基于网络药理学和分子对接技术探讨黄芪干预腹膜纤维化的机制

目的 运用网络药理学方法及分子对接技术探讨黄芪干预腹膜纤维化的可能机制。方法 利用中药系统药理学数据库及分析平台(TCMSP)检索黄芪的主要化学成分及靶点,并补充文献报道相关药理作用的成分作为潜在活性成分。以"peritoneal fibrosis"为关键词分别在OMIM、Genecards获取目前已知的与腹膜纤维化相关的疾病靶点,后取两者的交集靶点;对交集基因通过STRING数据库与Cytoscape 3.7.2软件构建"药物-成分-靶点-疾病"网络及蛋白互作(PPI)网络并筛选核心网络。基于R软件使用Bioconductor生物信息软件对核心靶点进行GO及KEGG富集分析,最终采用AutoDock软件将主要有效成分与核心靶点进行分子对接,得出其结合能力。结果 筛选出20个黄芪活性成分及文献报道有相关药理作用4个, 457药物作用靶点,与674个腹膜纤维化病靶点取交集,得到86个共同靶点。GO功能富集分析提示黄芪拮抗腹膜纤维化主要参与了蛋白激酶B信号转导的调节、细胞对化学的应激反应、炎症反应的调节等通路; KEGG通路富集分析主要涉及调控肿瘤、磷脂酰肌醇-3-羟激酶-蛋白激酶B(PI3K-Akt)、晚期糖基化终末产物/晚期糖基化终末产物受体(AGE-RAGE)、人类巨细胞病毒感染、HIF-1信号通路等;分子对接结果显示关键靶点与活性成分具有较好的结合能力。结论 黄芪治疗腹膜纤维化的分子机制,可能与抑制炎症及氧化应激反应、调节多种信号通路等相关。     

基于雨课堂的临床流行病学教学改革与实践

目的探讨雨课堂在临床流行病学教学中的作用和效果。方法采用随机对照法在本科阶段无流行病学学习经历的临床专业硕士研究生中,使用雨课堂线上课前预习及课后随堂练习的功能,用于评价雨课堂线上功能的辅助教学效果。结果应用雨课堂线上功能干预组与对照组在基线、阶段小测和末考卷面成绩均无统计学差异;但对于主动学习,雨课堂参与度较高的学生成绩提高明显。结论雨课堂有利于理论性较强课程的学习,但是仍不能忽略课堂教学师生互动过程。     

Estimation of phase signal change in neuronal current MRI for evoke response of tactile detection with realistic somatosensory laminar network model

Magnetic field generated by neuronal activity could alter magnetic resonance imaging (MRI) signals but detection of such signal is under debate. Previous researches proposed that magnitude signal change is below current detectable level, but phase signal change (PSC) may be measurable with current MRI systems. Optimal imaging parameters like echo time, voxel size and external field direction, could increase the probability of detection of this small signal change. We simulate a voxel of cortical column to determine effect of such parameters on PSC signal. We extended a laminar network model for somatosensory cortex to find neuronal current in each segment of pyramidal neurons (PN). 60,000 PNs of simulated network were positioned randomly in a voxel. Biot–savart law applied to calculate neuronal magnetic field and additional phase. The procedure repeated for eleven neuronal arrangements in the voxel. PSC signal variation with the echo time and voxel size was assessed. The simulated results show that PSC signal increases with echo time, especially 100/80 ms after stimulus for gradient echo/spin echo sequence. It can be up to 0.1 mrad for echo time = 175 ms and voxel size = 1.48 × 1.48 × 2.18 mm³. With echo time less than 25 ms after stimulus, it was just acquired effects of physiological noise on PSC signal. The absolute value of the signal increased with decrease of voxel size, but its components had complex variation. External field orthogonal to local surface of cortex maximizes the signal. Expected PSC signal for tactile detection in the somatosensory cortex increase with echo time and have no oscillation.     

Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.     

Exact confidence intervals for the average causal effect on a binary outcome

Based on the physical randomization of completely randomized experiments, in a recent article in Statistics in Medicine, Rigdon and Hudgens propose two approaches to obtaining exact confidence intervals for the average causal effect on a binary outcome. They construct the first confidence interval by combining, with the Bonferroni adjustment, the prediction sets for treatment effects among treatment and control groups, and the second one by inverting a series of randomization tests. With sample size n, their second approach requires performing O(n⁴)randomization tests. We demonstrate that the physical randomization also justifies other ways to constructing exact confidence intervals that are more computationally efficient. By exploiting recent advances in hypergeometric confidence intervals and the stochastic order information of randomization tests, we propose approaches that either do not need to invoke Monte Carlo or require performing at most O(n²)randomization tests. We provide technical details and R code in the Supporting Information . Copyright © 2016 John Wiley & Sons, Ltd.