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。     

The National Home-Based Primary Care Learning Network: A Practice-Based Quality Improvement and Research Network

Home-based primary care (HBPC) provides interdisciplinary, comprehensive care at home for homebound older adults and has been largely excluded from the national conversation on care quality and quality improvement. In this Pragmatic Innovations article, we describe the work of the National HBPC Learning Network (LN), which focuses on fostering a continuous learning culture among HBPC practices to improve practice quality, elevate the field of HBPC, and create a community of continuous growth and quality of care accountability. The LN recruits HBPC practices in waves of 9 to 10 practices. It currently comprises 38 HBPC practices that care for 58,000 patients across 25 states (approximately 26% of all patients receiving HBPC in the United States). In a Kickoff meeting, the HBPC practices in each wave are instructed in the basics of quality improvement, develop project aim statements and their first plan-do-study-act cycle, receive an introduction to the LN quality improvement software platform, and review plans for LN engagement. Each month, practices submit updates and receive real-time feedback on their quality improvement work. Monthly virtual workshops are held with all practices that include sharing results of a “1-minute survey” (a monthly 1-to 3-question survey sent to all LN participants on a topic relevant to HBPC practices), a didactic and discussion related to the 1-minute survey topic, and interactive progress updates from LN participants regarding their quality improvement work. Each wave ends with “Moving-up Day,” where practices report on their overall project and reflect on how their practice has changed as a result of the LN. LN practices have addressed and improved performance in multiple HBPC-related quality areas including assessment of functional status and cognitive impairment, falls prevention, advanced care planning, COVID-19 vaccination, and others. We present case studies of 3 LN practices and how LN participation strengthened their practices.     

基于网络药理学和分子对接技术分析筒鞘蛇菰多糖治疗肝损伤的作用机制及体内实验研究＊

目的 基于网络药理学探讨并分析筒鞘蛇菰（Balanophora involucrata Hook. f.，BIH）治疗肝损伤的作用及分子机制，并通过大鼠体内实验验证相关预测靶点及筒鞘蛇菰提取物-蛇菰多糖（Polysaccharides of Balanophora involucrata Hook. f.，BPS）对实验性肝损伤的保护作用。方法 化学专业数据库、TCMID和TCMSP平台检索筒鞘蛇菰组成的化合物及可能靶点，以肝损伤为关键词检索GeneCards和网站，获得相关靶点，绘制Venn图，选交集靶点，将“化合物-靶点和疾病-靶点”关系导入Cytoscape V3.7.2软件，获得化合物-靶点-疾病的三重网络，对化合物及相关靶点蛋白行分子对接，并用交集靶点绘制蛋白互作网络图及进行GO生物功能和KEGG信号途径富集分析。结果 筒鞘蛇菰主要成分有11个化合物，其中与肝损伤有37个交集靶点，高度关联靶点包括NOS3、ESR1、TNF、MAOA、PTGS2、IL10等，GO和KEGG富集分析发现筒鞘蛇菰治疗肝损伤的分子机制，可能与调节肾上腺素能信号通路、cGMP-PKG信号及神经活性配体-受体交互通路等有关，而且ADRA1B、ADRA2A、ADRA2C、ADRB1/2等基因高度富集于这些通路中。动物体内实验发现BPS灌胃处理可减轻肝组织损伤、调控血清炎症因子肿瘤坏死因子α（Tumor necrosis factor， TNF-α）和白细胞介素10（IL-10）水平、提高抗氧化酶超氧化物歧化酶（superoxide dismutase，SOD）活性，并增强肝组织内氧化应激相关蛋白核因子E2相关因子2（NF-E2-related factor 2，NRF2）和醌NADH脱氢酶1（NQO1）的表达，从而抑制大鼠体内氧化应激损伤、减轻炎症反应和细胞凋亡，达到保护实验性肝损伤的作用。结论 本研究初步确定筒鞘蛇菰治疗肝损伤的有效成分、“化合物-蛋白-靶点”关联网络及发挥作用的分子机制，并通过动物体内实验证实蛇菰多糖保护肝损伤的机制与上调NRF2/NQO1通路来减轻氧化应激反应性损伤、减轻肝细胞凋亡有关。     

