly decreased LPS-induced proinflammatory cytokines by inhibiting TRAF6 autoubiquitination, nuclear factor (NF)-κB activation, reactive oxygen species (ROS) and cellular nitric oxide (NO) levels. Furthermore, the PEP-sNASP peptide also inhibited NLR family pyrin domain containing 3 (NLRP3) inflammasome activation. Our results therefore suggest that the PEP-sNASP may provide a potential protein therapy against oxidative stress and pulmonary inflammation via selective TRAF6 signaling.