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.     

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.     

内脏利什曼病合并HIV感染患者诊断和治疗研究进展

内脏利什曼病是全球被忽视的传染病之一,危害严重。而利什曼原虫-人类免疫缺陷病毒(human immunodeficiency virus,HIV)合并感染对流行地区造成的威胁更甚。利什曼原虫与HIV存在相互作用,合并感染者在临床表现、诊断及治疗方面具有一定特殊性,其病死率及复发率均高于HIV阴性的内脏利什曼病患者。本文对利什曼原虫-HIV合并感染患者的临床表现、诊断和治疗进展进行综述。     

中日友好医院分型股骨头坏死腓骨植入治疗的三维有限元分析

文题释义：股骨头坏死中日友好医院分型的有限元分析：根据李子荣等提出的中日友好医院分型，建立股骨头坏死三维模型，分为 M型(内侧型)、C型(中央型)和 L型(外侧型)，其中 L型包括L1型(次外侧型)、L2型(极外侧型)和 L3型(全头型)。通过对建立的模型进行有限元分析，为该分型的保髋治疗提供了一定力学依据，显示外侧柱的存留是精准预防塌陷的重要因素，为进一步实现个体化治疗提供力学基础。 腓骨支撑坏死股骨头保髋手术：是对于早中期股骨头坏死需要保留股骨头患者进行的一种手术方式。首先需对股骨头进行髓芯减压，清除一定坏死骨，空腔填塞松质骨(髂骨为主)，打压结实后植入腓骨(异体或自体)支撑，给坏死区的提供力学支撑及生物学修复，预防股骨头进一步坏死及塌陷。 背景：研究报道股骨头坏死的保髋疗效与外侧柱存留密切相关，中日友好医院分型是根据三柱结构确立的，对股骨头塌陷的预测准确性高。 目的：建立股骨头坏死中日友好医院分型各分型仿真的三维有限元模型，通过有限元分析各分型腓骨植入的力学变化，探讨外侧柱存留对保髋疗效的意义，为该分型的塌陷精准预测提供基础。 方法：建立正常股骨头、中日友好医院分型(M型、C型、L1型、L2型、L3型)股骨头坏死及其腓骨植入3组11种三维有限元模型，运用ANSYS软件进行有限元分析计算，观察各组模型的最大应力值、最大位移值及股骨头内部载荷传递模式。 结果与结论：①坏死组位移最大，应变最大，且因坏死分型不同而位移不同，位移变化如下：M型相似文献   

In vivo epigenetic effects induced by engineered nanomaterials: A case study of copper oxide and laser printer-emitted engineered nanoparticles

Evidence continues to grow on potential environmental health hazards associated with engineered nanomaterials (ENMs). While the geno- and cytotoxic effects of ENMs have been investigated, their potential to target the epigenome remains largely unknown. The aim of this study is two-fold: 1) determining whether or not industry relevant ENMs can affect the epigenome in vivo and 2) validating a recently developed in vitro epigenetic screening platform for inhaled ENMs. Laser printer-emitted engineered nanoparticles (PEPs) released from nano-enabled toners during consumer use and copper oxide (CuO) were chosen since these particles induced significant epigenetic changes in a recent in vitro companion study. In this study, the epigenetic alterations in lung tissue, alveolar macrophages and peripheral blood from intratracheally instilled mice were evaluated. The methylation of global DNA and transposable elements (TEs), the expression of the DNA methylation machinery and TEs, in addition to general toxicological effects in the lung were assessed. CuO exhibited higher cell-damaging potential to the lung, while PEPs showed a greater ability to target the epigenome. Alterations in the methylation status of global DNA and TEs, and expression of TEs and DNA machinery in mouse lung were observed after exposure to CuO and PEPs. Additionally, epigenetic changes were detected in the peripheral blood after PEPs exposure. Altogether, CuO and PEPs can induce epigenetic alterations in a mouse experimental model, which in turn confirms that the recently developed in vitro epigenetic platform using macrophage and epithelial cell lines can be successfully utilized in the epigenetic screening of ENMs.