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Objective:To explore the effect of Xingnao Kaiqiao acupuncture treatment on brain network reorganization for the patients with stroke recovery, and therefore understand the neural mechanism underlying Xingnao Kaiqiao acupuncture treatment.Methods:Prospective case series study. Thirteen acute ischemia stroke patients were recruited from the Department of Neurology, Shanghai Minhang Hospital of Integrated Traditional Chinese and Western Medicine from Aug 2018 to Oct 2019. They were treated with Xingnao Kaiqiao acupuncture once a day for 10 consecutive days in addition to routine treatments, and received clinical assessments before treatment and 14 days after treatment onset. EEG signals were recorded during the first acupuncture treatment, from before inserting the needles (the baseline), during needle retention, to after removal of the needles. The brain network was constructed using phase locking index, and its clustering coefficient (CC), characteristic path length (PL) and small-worldness (S) were analyzed using one-way repeated ANOVA.Results:Compared with the baseline, the CC of delta-band network (sparsity=0.10: t=3.306, P=0.006; 0.12: t=2.909, P=0.013; 0.14: t=2.331, P=0.038) and the PL of delta-band (sparsity=0.12: t=3.236, P=0.007; 0.14: t=2.754, P=0.017, 0.18: t=2.878, P=0.014) and alpha-band (sparsity=0.10: t=2.432, P=0.032) networks were significantly decreased during the needle retention stage. Clinical assessments demonstrated a significant treatment efficacy of Xingnao Kaiqiao acupuncture, and its efficacy which was indicated by improved NIHSS score, was significantly correlated with the CC changes in the delta band network from baseline to needle retention. The correlation was strongest when the network sparsity was 0.12 ( r=0.78, P=0.002). Conclusion:Xingnao Kaiqiao acupuncture can regulate the brain network of stroke patients in real time, and this immediate regulation maybe associated with its treatment effect.
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Affective brain-computer interfaces (aBCIs) has important application value in the field of human-computer interaction. Electroencephalogram (EEG) has been widely concerned in the field of emotion recognition due to its advantages in time resolution, reliability and accuracy. However, the non-stationary characteristics and individual differences of EEG limit the generalization of emotion recognition model in different time and different subjects. In this paper, in order to realize the recognition of emotional states across different subjects and sessions, we proposed a new domain adaptation method, the maximum classifier difference for domain adversarial neural networks (MCD_DA). By establishing a neural network emotion recognition model, the shallow feature extractor was used to resist the domain classifier and the emotion classifier, respectively, so that the feature extractor could produce domain invariant expression, and train the decision boundary of classifier learning task specificity while realizing approximate joint distribution adaptation. The experimental results showed that the average classification accuracy of this method was 88.33% compared with 58.23% of the traditional general classifier. It improves the generalization ability of emotion brain-computer interface in practical application, and provides a new method for aBCIs to be used in practice.
Assuntos
Humanos , Algoritmos , Interfaces Cérebro-Computador , Eletroencefalografia , Emoções , Reprodutibilidade dos TestesRESUMO
Objective:To explore the association of tumor associated macrophages (TAM) with tumor invasiveness, metastasis and prognosis in cardia carcinoma tissues.Methods:The cancer tissues and pericarcinomatous tissues of 100 patients with cardia carcinoma who underwent D2 radical operation in the First Hospital of Putian City from January 2014 to January 2015 were collected. M2-type TAM was marked with CD163. The tissue microarray was made and the expression of CD163 in microarray tissues was detected by using immunohistochemistry. The median number of CD163 positive cells in all cancer tissues was taken as the cut-off value. The patients with the mean number of CD163 positive cells ≥ the cut-off value were those with high TAM infiltration, and vice versa. The association of TAM infiltration with clinicopathological features and prognosis was analyzed, and Cox proportional hazards model was used for multivariate analysis of survival.Results:The positive cell median number of CD163 in cardia carcinoma tissues was higher than that in adjacent tissues [the median number ( P25, P75): 32/high power field (HP) (16/HP, 46/HP) vs. 6/HP (4/HP, 11/HP)], and the difference was statistically significant ( Z = -35.044, P < 0.01). There were 48 cases in low invasive group (< 32/HP) and 52 cases in high invasive group (≥32/HP). The proportion of patients with high TAM infiltration in serosa and extraserosa was higher than that in mucosa and muscle [60.9% (39/64) vs. 36.1% (13/36)], and the proportion of patients with high TAM infiltration for patients with lymph node metastasis was higher than that for patients without lymph node metastasis [61.8% (42/68) vs. 31.3% (10/32)], and the proportion of patients with high TAM infiltration for those with TNM stage Ⅲ-Ⅳ was higher than that for those with TNM stage Ⅰ-Ⅱ [64.4% (38/59) vs. 34.1% (14/41)], and the differences were statistically significant (all P < 0.05). The median overall survival time of high TAM group was shorter than that of low TAM group [24.00 months (95% CI 17.25-43.50 months) vs. 62.00 months (95% CI 34.00-68.00)], and the difference in overall survival was statistically significant (χ 2 = 18.137, P < 0.01). Lymph node metastasis ( HR = 0.301, 95% CI 0.105-0.862, P = 0.025), TNM staging ( HR = 8.404, 95% CI 2.810-25.133, P < 0.01) and TAM infiltration level in cancer tissues ( HR = 4.277, 95% CI 2.372-7.712, P < 0.01) were independent influencing factors for overall survival of patients. Conclusions:TAM plays an important role in the invasion and metastasis of cardia carcinoma and can be used as an independent predictor of biological behavior and prognosis in cardia carcinoma.