Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.     

肝细胞癌TACE术后病灶存活或复发18F-FDGPET/CT和增强CT诊断价值Meta分析

目的采用Meta分析方法评价¹⁸F-脱氧葡萄糖正电子发射计算机体层摄影(¹⁸F-FDG PET/CT)和增强CT(CECT)诊断经导管肝动脉化疗栓塞术(TACE)术后存活或复发病灶的临床价值。方法根据PRISMA报告规范开展Meta分析。检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、万方和维普数据库中¹⁸F-FDG PET/CT和CECT诊断TACE术后存活或复发病灶的临床研究,时间至2019-04。由2位研究人员独立筛选文献、提取资料,根据诊断准确性研究质量评价工具-2(QUADAS-2)评价纳入研究的偏倚风险后,采用Stata 12.0软件进行Meta分析,计算其汇总敏感度(Sen)和特异度(Spe),绘制受试者工作特征曲线(SROC)并计算曲线下面积(AUC)。结果共纳入10篇¹⁸F-FDG PET/CT及13篇CECT诊断TACE术后存活或复发病灶的原始研究,分别包括322例患者的467个病灶和748例患者的943个病灶。Meta分析显示,¹⁸F-FDG PET/CT诊断TACE术后存活或复发病灶的Sen=0.92(95%CI为0.87~0.94)、Spe=0.95(95%CI为0.82~0.99)、AUC=0.97(95%CI为0.93~0.99);CECT诊断TACE术后存活或复发病灶的Sen=0.72(95%CI为0.66~0.78)、Spe=0.99(95%CI为0.93~1.00)、AUC=0.87(95%CI为0.83~0.89)。此外,CECT诊断TACE术后存活或复发Sen(Z=2.34,P=0.02)和AUC(Z=2.21,P=0.03)值低于¹⁸F-FDG PET/CT,差异有统计学意义。结论相比于CECT,¹⁸F-FDG PET/CT对TACE术后存活或复发病灶具有较高诊断效能,可视为TACE术后存活或复发病灶有效的影像学诊断方法。     

Helicobacter pylori induces epithelial-mesenchymal transition in gastric carcinogenesis via the AKT/GSK3β signaling pathway

Helicobacter pylori (H. pylori) is a main risk factor for gastric cancer (GC). Epithelial-mesenchymal transition (EMT) is involved in the development and progression of H. pylori-associated GC. However, the exact molecular mechanism of this process remains unclear. The AKT/GSK3β signaling pathway has been demonstrated to promote EMT in several types of cancer. The present study investigated whether H. pylori infection induced EMT, and promoted the development and metastasis of cancer in the normal gastric mucosa, and whether this process was dependent on AKT activation. The expression levels of the EMT-associated proteins, including E-cadherin and N-cadherin, were determined in 165 gastric mucosal samples of different disease stages by immunohistochemical analysis. The expression levels of E-cadherin, N-cadherin, AKT, phosphorylated (p-)AKT (Ser473), GSK3β and p-GSK3β (Ser9) were further determined in H. pylori-infected Mongolian gerbil gastric tissues and cells co-cultured with H. pylori by immunohistochemical analysis and western blotting. The results indicated that the expression levels of the epithelial marker E-cadherin were decreased, whereas the expression levels of the mesenchymal marker N-cadherin were increased during gastric carcinogenesis. Their expression levels were associated with H. pylori infection. Furthermore, H. pylori infection resulted in downregulation of E-cadherin expression and upregulation of N-cadherin expression in Mongolian gerbils and GES-1 cells. In addition, an investigation of the associated mechanism of action revealed that p-AKT (Ser473) and p-GSK3β (Ser9) were activated in GES-1 cells following co-culture with H. pylori. Furthermore, following pretreatment of the cells with the AKT inhibitor VIII, the expression levels of E-cadherin, N-cadherin, p-AKT and p-GSK3β did not show significant differences between GES-1 cells that were co-cultured with or without H. pylori. The levels of p-AKT and p-GSK3β were increased in H. pylori-infected Mongolian gerbils. In conclusion, the present study demonstrated that H. pylori infection activated AKT and resulted in the phosphorylation and inactivation of GSK3β, which in turn promoted early stage EMT. These effects were AKT-dependent. This mechanism may serve as a prerequisite for GC development.