“三全育人”视角下思政教育机制实践与探索——“杏林成长导师”计划的构建

“三全育人”是高校思政教育工作的关键一环，也是中医药高校推动思政教育的重要内容。以“三全育人”为视角对北京中医药大学思想政治教育举措“杏林成长导师”计划路径、内容深入分析，运用统计分析和文献研究方法，剖析该计划对中医学专业大学生的学业、思想和实践等多个层面的现实成效，从而为“三全育人”理念在中医药院校制度建构中的应用提供新的视角与方法。     

SLC及其受体CCR7与Ⅰ期非小细胞肺癌淋巴结微转移的相关性

目的 探讨溶质载体蛋白（SLC）及其受体趋化因子受体7（CCR7）与I期非小细胞肺癌（NSCLC）淋巴结微转移的相关性。方法 选取2019年1月~2020年3月于我院就诊的I期NSCLC患者127例为研究对象，按照淋巴结微转移情况分为对照组92例和转移组35例，所有患者入院后均通过根治术切除病灶，通过免疫组化方式检测病灶中SLC7A11及CCR7含量，并收集患者临床资料、实验室检查资料及影像学检查资料。通过Logistic回归分析评价SLC7A11及CCR7与淋巴结微转移之间的关系。最后通过建立ROC曲线分析两者及其联合检测对NSCLC患者微淋巴结转移的预测价值。结果 两组患者SLC7A11及CCR7表达水平存在显著差异（P＜0.05）。转移组患者病灶直径、支气管受累及TLG显著高于对照组（P＜0.05）。病灶直径（OR=49.254,95%CI=11.062~507.604）是影响NSCLC淋巴结微转移的独立危险因素（P＜0.05）。SLC7A11（OR=8.622）及CCR7（OR=8.709）表达水平是影响NSCLC淋巴结微转移的独立因素（P＜0.05）。SLC7A11、CCR7及联合诊断对NSCLC淋巴结微转移具有较好的检测价值（均P＜0.05）。联合检测特异度显著高于 SLC7A11及CCR7单独检测（2=7.292，15.125；均P＜0.01）。结论 SLC家族的中SLC7A11及其受体CCR7与NSCLC患者微淋巴结转移显著相关。     

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...     

安宁疗护对社区临终患者生活质量影响的Meta分析

目的通过Meta分析评价安宁疗护对社区临终患者生活质量的影响。方法计算机检索PubMed、CINAHL、ScienceDirect、MEDLINE、Cochrane Library、SAGE数据库、中国知网、维普中文科技期刊数据库、万方数据库和中国生物医学文献数据库中安宁疗护对社区临终患者的随机对照试验,由2名研究人员独立筛选文献并提取资料,对符合质量标准的随机对照试验进行Meta分析。结果共纳入7篇文献,包括1095名社区临终患者。Meta分析结果显示,安宁疗护可以改善社区临终患者的总体生活质量(SMD=0.48,95%CI0.07~0.88,P=0.02)和情绪功能(SMD=1.27,95%CI0.59~1.95,P<0.001),在改善生活质量的躯体功能、角色功能、认知功能和社会功能水平上差异无统计学意义(P>0.05)。结论安宁疗护能改善社区临终患者的总体生活质量和情绪功能,但对生活质量其他功能的改善情况还需要设计更加规范、多中心、大样本的随机对照试验进一步证实。     

中药生产过程质量控制关键技术研究进展

中医药发展已上升到国家战略层面,在医药行业贯彻实施"中国制造2025"战略的新形势下,中药生产过程质量控制是中药工业需要加快突破的关键领域之一。对中药生产过程质量控制领域在工艺设计、分析检测、过程建模、制造装备等方面的关键共性问题进行解析,综述了中药生产过程质量控制体系中工艺过程理解、生产过程实时分析方法开发、过程控制策略建立3个方面的研究进展;并结合企业研究实践,介绍了质量源于设计(quality by design,Qb D)、过程分析技术(process analytical technology,PAT)、实验设计(design of experiment,DOE)、多变量统计分析等关键技术在上述3个研究方向中的应用进展,分析了实际工业应用的难点问题并对其应用前景进行展望,旨在为中药企业应用和提升生产过程质量控制技术提供参考。     

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.     

Mixed Reality Combined with Three‐Dimensional Printing Technology in Total Hip Arthroplasty: An Updated Review with a Preliminary Case Presentation

Three‐dimensional (3D) printing technology, virtual reality, and augmented reality technology have been used to help surgeons to complete complex total hip arthroplasty, while their respective shortcomings limit their further application. With the development of technology, mixed reality (MR) technology has been applied to improve the success rate of complicated hip arthroplasty because of its unique advantages. We presented a case of a 59‐year‐old man with an intertrochanteric fracture in the left femur, who had received a prior left hip fusion. After admission to our hospital, a left total hip arthroplasty was performed on the patient using a combination of MR technology and 3D printing technology. Before surgery, 3D reconstruction of a certain bony landmark exposed in the surgical area was first performed. Then a veneer part was designed according to the bony landmark and connected to a reference registration landmark outside the body through a connecting rod. After that, the series of parts were made into a holistic reference registration instrument using 3D printing technology, and the patient's data for bone and surrounding tissue, along with digital 3D information of the reference registration instrument, were imported into the head‐mounted display (HMD). During the operation, the disinfected reference registration instrument was installed on the selected bony landmark, and then the automatic real‐time registration was realized by HMD through recognizing the registration landmark on the reference registration instrument, whereby the patient's virtual bone and other anatomical structures were quickly and accurately superimposed on the real body of the patient. To the best of our knowledge, this is the first report to use MR combined with 3D printing technology in total hip arthroplasty.     

Exact confidence intervals for the average causal effect on a binary outcome

Based on the physical randomization of completely randomized experiments, in a recent article in Statistics in Medicine, Rigdon and Hudgens propose two approaches to obtaining exact confidence intervals for the average causal effect on a binary outcome. They construct the first confidence interval by combining, with the Bonferroni adjustment, the prediction sets for treatment effects among treatment and control groups, and the second one by inverting a series of randomization tests. With sample size n, their second approach requires performing O(n⁴)randomization tests. We demonstrate that the physical randomization also justifies other ways to constructing exact confidence intervals that are more computationally efficient. By exploiting recent advances in hypergeometric confidence intervals and the stochastic order information of randomization tests, we propose approaches that either do not need to invoke Monte Carlo or require performing at most O(n²)randomization tests. We provide technical details and R code in the Supporting Information . Copyright © 2016 John Wiley & Sons, Ltd.