Mechanism of action of Orthosiphon stamineus against non-alcoholic fatty liver disease: Insights from systems pharmacology and molecular docking approaches

Non-alcoholic fatty liver disease (NAFLD) is one of the most common complications of a metabolic syndrome caused by excessive accumulation of fat in the liver. Orthosiphon stamineus also known as Orthosiphon aristatus is a medicinal plant with possible potential beneficial effects on various metabolic disorders. This study aims to investigate the in vitro inhibitory effects of O. stamineus on hepatic fat accumulation and to further use the computational systems pharmacology approach to identify the pharmacokinetic properties of the bioactive compounds of O. stamineus and to predict their molecular mechanisms against NAFLD. Methods: The effects of an ethanolic extract of O. stamineus leaves on cytotoxicity, fat accumulation and antioxidant activity were assessed using HepG2 cells. The bioactive compounds of O. stamineus were identified using LC/MS and two bioinformatics databases, namely the Traditional Chinese Medicine Integrated Database (TCMID) and the Bioinformatics Analysis Tool for the Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Pathway enrichment analysis was performed on the predicted targets of the bioactive compounds to provide a systematic overview of the molecular mechanism of action, while molecular docking was used to validate the predicted targets. Results: A total of 27 bioactive compounds corresponding to 50 potential NAFLD-related targets were identified. O. stamineus exerts its anti-NAFLD effects by modulating a variety of cellular processes, including oxidative stress, mitochondrial β-oxidation, inflammatory signalling pathways, insulin signalling, and fatty acid homeostasis pathways. O. stamineus is significantly targeting many oxidative stress regulators, including JNK, mammalian target of rapamycin (mTOR), NFKB1, PPAR, and AKT1. Molecular docking analysis confirmed the expected high affinity for the potential targets, while the in vitro assay indicates the ability of O. stamineus to inhibit hepatic fat accumulation. Conclusion: Using the computational systems pharmacology approach, the potentially beneficial effect of O. stamineus in NAFLD was indicated through the combination of multiple compounds, multiple targets, and multicellular components.     

基于系统药理学分析野生真菌硬皮马勃治疗肿瘤多层次作用机制＊

目的 鉴定当地民间应用普遍的野生药用真菌，并探讨其治疗肿瘤的作用机制。方法 采用形态学和分子生物学方法对一株采自定陶仿山野生药用真菌进行鉴定，确定为硬皮马勃。通过文献检索收集硬皮马勃化学成分，利用PubChem软件和TCMSP、GCS数据库得到化学成分结构信息及其药用动力学参数和相关靶点分析，通过SysDT和WES系统鉴定潜在化学成分靶点，利用CTD数据库获得靶点功能，将潜在化合物和肿瘤相关靶点导入Cytoscape3.8.0软件构建分子-靶标网络。应用DAVID数据库对肿瘤相关靶点进行GO和KEGG富集分析，揭示有关活性成分靶点所涉及的生物学过程和通路，将肿瘤相关靶点和通路导入Cytoscape3.8.0软件构建靶点-通路网络。结果 从文献中获得硬皮马勃的化学成分59个，通过ADME计算系统筛选出5个潜在活性的化合物即活性成分，预测到38个靶点，其中与肿瘤相关靶点16个。这些活性成分主要通过Toll-like receptor、PI3K-AKT、MAPK和NF-kappa B等通路参与免疫应答，抑制肿瘤细胞生长、增殖，促进其凋亡。结论 表明硬皮马勃治疗肿瘤具有多靶点、多途径协同作用的特点，并通过多层次效应达到治疗肿瘤的效果。本研究为更好理解硬皮马勃作用肿瘤的机制和肿瘤药物开发提供理论依据。     

