Experimental study on the biocompatibility and osteogenesis induction ability of PLLA/DDM scaffolds

Odontology - To investigate the characterization and function of a novel porous osteogenic material (PLLA / DDM) containing polylactic acid and demineralized dentin matrix. The surface morphology...     

Clinical Diagnostic Implications of Body Fluid MiRNA in Oral Squamous Cell Carcinoma: A Meta-Analysis

Oral cancer, predominantly oral squamous cell carcinoma (OSCC), is one of the most leading causes of cancers worldwide. Due to a low 5-year survival rate, highly effective methods for the early detection of OSCC are totally needed. MicroRNAs (miRNAs), as promising biomarkers, can bring insights into tumorigenesis of oral cancers. However, studies on the accuracy of miRNAs detection in OSCC have inconsistent conclusions, leading us to conduct this meta-analysis. The aim of this study was to systematically review the articles investigating the diagnostic value of miRNAs in OSCC.The PubMed, Embase, Chinese National Knowledge Infrastructure (CNKI), Web of Science were searched (updated to June 11th, 2015) to identify all articles evaluating the diagnostic yield of miRNAs for OSCC. The pooled sensitivity, specificity, and other diagnostic parameters were used to assess the performance of miRNAs assays on OSCC detection. Statistical analysis was conducted by employing the R software.The present meta-analysis comprised 23 studies from 10 articles, including 598 OSCC patients and 320 healthy individuals, available for analysis. The summary receiver operator characteristic (SROC) curve was plotted. Meanwhile, the pooled diagnostic parameters and the area under curve (AUC) were calculated based on all included studies. The pooled diagnostic parameters calculated from all 23 studies were as follows: pooled sensitivity of 0.759 (95% CI: 0.701–0.809), pooled specificity of 0.773 (95% CI: 0.713–0.823) and AUC of 0.832, which indicates a relatively high diagnostic accuracy of miRNAs in differentiating OSCC patients from healthy controls. Meanwhile, In addition, subgroup analyses were conducted to access the heterogeneity between studies, which is based on specimen (serum/plasma/blood/saliva/ tissue) and ethnicity (Asian/Caucasian).In summary, our meta-analysis suggests that miRNAs might be used in noninvasive screening tests for OSCC, which needs further large-scale studies to be validated.     

沙库巴曲缬沙坦在心力衰竭治疗中的应用

心力衰竭是一种慢性疾病，是心脏无法泵出足够的血液为其他身体器官提供氧气，从而引发呼吸短促、疲劳和水肿等症状。目前其治疗包括病因治疗、一般治疗、药物治疗及非药物治疗等，其中血管紧张素受体脑啡肽酶抑制剂（ARNI）是当前新研发出的一类抗心衰药物，沙库巴曲缬沙坦是其代表药物，具有阻断肾素-血管紧张-醛固酮系统（RAAS）及抑制脑啡肽酶（NEP）的双重作用，新的欧美指南均推荐用于射血分数降低心力衰竭（HFrEF）的治疗。本文现就沙库巴曲缬沙坦在心力衰竭治疗中的作用机理、临床试验、药物安全性作一综述，旨在为该病的临床治疗提供参考。     

偏瘫性肩痛患者腋囊的MRI观测及临床意义

目的通过MRI技术观察偏瘫患者肩疼痛腋囊形态变化,为影像诊断提供依据。方法对47例偏瘫性肩疼痛患者(疼痛组)和47例正常肩部(对照组),运用MRI技术对肩关节腋囊进行测量,观察腋囊下肱盂韧带信号。结果偏瘫性肩疼痛的腋囊厚度(4.1±1.45)mm,高于对照组。腋囊腔高度(8.70±1.80)mm,腋囊腔宽度(4.31±0.56)mm,小于对照组。偏瘫性肩痛下肱盂韧带呈高信号出现率达21%,腋囊厚度与VAS呈正相关,与肩关节外展外旋呈负相关。结论脑中风中后期肩周炎是引起偏瘫性肩疼痛患者的常见原因,腋囊厚度是限制肩关节活动度的重要因素。     

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.     

桃红四物汤治疗雷诺氏病44例

近年来,笔者采用桃红四物汤治疗雷诺氏病44例,疗效满意,现报告如下. 一般资料 44例患者均为门诊病人,其中女性35例,男性9例;年龄16～58岁,平均26.7岁;病程1～6个月13例,7个月～1年22例,1年以上9例.主要症状均表现为手指皮肤苍白,继而青紫,先从手指尖开始,逐渐累及手指或全掌,呈典型的“手套征”,伴有局部冷、麻、针刺样疼痛或其他异常感觉,接触冷水或遇寒冷或情绪变化时发作,一般脉象沉细.本病发作十数分钟至1小时后症状可自行消失,严重者须保暖治疗（如将患指浸于温水中）方可缓解,皮肤转为潮红,然后恢复正常肤色.     

负压进针在心血管内科病人中的应用

[目的]探讨负压进针在心血管内科病人的静脉输注中是否优于常规进针法.[方法]将2004年1月-2005年6月我科收治且静脉穿刺难度大的病人随机分为实验组和对照组,实验组150例应用负压进针法,对照组150例应用常规进针法,比较两组的穿刺成功率和回血率.[结果]负压进针法比常规进针法的穿刺成功率提高了12%,回血率提高了13%,两组间穿刺成功率和回血率的差异有统计学意义(P＜0.01).[结论]负压进针大大提高了穿刺成功率和回血率,减少了病人的痛苦,提高护理人员的工作效率和住院病人满意度.