Special issue “The advance of solid tumor research in China”: Multi-omics analysis based on 1311 clear cell renal cell carcinoma samples identifies a glycolysis signature associated with prognosis and treatment response

In clear cell renal cell carcinoma (ccRCC), glycolysis is enhanced mainly because of the increased expression of key enzymes in glycolysis. Hence, the discovery of new molecular biomarkers for glycolysis may help guide and establish a precise system of diagnosis and treatment for ccRCC. Expression profiles of 1079 tumor samples of ccRCC patients (including 311 patients treated with everolimus or nivolumab) were downloaded from public databases. Proteomic profiles of 232 ccRCC samples were obtained from Fudan University Shanghai Cancer Center (FUSCC). Biological changes, tumor microenvironment and prognostic differences were explored between samples with various glycolysis characteristics. There were significant differences in CD8⁺ effector T cells, epithelial-to-mesenchymal transition and pan-fibroblast TGFb between the Low and High glyScore groups. The tumor mutation burden of the Low glyScore group was lower than that of the High glyScore group. And higher glyScore was significantly associated with worse overall survival (OS) in 768 ccRCC patients (P < .0001). External validation in FUSCC cohort also indicated that glyScore was of strong ability for predicting OS (P < .05). GlyScore may serve as a biomarker for predicting everolimus response in ccRCC patients due to its significant associations with progression-free survival (PFS). And glyScore may also predict overall survival in patients treated with nivolumab. We calculated the glyScore in ccRCC and the defined glyScore was of strong ability for predicting OS. In addition, glyScore may also serve as a biomarker for predicting PFS in patients treated with everolimus and could predict OS in patients treated with nivolumab.     

慢性疼痛中枢调控网络的研究现状与思考＊

慢性疼痛是一种复杂的身心疾病，包括躯体痛觉异常、认知障碍、负性情绪等多个方面的改变，同时伴随着神经系统的功能以及结构的改变。本文将对慢性疼痛与下行疼痛调节通路、疼痛情感-认知调控网络以及中脑边缘奖赏网络的相关性，以及针刺镇痛的中枢机制相关研究文献进行综述，旨在探讨下行疼痛调节通路、疼痛情感-认知调控网络以及中脑边缘奖赏网络在慢痛发生机制中的作用，为临床治疗慢性疼痛类疾病提供更优势的治疗方案。     

Venetoclax alone or in combination with other regimens treatment achieve deep and sustained remission of relapsed/refractory chronic lymphocytic leukemia: a meta-analysis

Clinical and Experimental Medicine - Recently, the use of novel targeted drugs significantly improved the overall response rate (ORR) and survival of patients with relapsed/refractory chronic...     

Movement control as an effective measure against Covid-19 spread in Malaysia: an overview

Journal of Public Health - The first Covid-19 cases were reported in Malaysia on 25 January 2019 followed by a quiescent period before an upward swing of the cases at the end of February 2020,...     

基于超声影像组学的乳腺癌预测模型的诊断性能研究

目的评估并比较基于不同机器学习算法建立的乳腺癌超声影像组学预测模型的诊断性能。 方法回顾性收集2017年1月至2019年4月就诊皖南医学院第一附属医院、有明确病理结果的乳腺肿块病例828例，以2018年8月31日为节点将其分为训练集（526例）和验证集（302例），提取肿块的超声影像组学特征并进行特征筛选，运用k最近邻（kNN）、逻辑回归（LR）、朴素贝叶斯（NB）、随机森林（RF）和支持向量机（SVM）5种机器学习算法分别建立预测模型，使用重复交叉验证方法做内部验证，计算比较各模型的敏感度、特异度、阳性预测值（PPV）和阴性预测值（NPV），并实施外部验证，绘制ROC曲线并比较ROC曲线下面积（AUC）以评价模型的鉴别诊断性能，绘制校准曲线评价模型校准度。 结果从提取的109个影像组学特征中筛选出19个特征建立了5种机器学习算法模型。在内部验证中，5种模型的敏感度、特异度、PPV、NPV比较，总体差异均有统计学意义（P均＜0.001）。LR模型的特异度、PPV、NPV中位数分别为0.769、0.816、0.778，3项指标均高于其他4种模型；敏感度中位数为0.824，高于kNN、RF和SVM模型。此外，SVM模型的特异度、PPV、NPV中位数分别为0.706、0.774、0.759，虽均低于LR模型，但均高于其他3种模型。在外部验证中，LR、SVM、RF、kNN和NB的AUC依次为0.890、0.832、0.821、0.746和0.703，其中LR与SVM的AUC差异有统计学意义（P=0.012）；此外，各模型在校准性能上表现并不一致，LR和SVM模型的校准曲线显示乳腺癌实际概率与预测概率之间的一致性较好。 结论以超声影像组学特征为基础，运用不同机器学习算法建立的乳腺癌超声预测模型，均表现出较高的诊断性能，其中LR模型表现最为突出；选择合适的机器学习算法有助于进一步提高预测模型的诊断性能，提供更加准确的量化预测结果。     

胃癌患者心理痛苦的研究进展

综述心理痛苦的概念与内涵，胃癌患者的心理痛苦水平、评估工具、影响因素及干预措施。提出需构建胃癌患者心理痛苦模型，实施针对性的护理措施以减轻胃癌患者心理痛苦水平，提高生活质量。