[Electroencephalogram feature extraction and classification of autistic children based on recurrence quantification analysis].

Extraction and analysis of electroencephalogram (EEG) signal characteristics of patients with autism spectrum disorder (ASD) is of great significance for the diagnosis and treatment of the disease. Based on recurrence quantitative analysis (RQA)method, this study explored the differences in the nonlinear characteristics of EEG signals between ASD children and children with typical development (TD). In the experiment, RQA method was used to extract nonlinear features such as recurrence rate (RR), determinism (DET) and length of average diagonal line (LADL) of EEG signals in different brain regions of subjects, and support vector machine was combined to classify children with ASD and TD. The research results show that for the whole brain area (including parietal lobe, frontal lobe, occipital lobe and temporal lobe), when the three feature combinations of RR, DET and LADL are selected, the maximum classification accuracy rate is 84%, the sensitivity is 76%, the specificity is 92%, and the corresponding area under the curve (AUC) value is 0.875. For parietal lobe and frontal lobe (including parietal lobe, frontal lobe), when the three features of RR, DET and LADL are combined, the maximum classification accuracy rate is 82%, the sensitivity is 72%, and the specificity is 92%, which corresponds to an AUC value of 0.781. The research in this paper shows that the nonlinear characteristics of EEG signals extracted based on RQA method can become an objective indicator to distinguish children with ASD and TD, and combined with machine learning methods, the method can provide auxiliary evaluation indicators for clinical diagnosis. At the same time, the difference in the nonlinear characteristics of EEG signals between ASD children and TD children is statistically significant in the parietal-frontal lobe. This study analyzes the clinical characteristics of children with ASD based on the functions of the brain regions, and provides help for future diagnosis and treatment.

Lipopolysaccharides induces MUC5AC overproduction in human nasal epithelium.

Hyperproduction of mucin in the nasal epithelium is an important feature of nasal inflammatory diseases. We investigated the mechanism of lipopolysaccharides (LPS) involvement in mucin 5 subtype AC (MUC5AC) expression in human nasal epithelial cells. The primary human nasal epithelial cells were cultured in vitro, which were treated with LPS (10 nM/ml or 1 µM/ml) for 12 and 24 h. LPS-induced MUC5AC protein was determined in nasal epithelial cells. The levels of nuclear factor kappa B p65 (NF-κBp65) and its inhibitor kappa Bα (IκBα) protein were also detected, and interleukin-1ß (IL-1ß) mRNA was detected by real-time PCR. LPS up-regulated MUC5AC protein in human nasal epithelial cells, and we determined that the up-regulation of MUC5AC expression was due to a time- and dose-dependent degradation of IκBα protein, which resulted in the increase of NF-κBp65 nuclear translocation. Subsequently, we also determined that LPS can induce IL-1ß mRNA in a time- and dose-dependent manner. These data show that LPS treatment activated NF-κB by promoting the degradation of IκBα and the nuclear localization of NF-κBp65, which induced MUC5AC overproduction.

Effects of 1Hz repetitive transcranial magnetic stimulation on autism with intellectual disability: A pilot study.

OBJECTIVE: To explore whether 1 Hz repetitive transcranial magnetic stimulation (rTMS) has positive effects on brain activity and behavior of autistic children with intellectual disability. METHODS: 32 autistic children with intellectual disability (26 boys and 6 girls) were recruited to participate in this feasibility study. The autistic children were divided randomly and equally into an experimental group and a control group. 16 children (three girls and 13 boys; mean ± SD age: 7.8 ± 2.1 years) who received rTMS treatment twice a week were served as the experimental group, while 16 children (three girls and 13 boys; mean ± SD age: 7.2 ± 1.6 years) with sham stimulation were considered as the control group. Recurrence quantification analysis (RQA) was employed to quantify the nonlinear features of electroencephalogram (EEG) signals recorded during the resting state. Three RQA measures, including recursive rate (RR), deterministic (DET) and mean diagonal length (L) were extracted from the EEG signals to characterize the deterministic features of cortical activity. RESULTS: Significant differences in RR and DET were observed between the experimental group and the control group. We also found discernible discrepancies in the Autism Behavior Checklist (ABC) score pre- and post-rTMS for the experimental group. CONCLUSIONS: 1 Hz repetitive transcranial magnetic stimulation (rTMS) could positively influence brain activity and behavior of autistic children with intellectual disability.