Method’s corner: Allergist’s guide to network meta-analysis

Network meta-analyses (NMAs) simultaneously estimate the effects of multiple possible treatment options for a given clinical presentation. For allergists to benefit optimally from NMAs, they must understand the process and be able to interpret the results. Through a worked example published in Pediatric Allergy and Immunology, we summarize how to identify credible NMAs and interpret them with a focus on recent innovations in the GRADE approach (Grading of Recommendations Assessment, Development, and Evaluation). NMAs build on traditional systematic reviews and meta-analyses that consider only direct paired comparisons by including indirect evidence, thus allowing the simultaneous assessment of the relative effect of all pairs of competing alternatives. Our framework informs clinicians of how to identify credible NMAs and address the certainty of the evidence. Trustworthy NMAs fill a critical gap in providing key inferences using direct and indirect evidence to inform clinical decision making when faced with more than two competing courses of treatment options. This document will help allergists to identify trustworthy NMAs to enhance patient care.     

Assessment of a novel deep learning-based marker-less motion capture system for gait study

BackgroundMarker-less systems based on digital video cameras and deep learning for gait analysis could have a deep impact in clinical routine. A recently developed system has shown promising results in terms of joint center position but has not been yet evaluated in terms of gait outcomes.Research questionHow does this novel marker-less system compare to a marker-based reference system in terms of clinically relevant gait parameters?MethodsThe deep learning method behind the developed marker-less system was trained on a dedicated dataset consisting of forty-one asymptomatic and pathological subjects each performing ten walking trials. The system could estimate the three-dimensional position of seventeen joint centers or keypoints (e.g., neck, shoulders, hip, knee, and ankles). We evaluated the marker-less system against a marker-based system in terms of differences in joint position (Euclidean distance), detection of gait events (e.g., heel strike and toe-off), spatiotemporal parameters (e.g., step length, time), kinematic parameters (e.g., hip and knee extension-flexion), and inter-trial reliability for kinematic parameters.ResultsThe marker-less system was able to estimate the three-dimensional position of joint centers with a mean difference of 13.1 mm (SD = 10.2 mm). 99% of the estimated gait events were estimated within 10 ms of the corresponding reference values. Estimated spatiotemporal parameters showed zero bias. The mean and standard deviation of the differences of the estimated kinematic parameters varied by parameter (for example, the mean and standard deviation for knee extension flexion angle were −3.0° and 2.7°). Inter-trial reliability of the measured parameters was similar to that of the marker-based references.SignificanceThe developed marker-less system can measure the spatiotemporal parameters within the range of the minimum detectable changes obtained using the marker-based reference system. Moreover, except for hip extension flexion, the system showed promising results in terms of several kinematic parameters.     

国内健康信息研究作者合著网络及研究主题分析

目的分析核心作者、作者合著网络特征,推测国内健康信息研究的发展阶段、主要研究力量及主要研究主题。方法以CNKI期刊库为数据源,以"健康信息"及相关词为主题词,检索2000—2018年的相关文献,基于普莱斯定律及综合指数法确定核心作者,使用数据统计软件Excel及社会网络分析软件Vcinet,利用综合指数以及社会网络分析法计算作者间联系合作紧密度,并离析高产合作子网。结果文献量以较快指数型速率增长。作者合作率较高且信息传输渠道较通畅,2000—2018年国内研究的合著率稳定在80%,但学者的合作关系较为单一,多集中在同一机构或同一师门,阻碍了跨机构学者的交流合作。主要合作团队活跃度较高且核心成员多为研究领域的核心作者,科研产出量较大且被引频次较高。结论国内研究正处于旺盛发展期,但未形成稳定的核心作者群体。学者间因同机构或师门关系产生固定合作,健康信息管理、公众健康行为、健康教育等为核心作者或活跃团队研究的主要主题。