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。     

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.     

Prolyl and lysyl hydroxylases in collagen synthesis

Collagens are the most abundant proteins in the extracellular matrix. They provide a framework to build organs and tissues and give structural support to make them resistant to mechanical load and forces. Several intra‐ and extracellular modifications are needed to make functional collagen molecules, intracellular post‐translational modifications of proline and lysine residues having key roles in this. In this article, we provide a review on the enzymes responsible for the proline and lysine modifications, that is collagen prolyl 4‐hydroxylases, 3‐hydroxylases and lysyl hydroxylases, and discuss their biological functions and involvement in diseases.     

我国家庭医生签约服务政策执行的制约因素与优化路径：基于史密斯政策执行过程模型

深化家庭医生签约服务是深化医药卫生体制改革、强化基层医疗卫生服务、实现"健康中国"战略目标的重要选择，也是当前更好维护人民群众健康的重要途径。为有效推进签约服务工作，国家陆续推出各项政策，全国各地也在积极进行实践探索，成效明显。但是，签约服务仍面临诸多问题，其中"执行难"是签约服务深度推进的一大困境。通过史密斯政策执行过程模型，结合签约服务政策执行过程，发现签约服务仍存在法治性不足、政策执行人员水平不高、激励不足、政策环境影响等诸多制约因素。因此，需要从法律和制度方面进行顶层设计、提升执行人员素质和职业认同、建立医患互信、优化政策执行环境等角度进行政策创新，探索家庭医生签约服务可持续发展的路径。     

Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy

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Predicting Survival for Chimeric Antigen Receptor T-Cell Therapy: A Validation of Survival Models Using Follow-Up Data From ZUMA-1

ObjectivesSurvival extrapolation for chimeric antigen receptor T-cell therapies is challenging, owing to their unique mechanistic properties that translate to complex hazard functions. Axicabtagene ciloleucel is indicated for the treatment of relapse or refractory diffuse large B-cell lymphoma after 2 or more lines of therapy based on the ZUMA-1 trial. Four data snapshots are available, with minimum follow-up of 12, 24, 36, and 48 months. This analysis explores how survival extrapolations for axicabtagene ciloleucel using ZUMA-1 data can be validated and compared.MethodsThree different parametric modeling approaches were applied: standard parametric, spline-based, and cure-based models. Models were compared using a range of metrics, across the 4 data snapshot, including visual fit, plausibility of long-term estimates, statistical goodness of fit, inspection of hazard plots, point-estimate accuracy, and conditional survival estimates.ResultsStandard and spline-based parametric extrapolations were generally incapable of fitting the ZUMA-1 data well. Cure-based models provided the best fit based on the earliest data snapshot, with extrapolations remaining consistent as data matured. At 48 months, the maximum survival overestimate was 8.3% (Gompertz mixture-cure model) versus the maximum underestimate of 33.5% (Weibull standard parametric model).ConclusionsWhere a plateau in the survival curve is clinically plausible, cure-based models may be helpful in making accurate predictions based on immature data. The ability to reliably extrapolate from maturing data may reduce delays in patient access to potentially lifesaving treatments. Additional research is required to understand how models compare in broader contexts, including different treatments and therapeutic areas.     

甲状腺乳头状癌前上纵隔淋巴结转移临床病理特征初步分析

目的 探讨肿瘤位置、最大直径及甲状腺外浸等临床病理特征与甲状腺癌前上纵隔淋巴结转移的关系。 方法 研究分析初次手术治疗的60例甲状腺乳头状癌患者临床及病理资料,运用检验临床病理特征与前上纵隔淋巴结阳性率的相关性。 结果 肿块位置、最大直径、数量、腺体外侵、受累腺叶数及Ⅵ区淋巴结转移等特征,以及患者年龄等相关因素中,只有VI区淋巴结对前上纵隔淋巴结状态有影响;60例患者前上纵隔淋巴结转移率为10/60(16.67%)。相关因素的前上纵隔淋巴结转移率对比:≥55岁vs <55岁(20% vs 16.36%, P<0.05);肿块位于下极 vs 上极 vs 中极(P>0.05);最大直径≥1.5 cm vs 最大直径<1.5 cm(18.18% vs 15.79, P>0.05);单灶 vs 多灶(21.88% vs 10.71%, P>0.05);单叶 vs 多叶(17.5% vs 15%, P>0.05);男性vs女性(20% vs 15.55%, P>0.05); Ⅵ区淋巴结阳性vs 阴性(24.43% vs 3.57%, P<0.05); 结论 总体来说,甲状腺乳头状癌前上纵隔淋巴结转移率较低。本研究发现VI区淋巴结状态可能与前上纵隔淋巴结转移相关,未来仍需大样本前瞻性的研究验证。