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。     

【开放获取】男性肢端肥大症合并乳腺癌1例

患者男，64岁，因头颅增大、面部变长，颧骨隆起、下颌增大、双手掌肥厚、双手指粗短30余年，乳房肿物1年余就诊。患者30余年前无明显诱因出现渐进性手足增大，双手掌肥厚，嘴唇变厚，下颌增大，眉弓及颧骨突出，皮肤增厚，无乳腺增大、泌乳，未诊治……     

动物瘢痕模型的相关研究进展

皮肤损伤后的异常愈合会导致病理性瘢痕的产生。病理性瘢痕的出现不仅影响美观,严重时还会造成心理和生理功能障碍。病理性瘢痕的机制研究对于瘢痕治疗有极为重要的意义。其中,动物瘢痕模型是目前研究病理性瘢痕的重要模型手段之一。理想的动物瘢痕模型应该在组织学、细胞学等层面尽可能接近于人类的病理性瘢痕。该文分别从传统技术动物瘢痕中的啮齿类动物模型、兔耳模型和猪模型,以及新技术动物瘢痕模型这两个方面,结合近年来在瘢痕领域应用较多的研究,进行了相应系统的阐述。     

脑卒中患者恐惧疾病进展的研究现状

脑卒中患者在面对复杂的治疗期、漫长的康复期及难以预测的病情变化时容易产生对疾病或疾病进展的恐惧。恐惧疾病进展会损害脑卒中患者的身心健康和社会功能,最终影响患者的康复和预后。从恐惧疾病进展的定义、测量工具、国内外研究现状及影响因素几个方面进行综述,为临床护理人员深入了解脑卒中患者恐惧疾病进展现状、开展相关护理实践和临床研究提供依据。     

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.