BCAN基因在肾透明细胞癌中的表达及临床意义

目的以基因表达数据集资料为研究对象,分析BCAN基因在肾透明细胞癌中的表达情况以及对患者预后的影响。方法在Oncomine数据库中挖掘BCAN在肾透明细胞癌(ccRCC)中的表达情况。从TCGA数据库中获取ccRCC患者临床资料和目的基因的表达信息并进行统计分析。利用GEO数据库中GSE73731数据集的ccRCC样本进行基因富集分析。利用String数据库分析与BCAN相关的蛋白。结果BCAN低表达组的ccRCC患者在病理分期及T分期方面低于高表达组(P<0.001;P=0.001);N分期及M分期差异无统计学意义(P>0.05)。BCAN低表达组患者的总生存期优于高表达组(P=0.033)。BCAN基因高表达组的样本主要富集在KRAS信号通路。结论BCAN可以通过多种途径来促进肿瘤细胞的侵袭能力,有望成为ccRCC不良预后的重要生物标志物之一。     

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).     

Optimal tracking control for non-zero-sum games of linear discrete-time systems via off-policy reinforcement learning

In this article, a model-free off-policy reinforcement learning algorithm is applied to address the optimal tracking problem based on multiplayer non-zero-sum games for discrete-time linear systems. In contrast to the traditional method and the policy iteration method for solving the optimal tracking problems, the proposed algorithm operates with the system data rather than the knowledge of the system dynamics. For performing the proposed algorithm, an auxiliary augmented system is constructed via assembling the original system and the reference trajectory while a discount factor is introduced into the performance indexes. It is analyzed that the solutions of the proposed algorithm converge to the Nash equilibrium and the result is not influenced by the probing noise. Two simulations are presented to verify the feasibility and effectiveness of the proposed algorithm.     

A Tool to Assess Patient and Surrogate Knowledge About the POLST (Physician Orders for Life-Sustaining Treatment) Program

ContextIt is especially important that patients are well informed when making high-stakes, preference-sensitive decisions like those on the Physician Orders for Life-Sustaining Treatment (POLST) form. However, there is currently no way to easily evaluate whether patients understand key concepts when making these important decisions.ObjectivesTo develop a POLST knowledge survey.MethodsExpert (n = 62) ratings of key POLST facts were used to select items for a POLST knowledge survey. The survey was administered to nursing facility residents (n = 97) and surrogate decision-makers (n = 112). A subset (n = 135) were re-administered the survey after a standardized advance care planning discussion to assess the scale's responsiveness to change.ResultsThe 19-item survey demonstrated adequate reliability (α = 0.72.). Residents' scores (x = 11.4, standard deviation 3.3) were significantly lower than surrogate scores (x = 14.7, standard deviation 2.5) (P < 0.001). Scores for both groups increased significantly after administration of a standardized advance care planning discussion (P < 0.001). Although being a surrogate, age, race, education, cognitive functioning, and health literacy were significantly associated with higher POLST Knowledge Survey scores in univariate analyses, only being a surrogate (P < 0.001) and being white (P = 0.028) remained significantly associated with higher scores in multivariate analyses.ConclusionThe 19-item POLST Knowledge Survey demonstrated adequate reliability and responsiveness to change. Findings suggest the survey could be used to identify knowledge deficits and provide targeted education to ensure adequate understanding of key clinical decisions when completing POLST.