Objective:To analyze the electroencephalogram (EEG) features of patients with Alzheimer’s disease (AD) and mild cognitive impairment (MCI), and to combine the characteristics for classification and prediction.Methods:One hundred and thirty-five patients attending the Department of Neurology at the General Hospital of Tianjin Medical University were enrolled, including 34 patients with AD, 67 patients with MCI, and 34 healthy control (HC). The electroencephalogram signals of these patients in the resting state were collected and preprocessed. Relative power spectral density features and sample entropy features on a multi-band scale were extracted to compare the whole-brain differences in electroencephalogram features among the 3 groups of subjects, and then subdivided into brain regions and individual leads for in-depth analysis. The above two features were fused to classify and predict AD, MCI, and HC by support vector machine (SVM).Results:The frontal regions had higher δ relative power spectral densities than the other regions, and the occipital and temporal regions showed relatively lower distributions. θ-Band relative power spectral densities had a more even distribution of sizes across brain regions. α-Band relative power spectral densities were concentrated in the occipital lobe, while β-band relative power spectral densities were mainly concentrated in the parietal and temporal lobes. Except for the central lobe, the δ-band relative power spectral densities of the AD group were higher than those of the MCI group ( P < 0.05) and HC group ( P < 0.01) in all brain regions and the whole brain. θ-band relative power spectral densities of the AD group were higher than those of the MCI gourp ( P < 0.001) and HC group ( P < 0.001) in the whole brain and in all brain regions. α-Band relative power spectral densities of the AD group were lower than those of the other groups only in the temporal lobe (all P < 0.05). The relative power spectral density of the β-band in the AD group was higher than that of the other groups in the whole brain and in all brain regions ( P < 0.05, 0.01, 0.001). The difference in the relative power spectral density of the δ-band in the C3 lead in the central lobe of the AD and HC groups was statistically significant ( P < 0.05). The relative power spectral density of the γ-band in the temporal lobe was higher than that in the other regions of the AD group, the MCI group, and the HC group. The relative power spectral density of the γ-band in the T3 lead in the AD group was significantly lower than that in the T4 lead. The average entropy of samples in the whole brain and in each brain region was lower than that in the HC group in the AD and MCI groups (all P < 0.05). The entropy of the samples at lead C3 in the AD group was lower than that in the MCI group ( P < 0.05). The differences between the relative power spectral density, sample entropy, and the actual data classification evaluation indexes (accuracy rate, precision rate, recall rate, and F1 score) that fused the two features, and the rearranged data were all statistically significant (all P < 0.001). When the relative power spectral density feature and the sample entropy feature were fused in the classification features, the best classification prediction was achieved, with an accuracy rate of 80%, a precision rate of 78%, a recall rate of 78%, and the F1 score of 79%. Conclusions:Relative power spectral density and sample entropy analysis can reveal the abnormalities of electroencephalogram activities of AD and MCI patients from different perspectives (linear and nonlinear), and the combination of these two features in classification prediction can improve the classification effect.

Objective: To investigate the impact of childhood traumatic experiences on individual risktaking decisions in early adulthood using functional nearinfrared spectroscopy (fNIRS), so as to provide the reference for clarifying the brain mechanisms underlying the impact of childhood trauma on individual risky decision. Methods: From December 2023 to March 2024, 28 children with childhood trauma experiences (trauma group) and 32 healthy college students (control group) were selected from Jining Medical University by a combination of stratified descent and convenient sampling methods. All subjects participated in the Iowa Game task fNIRS scanning. The brain activation, functional connectivity, graph theory properties (degree centrality, betweenness centrality, and local efficiency), and Receiver Operating Characteristic (ROC) analysis were performed by using preprocessing fNIRS data. Results: Compared with control group, trauma group showed significantly fewer choice times in the inferior deck (Z=-0.88), and showed significantly decreased activation levels in the right frontalpolar (Z=-2.59), as well as showed significant decreased functional connectivity between left dorsolateral prefrontal and in right dorsolateral prefrontal (Z=-3.78), and between left dorsolateral prefrontal cortex and the right frontal pole (Z=-3.68)(P<0.05). The central index of right inferior frontal gyrus in the trauma group was higher than that in the control group, while the central index of left and right dorsolateral frontal lobes was lower than that in the control group (Z=2.13, -2.53, -2.12, P<0.05). The centrality index of the right inferior frontal gyrus in the trauma group was higher than that in the control group (Z=2.47, P<0.05). The local efficiency indicators of the right inferior frontal gyrus, left and right frontal pole in the trauma group were higher than those in the control group (Z=2.51, 2.17, 2.53, P<0.05). The results of the ROC curve analysis showed that the local efficiency achieved the highest area under the curve (AUC=0.68). Conclusions Young adults with childhood trauma experience tend to choose lower loss, and the frontal pole shows a lack of activation in the whole process of risk decision performance. The abnormalities in the brain connectivity and network properties might be the neural basis of excessive defense mechanisms that childhood trauma leads to risky decisions.

Background Prolonged exposure to vibration can cause vascular endothelial injury, and inflammatory response plays an important role in vascular endothelial injury. Studies have shown that long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) is involved in regulating the expression of inflammatory injury of endothelial cells. Objective To investigate the effects of vibration on the secretion of inflammatory factors and the expression of IncRNA MEG3 by vascular endothelial cells in vitro. Methods Human umbilical vein endothelial cells (HUVEC) were divided into two categories: vibration and control. The vibration exposure included 63 Hz (6.76 m·s⁻²), 200 Hz (5.08 m·s⁻²), and 250 Hz (4.56 m·s⁻²) frequency bands, and 1 and 2 d exposure time with 1 to 4 h of daily vibration. The control treatment was the same as the vibration category except that they were not exposed to vibration. CCK-8 was used to detect the effects of different vibration frequencies and time on the viability of HUVEC. The expression levels of tumor necrosis factor-α (TNF-α), interleukin-8 (IL-8), interleukin-4 (IL-4), and interleukin-10 (IL-10) in the cells and supernatants were detected by enzyme-linked immunosorbent assay. The expression levels of IncRNA MEG3 were detected by real-time fluorescence quantitative PCR. Results Compared with the cells with the control treatment, the cell viability of the 1-day exposure group increased after 1.5 h and 3 h of vibration at 63 Hz, while decreased after 2 h and 2.5 h; the cell viability of the 2-day exposure group increased at the frequency of 63 Hz for 1.5 h, but decreased at 2 h and 2.5 h. At the frequency of 200 Hz, the cell viability of the 1-day exposure group increased at 2 h and 4 h, but decreased at 2.5 h and 3 h; the cell viability of the 2-day exposure group increased at 1.5 h and decreased at 2.5 h. For the vibration exposure at frequency of 250 Hz, the cell viability of the 1-day exposure group increased at 1.5 h and 2.5 h, but decreased at 3 h; of the 2-day exposure group, the cell viability increased at 1.5 h and decreased at 3 h. For the exposure settings of 63 and 200 Hz vibration for 2.5 h and 250 Hz vibration for 3 h, and with the control treatment as reference, the expression levels of TNF-α, IL-8, IL-4, and IL-10 in cells and supernatants were increased in the 1 d and 2 d exposures; the expression level of lncRNA MEG3 decreased in the 1 d exposure group; however, for the 2 d exposure, the expression level of lncRNA MEG3 decreased only in the 63 Hz vibration exposure. All of these results were statistically significant (P<0.05). Conclusion Vibration could induce an increase in the levels of inflammatory factors TNF-α, IL-8, IL-4, and IL-10 and a decrease in the expression level of lncRNA MEG3 in vascular endothelial cells in vitro.