基于CiteSpace可视化分析代谢组学在中医药领域的研究现状及趋势＊

目的 应用可视化方法分析代谢组学在中医药领域的现状及趋势。方法 检索中国知网数据库（CNKI）和Web of Science 核心合集数据库2021年3月15日之前收录的中医药领域代谢组学研究的相关文献，应用CiteSpace软件对纳入的文献进行关键词、作者、研究机构等内容进行可视化分析。结果 共纳入中文文献247篇，英文文献350篇。文献数量在波动中迅速上升。中、英文文献作者合作网络显示，张爱华是中医药领域代谢组学研究发文量最多的作者，并形成了核心研究团队。发文机构显示，中国医学科学院是该领域的重要研究机构，机构间合作紧密。中、英文文献关键词分析显示，研究内容主要集中在核磁共振、代谢标记物、冠心病、质谱技术、代谢通路等相关领域。结论 中医药领域代谢组学研究的热点主要为中医药治疗代谢性疾病的机制研究。研究趋势为卵泡代谢组学研究及中药有效成分的研究。     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Worry as a mechanism of the relationship between perceived new knowledge and discouragement to smoke elicited from graphic cigarette warnings

Journal of Behavioral Medicine - Evidence supports the use of graphic warnings to educate the public about the health harms of smoking and suggests warnings eliciting negative emotional responses...     

Confounded association between proton pump inhibitor use and risk of biliary tract cancer: Result from three cohorts

Recent epidemiological studies suggested that proton pump inhibitor (PPI) use was associated with an increased risk of biliary tract cancer (BTC), however, confounders were not adequately controlled. Our study aimed to evaluate PPI use and subsequent risk of BTC and its subtypes in three well-established cohorts. We conducted a pooled analysis of the subjects free of cancers in UK Biobank (n = 463 643), Nurses' Health Study (NHS, n = 80 235) and NHS II (n = 95 869). Propensity score weighted Cox models were used to estimate marginal HRs of PPIs use on BTC risk, accounting for potential confounders. We documented 284 BTC cases in UK Biobank (median follow-up: 7.6 years), and 91 cases in NHS and NHS II cohorts (median follow-up: 15.8 years). In UK biobank, PPI users had a 96% higher risk of BTC compared to nonusers in crude model (HR 1.96, 95% CI 1.44-2.66), but the effect was attenuated to null after adjusting for potential confounders (HR 0.95, 95% CI 0.60-1.49). PPI use was not associated with risk of BTC in the pooled analysis of three cohorts (HR 0.93, 95% CI 0.60-1.43). We also observed no associations between PPI use with risk of intrahepatic (HR 1.00, 95% CI 0.49-2.04), extrahepatic bile duct (HR 1.09, 95% CI 0.52-2.27) and gallbladder cancers (HR 0.66, 95% CI 0.26-1.66) in UK Biobank. In summary, regular use of PPIs was not associated with the risk of BTC and its subtypes.     

Experimental study on the biocompatibility and osteogenesis induction ability of PLLA/DDM scaffolds

Odontology - To investigate the characterization and function of a novel porous osteogenic material (PLLA / DDM) containing polylactic acid and demineralized dentin matrix. The surface morphology...     

特发性肺纤维化急性加重期证候与血清生物标志物的相关性研究＊

目的 通过分析特发性肺纤维化急性加重期（AE-IPF）患者证候与血清生物标志物的关系，为中医辨证治疗提供参考。方法 采用观察性研究设计，收集2019年3月至2019年11月三个中心的AE-IPF患者76例，其中痰热壅肺证26例、痰浊阻肺证50例，并纳入健康志愿者10例作为对照。采用ELISA测定患者血清CCL18、HMGB1、KL-6、MMP-7、SP-A和SP-D水平，分析与中医证候的相关性。结果 AE-IPF患者血清CCL18、HMGB1、KL-6、MMP-7、SP-A和SP-D水平均显著高于健康对照组。血清CCL18、HMGB1、KL-6、MMP-7和SP-D水平在痰热壅肺证和痰浊阻肺证患者间无显著性差异（P＞0.05），而血清SP-A水平存在显著性差异（P＜0.05）。结论 血清SP-A与AE-IPF证候存在一定的相关性，血清SP-A的浓度升高，与痰热壅肺证关系越密切，反之，血清SP-A浓度降低，则与痰浊阻肺证关系越密切。AE-IPF痰热壅肺证患者的预后可能较痰浊阻肺证患者更差。     

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。     

论当前疾病预防控制体系面临的主要问题

对当前的疾病预防控制体系和机构面临的体系不健全、政府投入不充分、事业发展不平衡、人才缺失和能力不足、缺乏系统的理论指导、体系的碎片化严重、与社会经济发展的战略衔接不力、机构内部内生动力和活力不足以及体系治理能力不足等问题做了讨论分析,以期进一步分析在健康中国战略和事业单位机构改革等宏观环境变化所带来的机遇以及疾控体系的发展策略和具体措施,促进疾病预防控制事业在改革中谋发展。     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.