早期症状改善预测焦虑患者rTMS治疗的疗效

目的 探讨重复经颅磁刺激(Repetitive transcranial magnetic stimulation,rTMS)治疗焦虑障碍患者早期症状的改善能否预测最终的临床疗效。方法 选择40例2017年7月-2019年11月本院焦虑障碍患者进行rTMS治疗,早期症状改善的界限值定义为治疗1或2周后汉密尔顿焦虑量表(Hamilton anxiety scale,HAMA)减分率15%～40%,分别计算其预测治疗4周后最终临床疗效的灵敏度、特异度、阳性预报值、阴性预报值,并通过受试者工作特征曲线(Receiver operating characteristic curve,ROC曲线)评估其预测效应。结果 治疗总有效率为62.5%; 以rTMS治疗1周后HAMA减分率15%及20%或治疗2周后HAMA减分率15%、20%、25%、30%及35%为界限值预测临床疗效有相对较高的灵敏度和阴性预报值; 以rTMS治疗1周后HAMA减分率30%、35%及40%或治疗2周后HAMA减分率35%及40%为界限值预测临床疗效有相对较高的特异度和阳性预报值; 以治疗1和2周后HAMA减分率预测治疗4周后临床疗效的ROC曲线下面积分别为0.712(P<0.05)和0.856(P<0.01)。结论 rTMS治疗焦虑障碍早期症状改善可有效预测最终临床疗效。     

Melatonin-stimulated exosomes enhance the regenerative potential of chronic kidney disease-derived mesenchymal stem/stromal cells via cellular prion proteins

Chronic kidney disease (CKD) is caused by dysfunctional kidneys, which result in complications like cardiovascular diseases. Chronic kidney disease-induced pathophysiological conditions decrease efficacy of autologous mesenchymal stem/stromal cell (MSC)-based therapy by reducing MSC functionality. To enhance therapeutic potential in patients with CKD, we isolated exosomes derived from melatonin-treated healthy MSCs (MT exosomes) and assessed the biological functions of MT exosome–treated MSCs isolated from patients with CKD (CKD-MSCs). Treatment with melatonin increased the expression of cellular prion protein (PrP^C) in exosomes isolated from MSCs through the upregulation of miR-4516. Treatment with MT exosomes protected mitochondrial function, cellular senescence, and proliferative potential of CKD-MSCs. MT exosomes significantly increased the level of angiogenesis-associated proteins in CKD-MSCs. In a murine hindlimb ischemia model with CKD, MT exosome–treated CKD-MSCs improved functional recovery and vessel repair. These findings elucidate the regenerative potential of MT exosome–treated CKD-MSCs via the miR-4516-PrP^C signaling axis. This study suggests that the treatment of CKD-MSCs with MT exosomes might be a powerful strategy for developing autologous MSC-based therapeutics for patients with CKD. Furthermore, miR-4516 and PrP^C could be key molecules for enhancing the regenerative potential of MSCs in ischemic diseases.     

前列腺癌并阴茎转移综合治疗一例报告并文献复习

目的探讨前列腺癌并阴茎转移的发病机制、临床特征及诊疗预后。 方法回顾性分析1例前列腺癌并阴茎转移患者的临床资料。 结果患者68岁，因排尿困难在我院行经尿道前列腺电切术，术后病理检查报告为前列腺腺癌。术后行外放射治疗及内分泌治疗，15个月后发生阴茎转移，予以个体化的治疗方案后前列腺癌特异性抗原下降，阴茎肿块缩小，不适症状缓解。 结论前列腺癌阴茎转移发生罕见且预后差，有多种转移机制参与；手术及放化疗虽为姑息性治疗，但个体化的治疗方案可延缓疾病进展，改善患者生活质量。     

