前列腺癌早期诊断的研究进展北大核心

前列腺癌(prostate cancer, PCa)是中老年男性常见恶性肿瘤之一,目前尚缺乏有效的晚期癌症治疗方法,因此早期诊断对于降低PCa死亡率至关重要。近年来,较多研究开发出多种新型诊断方法以改善对PCa诊断的准确性,同时避免过度诊疗,但其有效性及实用性尚需进一步验证。本文对目前新型生物标志物、联合成像技术及风险预测模型等的早期诊断技术进行总结,以期为临床研究提供指导作用。     

IL-37b作用于树突状细胞CD39/ATP轴抑制类风湿性关节炎大鼠炎症反应的作用及机制

目的探讨白细胞介素37b重组蛋白(rmIL-37b)通过调节CD39/ATP轴抑制树突状细胞(DC)诱导类风湿性关节炎(RA)大鼠炎症反应的机制。方法将SD大鼠随机分为空白对照组(CTL)、CIA模型组、rmIL-37b 5μg/kg组、rmIL-37b 10μg/kg组,每组各10只。除了空白对照组外,其余大鼠采用含有卡介苗的完全弗氏佐剂和牛Ⅱ型胶原混合乳液免疫刺激,建立CIA模型。确定建模成功当天(D0),rmIL-37b组分别尾静脉注射5μg/kg、10μg/kg rmIL-37b;CTL组和CIA模型组注射相同体积的(1 ml/kg)生理盐水,连续给药15 d。免疫组化法检测滑膜组织Nod样受体蛋白3(NRPL3)炎症小体的表达,流式细胞术检测DC表型,另外试剂盒检测血清三磷酸腺苷(ATP)和免疫学指标。结果与CIA模型组相比,rmIL-37b 10μg/kg组大鼠足容积、AI值、NLRP3炎症小体表达量、血清ATP、IL-1β、IL-18、肿瘤坏死因子α(TNF-α)、抗Ⅱ型胶原抗体亚型(anti-ColⅡ-IgG、anti-ColⅡ-IgG2a)水平均降低,同时DC表面CD...     

外柱细胞软化对Corti器感音影响的生物力学研究

Corti器的感音过程容易受到内部结构属性变化的影响。外柱细胞血管舒张刺激磷蛋白缺失会减缓肌动蛋白丝的形成,从而产生听力延迟。本研究运用COMSOL建立三维有限元模型研究肌动蛋白缺失导致外柱细胞软化时,Corti器感音过程中基底膜和外毛细胞与Deiters细胞结合点的力学行为变化。结果表明,外柱细胞软化会削弱外毛细胞主动力对基底膜位移增益的放大作用,但削弱作用并不会立即产生,Corti器存在维持正常功能的"缓冲"阶段。在100 dB和120 dB之间可能存在一个声压级临界值,在该临界值两侧外柱细胞软化对基底膜应力变化的影响是截然相反的。另外外柱细胞软化对不同外毛细胞与Deiters细胞结合点力学行为的影响也不同,位移增益优先级会因此产生改变。     

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。     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Delineating the geographic context of physical activities: A systematic search and scoping review of the methodological approaches used in social ecological research over two decades

BackgroundThe social ecological approach suggests that the spatial context among other factors influence physical activity behavior. Ample research documents physical environmental effects on physical activity. Yet, to date inconsistent associations remain, which might be explained by conceptual and methodological challenges in measuring the spatial dimensions of health behavior. We review methods applied to measure the spatial contexts in the social ecological physical activity literature.MethodsOnline databases and selected reviews were used to identify papers published between 1990 and 2020. A total of 2167 records were retrieved, from which 412 studies that used physical activity as a primary outcome variable, included measures of the physical environment and applied the main principles of the social ecological approach, were included.ResultsSubjective approaches were the dominant method to capture the spatial context of physical activities. These approaches were applied in 67% (n=279) of the studies. From the objective approaches an administrative unit was most prevalent and was applied in 29% (n=118) of the studies. The most comprehensive objective spatial methods that capture the true environmental exposure, were used only in 2% (n=10) of the studies.ConclusionsCurrent social ecological physical activity research applies simple conceptualizations and methods of the spatial context. While conceptual and methodological concerns have been repeatedly expressed, no substantive progress has been made in the use of spatial approaches. To further our understanding on place effects on health, future studies should carefully consider the choice of spatial approaches, and their effect on study results.     

