基于文献的老年人群常见证候分布特征研究＊

目的 了解我国老年人中医证候分布特征，为中医药辨治老年人提供参考依据。方法 系统检索中国知识基础设施（CNKI）、中文科技期刊数据库（CCD）、万方数据资源系统数据库（CSPD），纳入研究对象为老年人的临床流行病学调查研究文献，对其调查目的、调查疾病及调查结果等进行描述统计。结果 ①最终纳入168篇文献，其中2010至2020年之间发表138篇（82.14%）；调查地区涵盖全国28个省市自治区，共纳入43948例老年人，累计覆盖340个研究中心；②主要研究结果显示，老年人中医证候阴虚阳亢证（10.05%）>血瘀证（9.5%）>痰浊（湿）证（8.91%）>阴阳两虚证（4.98%）>痰瘀互结证（4.96%）；单元证分布阴虚证（14.70%）>痰证（11.22%）>气虚证（7.15%）>肾虚证（4.72%）>血瘀证（4.18%）；涉及病变脏腑肾>肝>脾>肺>心。结论 根据统计结果，可以看出老年人证候分布虚证多于实证，虚证中又以阴虚证、气虚证最为多见，实证常见血瘀证、痰浊（湿）证等，且多见痰瘀互结证；老年人五脏皆损，其中又以肾、肝、脾功能失调最为突出。     

玳玳果黄酮降脂提取物体内组织分布规律及特征研究

目的：建立UPLC-MS/MS分析方法同时测定玳玳果黄酮降脂提取物效应组分新橙皮苷和柚皮苷在大鼠10种脏器组织中含量，分布规律及特征。方法：采用UPLC-MS/MS技术建立提取物效应组分新橙皮苷及柚皮苷在大鼠心、肝、脾、肺、肾、脑、胃、小肠、脂质、肌肉组织中的定量分析方法；大鼠给药后分别于0.33，0.67，1，4，8 h的5个时间点，分别摘取以上10种脏器组织，测定脏器组织及血液中效应组分的质量浓度，采用DAS（V 2.0）药动学软件对各样本的药物浓度-时间数据进行房室拟合，并计算不同组织效应组分的药-时曲线下面积（AUC）及平均滞留时间（MRT）。结果：所建立的UPLC-MS/MS定量分析方法具备良好的专属性、标准曲线及线性范围良好、方法准确度与精密度、定量下限均符合有关规定；玳玳果黄酮降脂提取物效应组分在血液中的分布符合一室模型，除肾脏及脑组织外，其余脏器中提取物效应组分的房室特征多为静脉注射的二室模型，柚皮苷在肾脏中的拟合结果为非静脉注射的二室模型，新橙皮苷在脑组织拟合结果为静脉注射的三室模型，给药后8 h各组织中效应组分新橙皮苷及柚皮苷AUC值大小顺序均为小肠 > 胃 > 肾 > 脂质 ≈ 脾脏 > 肺 > 肌肉 > 肝 > 心 > 脑，效应组分在各脏器中均无明显蓄积；效应组分在血液、肾脏、肝脏中的滞留时间较长，MRT均大于2 h，脂质最短，MRT不足1 h；各脏器中新橙皮苷的药-时曲线下面积约是柚皮苷的3倍，而心、肝、肾中则是3.5，2.1和3.4倍。结论：玳玳果黄酮降脂提取物效应组分在大鼠组织中分布迅速，达峰时间早于血液；效应组分在肠道内消除缓慢，给药8 h后在各脏器中的含量均显著下降且无特异的蓄积部位。研究结果揭示玳玳果黄酮降脂提取物效应组分在大鼠体内的分布特征及规律，为进一步理解玳玳果黄酮降脂提取物在体内的作用靶点及机制奠定了基础。     

Troubled-Cell Indicator Based on Mean Value Property for Hybrid WENO Schemes

In this paper, we introduce a new type of troubled-cell indicator to improve hybrid weighted essentially non-oscillatory (WENO) schemes for solving the hyperbolic conservation laws. The hybrid WENO schemes selectively adopt the high-order linear upwind scheme or the WENO scheme to avoid the local characteristic decompositions and calculations of the nonlinear weights in smooth regions. Therefore, they can reduce computational cost while maintaining non-oscillatory properties in non-smooth regions. Reliable troubled-cell indicators are essential for efficient hybrid WENO methods. Most of troubled-cell indicators require proper parameters to detect discontinuities precisely, but it is very difficult to determine the parameters automatically. We develop a new troubled-cell indicator derived from the mean value theorem that does not require any variable parameters. Additionally, we investigate the characteristics of indicator variable; one of the conserved properties or the entropy is considered as indicator variable. Detailed numerical tests for 1D and 2D Euler equations are conducted to demonstrate the performance of the proposed indicator. The results with the proposed troubled-cell indicator are in good agreement with pure WENO schemes. Also the new indicator has advantages in the computational cost compared with the other indicators.     

The impact of a total knee arthroplasty on jaw movements,upper body posture,plantar pressure distribution,and postural control

ABSTRACT

Objective: The purpose of this study was to examine the influence of a total knee arthroplasty (TKA) on linked cranial and caudal structures.

Methods: Thirty-five (14f/21m) subjects participated in this study: 15 subjects (9f, 6m) pre- and post- TKA and a control group of 20 subjects (5f, 15m). The measurements included: jaw condyle position and movement, back scan, plantar pressure distribution, and body sway.

Results: There were no significant differences in electronic position analysis of the jaw; however, the protrusion of the TKA group improved (p = 0.001). The test group had a more anteriorly inclined thoracic spine and a less pronounced lumbar lordosis. Before and after surgery, the body sway in the test group was larger.

