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The incidence of non-suicidal self-injury (NSSI) has been on the rise in recent years. Studies have shown that people with NSSI have difficulties in emotion regulation and cognitive control. In addition, some studies have investigated the cognitive emotion regulation of people with NSSI which found that they have difficulties in cognitive emotion regulation, but there was a lack of research on cognitive emotion regulation strategies and related neural mechanisms. This study included 117 people with NSSI (age = 19.47 ± 5.13, male = 17) and 84 non-NSSI participants (age = 19.86 ± 4.14, male = 16). People with NSSI met the DSM-5 diagnostic criteria, and non-NSSI participants had no mental or physical disorders. The study collected all participants' data of Cognitive Emotion Regulation Questionnaire (CERQ) and functional magnetic resonance imaging (fMRI) to explore the differences in psychological performance and brain between two groups. Afterwards, Machine learning was used to select the found differential brain regions to obtain the highest correlation regions with NSSI. Then, Allen's Human Brain Atlas database was used to compare with the information on the abnormal brain regions of people with NSSI to find the genetic information related to NSSI. In addition, gene enrichment analysis was carried out to find the related pathways and specific cells that may have differences. The differences between NSSI participants and non-NSSI participants were as follows: positive refocusing (t = −4.74, p < 0.01); refocusing on plans (t = −4.11, p < 0.01); positive reappraisal (t = −9.22, p < 0.01); self-blame (t = 6.30, p < 0.01); rumination (t = 3.64, p < 0.01); catastrophizing (t = 9.10, p < 0.01), and blaming others (t = 2.52, p < 0.01), the precentral gyrus (t = 6.04, p FDR < 0.05) and the rolandic operculum (t = −4.57, p FDR < 0.05). Rolandic operculum activity was negatively correlated with blaming others (r = −0.20, p < 0.05). Epigenetic results showed that excitatory neurons (p < 0.01) and inhibitory neurons (p < 0.01) were significant differences in two pathways, "trans-synaptic signaling" (p < −log108) and "modulation of chemical synaptic transmission" (p < −log108) in both cells. People with NSSI are more inclined to adopt non-adaptive cognitive emotion regulation strategies. Rolandic operculum is also abnormally active. Abnormal changes in the rolandic operculum of them are associated with non-adaptive cognitive emotion regulation strategies. Changes in the excitatory and inhibitory neurons provide hints to explore the abnormalities of the neurological mechanisms at the cellular level of them. Trial registration number NCT04094623 • The use of non-adaptive cognitive emotion regulation strategies was associated with abnormal changes in the Rolandic operculum. • Changes in excitatory and inhibitory neurons and abnormal performance of related pathways may be related to changes in brain regions and the use of cognitive emotion regulation strategies. [ABSTRACT FROM AUTHOR]

Attention Deficit Hyperactivity Disorder (ADHD) is one of most prevalent neurodevelopmental disorders in children. In decades, various neurobiological diagnosis methods have been well developed, yielding ADHD classification accuracy significantly improved. To our knowledge, deep-learning-based approaches attract more interest nowadays, since they effectively learn the potential features indicating ADHD disease. However, these learned features cannot directly project to certain biomarkers that have neurobiological meanings, which greatly hinders the neurobiological findings on ADHD. To ameliorate this problem, we proposed an attention auto-encoding network (Att-AENet) under an existing binary hypothesis testing (BHT) framework. By using brain functional connectivities (FCs) as input materials, an attention mechanism was employed to calculate the weights of FCs and measure the FC significance on ADHD. Therefore, the FC biomarkers of ADHD were conveniently identified from these weights. In detail, we built two attention subnetworks with dense and two-dimension convolution structures, respectively, and then evaluated the effect of these subnetworks from the viewpoint of ADHD classification. Sequentially, we took the biomarker detection analysis on the proposed dense-based attention subnetwork for its higher classification accuracy. On the test of ADHD-200 database, it shows the Att-AENet achieves a remarkable classification result with the average accuracy of 98.9%, especially 99.9% on some large-size datasets. More importantly, the FC biomarkers, corresponding to the discriminative weights learned by our attention subnetwork, are in accord with existing reported results. It demonstrates the reliability of these biomarkers. As a result, the proposed Att-AENet well fulfills the task of ADHD biomarker detection. • An attention auto-encoding network (Att-AENet) is provided for ADHD classification. • Two attention subnetworks with dense and 2D convolution structures are discussed. • FC biomarkers are found by the weights learned from the attention subnetworks. • The biomarkers are with high validity in this high-accuracy classification system. [ABSTRACT FROM AUTHOR]

To explore the local spontaneous neural activity and whole-brain functional connectivity patterns in the resting brain of acrophobia patients. 50 patients with acrophobia and 47 healthy controls were selected for this study. All participants underwent resting-state MRI scans after enrollment. The imaging data were then analyzed using a voxel-based degree centrality (DC) method, and seed-based functional connectivity (FC) correlation analysis was used to explore the correlation between abnormal functional connectivity and clinical symptom scales in acrophobia. The severity of symptoms was evaluated using self-report and behavioral measures. Compared to controls, acrophobia patients showed higher DC in the right cuneus and left middle occipital gyrus and significantly lower DC in the right cerebellum and left orbitofrontal cortex (p < 0.01, GRF corrected). Additionally, there were negative correlations between the acrophobia questionnaire avoidance (AQ- Avoidance) scores and right cerebellum-left perirhinal cortex FC (r = −0.317, p = 0.025) and between scores of the 7-item generalized anxiety disorder scale and left middle occipital gyrus-right cuneus FC (r = −0.379, p = 0.007). In the acrophobia group, there was a positive correlation between behavioral avoidance scale and right cerebellum-right cuneus FC (r = 0.377, p = 0.007). The findings indicated that there are local abnormalities in spontaneous neural activity and functional connectivity in the visual cortex, cerebellum, and orbitofrontal cortex in patients with acrophobia. [ABSTRACT FROM AUTHOR]

[Display omitted] • Curcumin-β-cyclodextrin complex (Cur-β-CD) was prepared as a novel photosensitizer. • Cur-β-CD generated ROS upon blue light activation. • Cur-β-CD showed desirable bactericidal activity against food-borne pathogens. To overcome the poor water solubility of curcumin, a curcumin-β-cyclodextrin (Cur-β-CD) complex was prepared as a novel photosensitizer. Fourier-transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), and X-ray diffraction (XRD) were used to verify the formation of Cur-β-CD. Furthermore, the ROS generation capacity and photodynamic bactericidal effect were measured to confirm this Cur-β-CD complex kept photodynamic activity of curcumin. The result showed Cur-β-CD could effectively generate ROS upon blue-light irradiation. The plate count assay demonstrated Cur-β-CD complex possess desirable photodynamic antibacterial effect against food-borne pathogens including Staphylococcus aureus , Listeria monocytogenes and Escherichia coli. The cell morphology determined by scanning electron microscope (SEM) and transmission electron microscope (TEM) showed Cur-β-CD could cause cell deformation, surface collapse and cell structure damage of the bacteria, resulting in the leakage of cytoplasmic; while agarose gel electrophoresis and SDS-PAGE further illustrated the inactivation mechanisms by Cur-β-CD involve bacterial DNA damage and protein degradation. [ABSTRACT FROM AUTHOR]