基于LDA模型的中医药人工智能领域主题演化分析＊

目的 梳理总结中医药人工智能领域近40年的研究情况，分析该领域研究主题演化过程，发现热点主题和研究前沿。方法 本研究检索了CNKI和WOS中中医药人工智能领域的文献，根据生命周期理论划分不同时间片，将文献摘要作为研究对象，采用LDA主题模型挖掘文本主题，分析主题的演化过程，识别热点主题。结果 纳入中英文文献2750篇，根据生命周期理论划分中医药人工智能领域发展阶段，分别建立全局和各阶段的LDA模型，挖掘出全局热点主题有中医专家系统、中医辅助诊断系统、中医药数据挖掘等，发现主题演化路径并进行可视化展示。结论 中医药与人工智能主要的结合点在中医智能系统、中医药知识组织和中医智能诊疗机器人这3方面，这3个方向的研究均离不开神经网络技术的支持，同时也结合了关联规则发现、复杂网络研究等方法。     

蒙药安神补心六味丸预防给药对心肌缺血大鼠的保护作用及氧化应激水平的影响＊

目的 研究蒙药安神补心六味丸对大鼠心肌缺血损伤的保护作用和氧化应激机制。方法 将60只大鼠随机分为空白组、模型组、阳性对照组（丹参滴丸）及蒙药安神补心六味丸低、中、高剂量组，使用腹腔注射异丙肾上腺素方法制备大鼠急性心肌缺血模型，记录并观察大鼠心电图活动变化，然后进行腹主动脉取血，分离血清，测定乳酸脱氢酶（Lactic dehydrogenase，LDH）、肌酸激酶（Creatine kinase，CK）、磷酸肌酸激酶（Creatine kinase isoenzyme，CK-MB）、谷草转氨酶（Aspartate aminotransferase，AST）、超氧化物歧化酶（Superoxide dismutase，SOD）、丙二醛（Malondialdehyde，MDA）和谷胱甘肽过氧化物酶（Glutathione peroxidase，GSH-PX）含量变化。取心肌组织固定，对大鼠心肌组织进行HE染色，通过对心肌酶学和和心肌组织形态学两个方面来考察蒙药安神补心六味丸对大鼠心肌缺血模型的保护作用。结果 与空白组比较，模型组大鼠血清中LDH活性极显著升高（P<0.01），CK、CK-MB、AST、MDA活性均显著升高（P<0.05），SOD活性显著降低（P<0.05），GSH-PX活性高度显著降低（P<0.001），且差异均具有统计学意义；与模型组比较，蒙药安神补心六味丸组高剂量组大鼠血清中LDH、CK、CK-MB、MDA活性显著降低（P<0.05），SOD活性显著升高（P<0.05），GSH-PX活性极显著升高（P<0.01），且差异均具有统计学意义。从HE染色分析，蒙药安神补心六味丸能够改善因缺血而造成的心肌组织损伤。结论 蒙药安神补心六味丸能有效改善心肌组织病理状态，减轻大鼠心肌缺血损伤，以达到保护心肌作用，机制可能与氧化应激机制相关。     

The use of ultrasound,fibronectin and other parameters to predict the success of labour induction

Induction of labour is a common obstetrical procedure and is undertaken when the benefits of delivery are considered to outweigh the risks of continuation of pregnancy. However, more than one-fifth of induction cases fail to result in vaginal births and lead to unplanned caesarean deliveries, which compromise the birth experience and have negative clinical and resource implications. The need for accurate prediction of successful labour induction is increasingly recognised and many researchers have attempted to evaluate the potential predictability of different factors including maternal characteristics, Bishop score, various biochemical markers and ultrasound markers and derive predictive models to address this issue.