国内外安宁疗护准入标准的研究进展

安宁疗护可提高患者在生命终末阶段的生活质量，减轻患者和家属的身心痛苦。科学合理的安宁疗护准入标准可帮助医护人员识别出需要安宁疗护服务的患者，使其及时获得安宁疗护服务，因此明确安宁疗护的准入标准是推进安宁疗护发展的基础。本文就国内外安宁疗护准入标准的制定方法、具体内容及优缺点进行综述，以期为我国安宁疗护准入标准的构建提供参考。     

良性前列腺增生与前列腺慢性炎症的相关性研究进展

良性前列腺增生（BPH）是老年男性常见的泌尿系统疾病，其发病与前列腺慢性炎症之间存在显著相关。感染因子、尿液返流、代谢综合征、衰老过程和自身免疫应答在内的几种刺激，通过相应分子途径引起前列腺免疫细胞的组织定位和组成成分发生广泛改变，从而导致免疫系统失调，之后引发的组织损伤和缓慢愈合，导致了BPH发生和进展。本文通过总结良性前列腺增生与前列腺慢性炎症的相关性的临床研究结果，前列腺免疫细胞在病理生理机制层面与前两者之间的内在联系，以及抗炎药物对BPH-LUTS的干预作用，以其为BPH-LUTS的药物研发提供参考。     

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.     

肿瘤免疫检查点抑制剂相关的肝毒性

肿瘤免疫检查点抑制剂治疗为肿瘤患者带来生存获益的同时,也面临了许多挑战,例如免疫介导的肝毒性的发生。深入了解免疫检查点抑制剂治疗肿瘤过程中导致肝损伤的发生情况、可能机制、危险因素等,有助于更好地临床管理。     

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。     

Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m^?2,1.04 kg m^?2, and 1.13 kg m^?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R² (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m^?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.