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BackgroundMaternal exposure to inflammation is one of the causes of autism spectrum disorder (ASD). Electrical stimulation of the vagus nerve exerts a neuroprotective effect via its anti-inflammatory action. We thus investigated whether transcutaneous auricular vagus nerve stimulation (taVNS) can enhance social abilities in a mouse model of ASD induced by maternal immune activation (MIA).MethodsASD mouse model were constructed by intraperitoneal injection of polyinosinic:polycytidylic acid (poly (I:C)). TaVNS with different parameters were tested in ASD mouse model and in C57BL/6 mice, then various behavioral tests and biochemical analyses related to autism were conducted. ASD model mice were injected with an interleukin (IL)-17a antibody into the brain, followed by behavioral testing and biochemical analyses.ResultsTaVNS reduced anxiety, improved social function, decreased the number of microglia, and inhibited M1 polarization of microglia. Additionally, taVNS attenuated the expression of the IL-17a protein in the prefrontal cortex and blood of ASD model mice. To examine the possible involvement of IL-17a in taVNS-induced neuroprotection, we injected an IL-17a antibody into the prefrontal cortex of ASD model mice and found that neutralizing IL-17a decreased the number of microglia and inhibited M1 polarization. Furthermore, neutralizing IL-17a improved social function in autism model mice.ConclusionOur study revealed that reduced neuroinflammation is an important mechanism of taVNS-mediated social improvement and neuroprotection against autism. This effect of taVNS could be attributed to the inhibition of the IL-17a pathway.

The Objectives of this study are (1) to evaluate tone production in Mandarin-speaking patients with post-stroke dysarthria (PSD) using an artificial neural network (ANN), (2) to investigate the efficacy of recognition performance of the ANN model contrast to the human listeners and the convolutional neural network (CNN) model, and (3) to explore rehabilitation application of the artificial intelligence recognition for lexical tone production disorder with PSD. The subjects include two groups of native Mandarin speaking adults: 31 patients with PSD and 42 normal-speaking adults (NA) in a similar age range as controls. Each subject was recorded producing a list of 7 Mandarin monosyllables with 4 tones (i.e., a total of 28 tokens). The fundamental frequency (F0) of each monosyllable was extracted using auto-correlation algorithm. The ANN was trained with F0 data of the tone tokens from the NA, to generate the final model. The recognition rates of the human ears, ANN model, and CNN model were 87.78% ± 8.96% (mean ± SD), 89.11% ±11.80%, 65.91% ± 8.79% respectively for tone production of NA group; 70.28% ± 17.61%, 63.35% ± 17.40%, 34.71% ± 6.92% respectively for tone production of PSD group. For PSD group, there was significant correlation between the performance of the ANN model and human listeners (r = 0.826, P