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.     

Bilateral dacryops

The clinical, radiologic, and histopathologic findings of a case of bilateral dacryops is reported in a 49-year-old man. The patient presented with cystic masses located in superior lateral orbits and underwent bilateral excisions of these without any postoperative complications.     

经皮穿刺髓核成形术治疗腰椎间盘突出症初步临床报道

目的　寻求一种简单、安全、有效、微创的椎间盘突出症治疗方法。方法　对 1 6例腰椎间盘突出症采用经皮穿刺髓核成形术 (Nucleoplasty)治疗 ,并对其疗效进行观察分析。 结果　全部患者经二周至一个月短期随访 ,症状均有不同程度改善 ,疗效优良率为 93 8% ,有效率为 1 0 0 %。未发现明显并发症。结论　髓核成形术是一种先进、安全、有效的椎间盘突出微创手术 ,具有操作简单、安全、微创、疗效佳、恢复快、无需住院等优点。     

烹调油烟致大小鼠肺癌的实验研究

[目的]了解烹调油烟（cooking oil fumes，COF）的动物致癌性。[方法]采用动式染毒法给Balb／c小鼠（雌雄各半）吸入COF浓度为9．09、20．65、38．85mg／m^3，染毒1次／1～2d，30min／次，共150次，计8个月；SD大鼠（雌雄各半）吸入COF浓度为6、88、15．06、35．33mg／m^3，染毒1次／2d，30min／次，共191次，计12．5个月。分别制备COF慢性中毒动物模型；两实验均设空白对照组，吸入与实验组相同温度的清洁空气。[结果]COF诱发Balb／c小鼠实验组肺癌总发生率为18、95％（29／153），低、中、高浓度组肺癌发生率分别为15．09％、20、00％和22．00％，与对照组差异均有显著性。但低、中、高三组间差异无显著性（P〉0．05）；COF诱发SD大鼠肺癌总发生率为9、10％（9／99），低、中、高浓度组肺癌发生率分别为6．45％、8．57％、12．12％，高浓度组肺癌发生率高于对照组（P〈0．05）。各性别组间肺癌发生率的差别无显著性（P〉0．05）。[结论]COF可以诱导Balb／c小鼠和SD大鼠肺癌，诱发的肺癌主要为肺腺癌（小鼠28／29，大鼠7／9），余为小细胞肺癌。     

视疲劳中医古籍探源及其证治

中医学认为，肝开窍于目，劳瞻竭视，暗耗精血，而出现上述诸多证候，故称之为“肝劳”。古代医家对肝劳在病名、病因、病机方面做了较为全面的论述，在调养和治疗方面亦有述及，现分述如下