Conclusion: The TKA affected most prominently the static mechanisms of the postural control and the spine position. The trajectories of the mandible during protrusion also changed slightly.     

我国东部地区结节性痒疹患者中医体质类型分布规律

目的探讨我国东部地区结节性痒疹患者中医体质类型的分布特点。方法采用病例对照设计方法,选取120例结节性痒疹患者作为病例组,120例健康体检者作为对照组,参照《中医体质分类与判定表》进行中医体质类型调查,分析其分布规律。结果结节性痒疹患者年龄(41.58±16.27)岁,性别男女比例约1∶1.2,体质类型分布前四位的是湿热质23例、血瘀质20例、气郁质19例、特禀质13例;健康体检者体质类型分布前四位的是平和质33例、气虚质19例、阳虚质14例、痰湿质13例;与对照组相比,病例组偏颇体质明显增多(P<0.01),2组体质构成比亦有显著性差异(P<0.01),其中湿热质、气郁质、血瘀质、特禀质较对照组转化分增加(P<0.05)。结论结节性痒疹的发病与湿热质、血瘀质、气郁质、特禀质偏颇体质类型密切相关。     

马齿苋“成分-活性-中药功效-疾病”研究进展及关联分析

马齿苋是一种药食同源品,具有清热解毒、凉血止血、止痢的功效,为常见中药,作为药物安全性高。马齿苋具有多种活性成分及药理作用,为了充分开发利用马齿苋,加快马齿苋研究的现代化进程,综述马齿苋的研究进展并在此基础上对于其"成分-活性-中药功效-疾病"进行关联分析,为马齿苋的现代化研究提供思路。     

Boosting treatment stabilization in patients of amphetamine-type stimulant use disorder

BackgroundTo investigate boosting effects on treatment stabilization in the mandatory treatment modality for patients of amphetamine-type stimulant use disorder.MethodsThis is a retrospective follow-up study over a period from January 2013 to December 2018. We analyzed 425 patients of amphetamine-type stimulant use disorder under mandating treatments. Treatment stabilization for a given patient was defined once 4 negative urinalysis had been observed. We developed a dynamic monitoring model of boosting effects informed by the available data, specifically the number of negative urine samples required to reach stabilization, the sum of urinalyses done at the time when the given number of negative urine samples had been observed and who the patient was. To represent the simulated population, a Monte Carlo method was used to generate p-values from 1000 experiments conducted on a computer.ResultsIn the observed samples, the probability of 4 negative results in urinalysis from 4 outpatient visits was 75.5%. In comparison, the probability for achieving 4th negative results in urinalysis over 4 visits from negative binominal distribution was 57.3%, and from the computer simulation, 49.8%. The observed samples had significantly higher probability of achieving 4 negative results in urinalysis over 4 outpatient visits (p < 0.001).ConclusionsThe mandatory treatment modality boosted treatment stabilization for patients of amphetamine-type stimulant use disorder. The major benefit of using the monitoring model is the ability to monitor boosting effects of stabilization. Results supported the effectiveness of this mandatory treatment modality and can be implemented in deferred-prosecution based treatment modality.     

2016至2018年某医院真菌血流感染者流行病学特征及耐药性分析

目的分析真菌性血流感染的病原菌分布以及耐药特征，为真菌血流感染的早期合理用药提供理论依据。 方法回顾性分析武汉大学人民医院2016年1月至2018年12月收治的真菌性血流感染者的菌群、科室分布以及耐药性。 结果入组192例真菌血流感染者的血培养样本中共分离192株真菌，其中白色念珠菌检出率为31.77%（61/192），其次热带念珠菌检出率为18.75%（36/192）；重症医学科检出率最高为33.85%（65/192）。所有菌株均对两性霉素B敏感，对其他抗菌药物耐药率分别为5-氟胞嘧啶4.49%（9/192）、伊曲康唑5.73%（11/192）、氟康唑10.94%（21/192）和伏立康唑11.46%（22/192）；除两性霉素B外，2016至2018年真菌对其他抗菌药物的耐药率均逐年上升，其中2018年所分离192株光滑念珠菌对伊曲康唑耐药菌率达46.7%。 结论真菌血流感染病原菌以念珠菌属为主，对目前抗真菌药物具有较高敏感性，但耐药率逐年上升，加强监测血培养病原菌变化及耐药趋势对指导临床用药至关重要。     

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

Conservation laws are considered to be fundamental laws of nature. It has broad applications in many fields, including physics, chemistry, biology, geology, and engineering. Solving the differential equations associated with conservation laws is a major branch in computational mathematics. The recent success of machine learning, especially deep learning in areas such as computer vision and natural language processing, has attracted a lot of attention from the community of computational mathematics and inspired many intriguing works in combining machine learning with traditional methods. In this paper, we are the first to view numerical PDE solvers as an MDP and to use (deep) RL to learn new solvers. As proof of concept, we focus on 1-dimensional scalar conservation laws. We deploy the machinery of deep reinforcement learning to train a policy network that can decide on how the numerical solutions should be approximated in a sequential and spatial-temporal adaptive manner. We will show that the problem of solving conservation laws can be naturally viewed as a sequential decision-making process, and the numerical schemes learned in such a way can easily enforce long-term accuracy. Furthermore, the learned policy network is carefully designed to determine a good local discrete approximation based on the current state of the solution, which essentially makes the proposed method a meta-learning approach. In other words, the proposed method is capable of learning how to discretize for a given situation mimicking human experts. Finally, we will provide details on how the policy network is trained, how well it performs compared with some state-of-the-art numerical solvers such as WENO schemes, and supervised learning based approach L3D and PINN, and how well it generalizes.