表皮生长因子受体酪氨酸激酶抑制剂治疗晚期非小细胞肺癌的效果及对免疫功能的调节作用

目的探讨表皮生长因子受体酪氨酸激酶抑制剂(EGFR-TKI)治疗晚期非小细胞肺癌(NSCLC)患者的效果及对免疫功能的调节作用。方法选取2017年1月至2019年12月山西省肿瘤医院呼吸二科收治的100例经病理诊断为晚期(ⅢA~Ⅳ期)NSCLC的患者,男60例,女40例,年龄(58.94±12.33)岁,年龄范围为35~72岁。根据基因检测结果,依据患者基因突变情况分为EGFR-TKI组(n=48)、克唑替尼组(n=7)与联合治疗组(n=45),EGFR-TKI组采用EGFR-TKI治疗,克唑替尼组采用克唑替尼治疗,联合治疗组采用多西他赛联合顺铂治疗。比较三组患者的治疗效果、不良反应发生情况、淋巴细胞亚群[表面抗原分化簇3(CD3⁺)、表面抗原分化簇4(CD4⁺)、表面抗原分化簇8(CD8⁺)、CD4⁺/CD8⁺]和生活质量[健康调查简表(SF-36)评分、卡氏行为能力状况量表(KPS)评分]。结果 EGFR-TKI组的有效率(68.8%)、疾病控制率(87.5%)和克唑替尼组的有效率(71.4%)、疾病控制率(85.7%)高于联合治疗组[(31.1%)、(44.4%)],差异有统计学意义(P<0.05)。三组患者不良反应发生率比较,差异无统计学意义(P>0.05)。治疗后,EGFR-TKI组CD3⁺[(49.67±7.35)%]、CD4⁺[(42.00±5.17)%]、CD4⁺/CD8⁺(1.97±0.51)高于治疗前[(28.73±4.92)%]、[(24.16±3.90)%、(1.30±0.49)],克唑替尼组CD3⁺[(51.21±7.72)%]、CD4⁺[(40.79±4.37)%]、CD4⁺/CD8⁺(2.01±0.48)高于治疗前[(28.42±4.52)%]、[(23.85±3.73)%、(1.30±0.52)],联合治疗组CD3⁺[(41.05±6.37)%]、CD4⁺[(34.52±4.41)%]、CD4⁺/CD8⁺(1.67±0.45)高于治疗前[(28.62±5.36)%]、[(23.65±3.66)%、(1.28±0.53)],三组患者的CD8⁺[(16.71±1.79)%、(15.90±1.93)%、(21.28±2.40)%]均低于治疗前[(26.44±3.20)%、(26.42±3.11)%、(26.32±3.05)%];治疗后,EGFR-TKI组的SF-36评分[(84.26±6.70)分]、卡氏评分[(86.29±7.92)分]和克唑替尼组的SF-36评分[(82.85±5.72)分]、卡氏评分[(87.84±7.28)分]均高于联合治疗组[(67.19±6.33)分、(73.56±8.16)分],差异均有统计学意义(P<0.05)。结论靶向药物在晚期非小细胞肺癌患者治疗中具有较为显著的效果,不良反应发生率低,可改善患者免疫功能,值得临床推广。     

温阳补肾法对高原类风湿关节炎患者血清25羟维生素D3水平的影响

目的:观察温阳补肾法对高原类风湿关节炎患者血清25羟维生素D3水平的影响。方法:选取2015年7月至2017年8月青海省中医院收治的高原类风湿关节炎患者132例作为研究对象,随机分为对照组和观察组,每组66例。对照组应用常规西医治疗,观察组在对照组治疗基础上应用温阳补肾法治疗,2组均连续治疗3个月。比较2组治疗后临床疗效,统计2组治疗前后主要临床症状与体征、健康状况评定量表(HAQ)评分和DAS28评分,检测2组治疗前后实验室检查指标、血清25羟维生素D3以及血液流变学指标水平。结果:治疗后,观察组临床治疗总有效率显著高于对照组(P 0. 05); 2组关节肿胀指数、关节疼痛指数、关节压痛指数、晨僵时间、关节功能分级和20 m步行时间均较治疗前显著降低(P 0. 05),且观察组均显著低于对照组(P 0. 05); 2组HAQ评分、DAS28评分、类风湿因子(RF)、C反应蛋白(CRP)和红细胞沉降率(ESR)水平均较治疗前显著降低(P 0. 05),且观察组均显著低于对照组(P 0. 05); 2组血清25羟维生素D3水平均较治疗前显著升高(P 0. 05),且观察组显著高于对照组(P 0. 05); 2组红细胞电泳指数、红细胞压积、血浆黏度、全血低切黏度、全血高切黏度水平均较治疗前显著降低(P 0. 05),且观察组均显著低于对照组(P 0. 05)。结论:温阳补肾法治疗高原类风湿关节炎,疗效满意,同时能明显增加血清25羟维生素D3水平。     

Deep learning applied to two-dimensional color Doppler flow imaging ultrasound images significantly improves diagnostic performance in the classification of breast masses: a multicenter study

BackgroundThe current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images.MethodsTaking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR−), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists.ResultsThe accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87–0.91, 0.89–0.92, 0.87–0.91, and 0.86–0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%).ConclusionsThe CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists.Trial registrationChictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.     

基于Faster-RCNN的肺结节检测算法

针对目前的肺结节检测中存在的个体差异、同病异影、同影异病的问题,提出一种大样本条件下的基于Faster-RCNN的肺结节检测算法,对比研究目前的深度学习模型的适应性,给出一种通用的随着样本数量增加肺结节检测率持续提升的策略。首先搭建深度学习的软硬件环境,设置影像数据接口与Faster-RCNN的网络接口匹配;然后搭建Faster-RCNN的单类分类网络,并对网络结构的参数进行调整优化;最后用包含2 000例病人的肺结节数据集,通过不同的卷积神经网络模型 (包括ZF和VGG),计算CT图像在各自模型中的特征。对测试结果进行分析评估,分别统计其漏检率、检测准确率,并探讨不同训练数量和数据增广类型对最终检测准确率的影响。最终ZF模型的检测准确率为90.82%,准确率的波动方差为13.30%;VGG模型的检测准确率为87.02%,准确率的波动方差为37.10%。ZF模型的波动方差小,检测精确度高,综合考虑,ZF模型对肺结节的检测效果优于VGG模型的检出效果。所提出的肺结节检测技术具有良好的理论价值和工程应用价值。     

Efficient drug discovery by rational lead hybridization based on crystallographic overlay

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