[Expression of MicroRNA-3162-3p in Different Clinical Stages of Children with Primary Immune Thrombocytopenia and Its Significance].

OBJECTIVE: To explore the expression of microRNA-3162-3p in different clinical stages of childhood primary immune thrombocytopenia (ITP) and its significance. METHODS: Ninety-six children with ITP were enrolled and divided into new diagnosis group (n=40), persistent group (n=30) and chronic group (n=26) according to the course of disease. 80 healthy children were selected as the control group. Peripheral blood mononuclear cells (PBMNC) of ITP children and healthy children were isolated and cultured, and the expression of microRNA-3162-3p in PBMNC of subjects was detected by real-time fluorescence quantitative PCR. The contents of IL-17, IL-23, IL-10 and TGF-ß in PBMNC of subjects were determined by ELISA. The correlation between microRNA-3162-3p and platelet count, IL-17, IL-23, IL-10 and TGF-ß was analyzed. RESULTS: Compared with the control group, the expression of microRNA-3162-3p and IL-10 in PBMNC and platelet count of ITP children were significantly decreased（P < 0.05）, while IL-17, IL-23 and TGF-ß were significantly increased (P < 0.05). With the prolongation of the disease course, the expressions of microRNA-3162-3p and IL-10 in PBMNC and platelet count were significantly decreased（P < 0.05）, while the expressions of IL-17, IL-23 and TGF-ß were significantly increased (P < 0.05). The expression of microRNA-3162-3p in PBMNC was positively correlated with platelet count and IL-10 (r =0.716, 0.667), and negatively correlated with IL-17, IL-23, and TGF-ß (r =-0.540, -0.641, -0.560). CONCLUSION: MicroRNA-3162-3p expression is significantly reduced in PBMNC of children with ITP, and is involved in the regulation of Th17/Treg imbalance, which can be used as a potential therapeutic target of ITP.

Assessment of small strain modulus in soil using advanced computational models.

Small-strain shear modulus ([Formula: see text]) of soils is a crucial dynamic parameter that significantly impacts seismic site response analysis and foundation design. [Formula: see text] is susceptible to multiple factors, including soil uniformity coefficient ([Formula: see text]), void ratio (e), mean particle size ([Formula: see text]), and confining stress ([Formula: see text]). This study aims to establish a [Formula: see text] database and suggests three advanced computational models for [Formula: see text] prediction. Nine performance indicators, including four new indices, are employed to calculate and analyze the model's performance. The XGBoost model outperforms the other two models, with all three models achieving [Formula: see text] values exceeding 0.9, RMSE values below 30, MAE values below 25, VAF values surpassing 80%, and ARE values below 50%. Compared to the empirical formula-based traditional prediction models, the model proposed in this study exhibits better performance in IOS, IOA, a20-index, and PI metrics values. The model has higher prediction accuracy and better generalization ability.