Background: Researches have found that alteration of intestinal flora may be closely related to the development of autism spectrum disorder (ASD). However, whether probiotics supplementation has a protective effect on ASD remains controversial. This meta-analysis aimed to analyze the outcome of probiotics in the treatment of ASD children. Methods: The Pubmed, Cochrane Library, Web of Science and Embase were searched until Sep 2022. Randomized controlled trials (RCTs) relevant to the probiotics and placebo treatment on ASD children were screened. Quality assessment of the included RCTs was evaluated by the Cochrane collaboration’s tool. The primary outcomes were ASD assessment scales, including ABC (aberrant behavior checklist) and CBCL (child behavior checklist) for evaluating the behavior improvement, SRS (social responsiveness scale) for social assessment, DQ (developmental quotient) for physical and mental development and CGI-I (clinical global impression improvement) for overall improvement. The secondary outcome was total 6-GSI (gastrointestinal severity index). Results: In total, 6 RCTs from 6 studies with 302 children were included in the systemic review. Total 6-GSI (MD=-0.59, 95%CI [-1.02,-0.17], P<0.05) decreased significantly after oral administration of probiotics. Whereas, there was no statistical difference in ABC, CBCL, SRS, DQ and CGI-I between probiotics and placebo groups in ASD children. Conclusion: Probiotics treatment could improve gastrointestinal symptoms, but there was no significant improvement in ASD.

Background: Regulatory T (Treg) cells are a class of anti-inflammatory lymphocyte subpopulations with a potential protective effect against atherosclerosis, whereas T helper 17 (Th17) cells have been reported to possess proatherogenic activity. It was believed that disturbed circulating Treg/Th17 balance was associated with the onset and progression of atherosclerosis. This study is designed to probe the regulative action of serum Nod-like receptor protein 3 (NLRP3) on the Treg/Th17 balance in patients with atherosclerosis. Methods: Fifty-two patients with coronary atherosclerosis and stenosis degrees of more than 50% were assigned to the coronary artery disease (CAD) group, and an equal number of people without coronary atherosclerosis were assigned to the control group (assessed by coronary angiography). Peripheral blood mononuclear cells (PBMCs) from two group patients were extracted and cultivated. The calculation of the Treg/Th17 ratio and quantitative analysis of the Treg and Th17 cell frequencies were performed through flow cytometry. Real-time fluorescence quantitative polymerase chain reaction (RT-PCR) was executed for the quantitative mRNA detection of the fork headwinged helix transcription factor (Foxp3) and the retinoic acid-related orphan nuclear receptor C (RORC) in PBMCs. Enzyme-linked immunosorbent assays were applied to measure the serum level of NLRP3, interleukin (IL)-10, IL-1β, IL-17A, IL-23, and transforming growth factor (TGF)-β1. Additionally, the connection between serum Treg/Th17 ratio and NLRP3 levels was analyzed using the Pearson correlation coefficient. Results: The baseline parameters, including sex, age, or blood biochemical indices had no difference in both groups (p > 0.05). The CAD group showed higher Th17 cell frequency, lower Treg cell frequency, and a lower Treg/Th17 ratio when compared to the control (p < 0.05). Consistent with the variation in the T-cell subset ratio, in patients with atherosclerosis, the Th17cell-related transcription factor RORC showed a markedly higher mRNA level (p < 0.05), conversely, the mRNA expression of the Treg cell-related transcription factor Foxp3 was notably reduced (p < 0.05). Similarly, the serum levels of NLRP3, IL-17A, IL-1, and IL-23 were significantly enhanced in CAD group but IL-10 and TGF-β1 were reduced (p < 0.05). Additionally, a negative correlation was found between NLRP3 and the Treg/Th17 ratio (r = -0.69, p < 0.001). Conclusions: Due to the potential impact on the serum Treg/Th17 ratio, NLRP3 may act as an aggravator in the onset and progression of atherosclerotic disease.

Automatic speaking assessment methods are essential for helping non-native learners to learn native pronunciation. The automated speaking assessment method consists of mispronunciation detection and pronunciation quality assessment. In the past, researchers have usually focused their research on only one specific aspect of the speaking assessment task. Research on multifaceted speaking tasks has been rare, and model building has often led to reduced performance due to the omission of local feature details. In this paper, we propose a multi-width band (MB) method and apply it to the Conformer model. This method can effectively increase the ability of the model to obtain local feature information at different scales. At the same time, we used a multi-task learning approach to train a multifaceted speaking assessment model based on GOP features. We conducted experiments on a self-built monosyllabic Mandarin mispronunciation detection dataset (PSC-MonoSyllable) and an English open-source pronunciation quality assessment dataset (SpeechOcean762), respectively. The experimental results show that the method's mispronunciation detection metrics in terms of phonemes, tones, and words on the PSC-MonoSyllable dataset (F1 scores) reached 70.18%, 80.06%, and 79.82%, respectively. The results of the method on the SpeechOcean 762 dataset for the pronunciation quality assessment task also showed a certain degree of improvement in all aspects of the phoneme-and grapheme-level correlation metrics compared with the baseline model.

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