膝骨关节炎患者关节滑液中IL-17水平与疾病严重程度的相关性

目的 探讨膝骨美节炎(KOA)患者美节滑液中IL 17的水平与疾病严重程度的相关性，为临床诊治KOA 提供新思路及新方法。方法 选取2017年1月?2018年12月南充市中心医院康复科收治的15。例膝骨美节炎患者作 为实验组，同时纳入30例健康志愿者作为对照组。实验组釆用视觉模拟量表(VAS)评价膝关节的疼痛程度，采用膝关 节学会评分系统(KSS)评价膝关节的功能及采用Kellgren Lawrence (KL)分级系统评价膝关节X线严重程度，通过 ELISA试验检测两组膝关节滑液中IL17的水平。采用Spearman相关分析KOA患者关节滑液中IL 17水平与膝关节 疼痛程度、膝关节功能及X线严重程度的相关性。结果 实验组关节滑液中IL17的水平明显高于对照组(P <0. 05). IL 17水平在滕美节炎KL分级之间比较，差异无统计学差异(P>0. 05)。IL 17的水平与膝关节VAS评分呈正相关 (P=0. 914,P<0.01),IL 17的水平与KSS呈负相关(P=—0. 847,P<0. 01), IL 17的水平与KL分级无相关性(r = 0.050,P= 0.545)。结论 IL 17可反应膝骨关节炎患者疼痛程度及功能损伤程度，但不能反映疾病的X线严重程度。 IL 17可作为一个生化指标反应膝关节炎疼痛程度及膝关节功能，临床通过减少关节滑液中IL 17,可能会减轻膝骨关 节炎患者的临床症状。     

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.     

补骨脂素抗增生性瘢痕作用机制研究

目的探讨补骨脂素抗增生性瘢痕的作用机制。方法体外培养成纤维细胞,按随机数字表法分为正常组(培养正常成纤维细胞)、瘢痕组(培养增生性瘢痕成纤维细胞)、TGF-β1组(10 ng/ml TGF-β1处理增生性瘢痕成纤维细胞5 min^12 h)、Smurf2 RNA干扰组[Smad泛素化调节因子2(Smad ubiquitin regulatory factor2,Smurf2)siRNA转染增生性瘢痕成纤维细胞72 h]、补骨脂素组(10μmol/L补骨脂素处理增生性瘢痕成纤维细胞继续培养72 h)、补骨脂素+TGF-β1组(增生性瘢痕成纤维细胞加入补骨脂素培养72 h后加入TGF-β1培养6 h)。采用Western blot法检测Smurf2、α-平滑肌肌动蛋白(α-actin SMA,α-SMA)蛋白表达;RT-PCR法检测Ⅰ型胶原蛋白mRNA表达;ELISA法检测TGF-β1蛋白分泌。结果与正常组比较,瘢痕组Smurf2蛋白[(0.83±0.08)比(0.38±0.07)]表达增加(P<0.05);与瘢痕组比较,Smurf2 RNA干扰组TGF-β1[(2.2±0.18)比(4.2±0.47)]表达降低(P<0.05);TGF-β1组Smurf2[(0.71±0.06)比(0.42±0.04)]、α-SMA[(1.42±0.12)比(0.91±0.09)]蛋白表达增加(P<0.05),Ⅰ型胶原蛋白mRNA[(0.72±0.09)比(0.41±0.07)]表达增加(P<0.05);补骨脂素组Smurf2[(0.05±0.01)比(0.42±0.04)]、α-SMA[(0.71±0.07)比(0.91±0.09)]蛋白表达降低(P<0.05),Ⅰ型胶原蛋白mRNA表达[(0.12±0.04)比(0.41±0.07)]降低(P<0.05)。结论补骨脂素可能通过TGF-β1/Smurf2信号通路抑制α-SMA蛋白表达,从而降低Ⅰ型胶原蛋白表达,起到抑制瘢痕形成的作用。     

The prognostic role of tumour‐infiltrating lymphocytes in oral squamous cell carcinoma: A meta‐analysis

It has been suggested that tumour‐infiltrating lymphocytes (TILs) are associated with the progression of oral squamous cell carcinoma (OSCC). However, the prognostic value of TILs is inconclusive due to the heterogeneity of immune cells within the tumour microenvironment. In this meta‐analysis, we aimed to assess the prognostic value of TILs in OSCC. The PubMed, Cochrane, Embase, Scopus and Web of Science databases were searched up to April 20, 2019, and 33 studies were ultimately included in this meta‐analysis. Our pooled meta‐analysis showed that high infiltration of CD8⁺ TILs, CD45RO⁺ TILs and CD57⁺ TILs favoured better overall survival (OS). However, high infiltration of CD68⁺ macrophages and CD163⁺ macrophages was associated with poor prognosis in OSCC. These findings suggest that CD8⁺ TILs, CD45RO⁺ TILs, CD57⁺ TILs, CD68⁺ macrophages and CD163⁺ macrophages might serve as novel prognostic factors and therapeutic targets in OSCC.     

改良俯卧位对俯卧位通气临床疗效及并发症的影响

目的观察改良俯卧位对俯卧位通气(PPV)临床疗效及并发症的影响。方法将该院呼吸和危重症医学科行PPV的52例患者随机分为对照组和实验组各26例,对照组应用常规方法进行PPV,实验组采用改良俯卧位进行PPV。比较两组患者PPV的临床效果和并发症发生情况。结果两组间俯卧位前和俯卧位后12 h的氧合指数无明显差异(P>0.05);两组患者俯卧位后12 h的氧合指数均较各组俯卧位前明显改善(P<0.05);两组患者气管插管脱出、血流动力学显著波动、误吸和面部水肿的发生率无显著差异(P>0.05);实验组皮肤压疮的发生率明显低于对照组(P<0.05)。结论改良俯卧位对PPV的临床疗效无显著影响,但可以降低皮肤压疮的发生率。     

抑郁症患者血浆孤啡肽含量研究

目的为探讨抑郁症的可能病因,对抑郁症患者血浆孤啡肽(OFQ)含量进行了对照研究。方法抽取29例抑郁症患者和24例正常人的静脉血,用放射免疫(RIA)的方法分别测其血浆中OFQ含量,比较抑郁症患者和正常人血浆OFQ含量有无差异,抑郁症患者OFQ含量与汉密顿抑郁量表(HAMD)评分的相关性,及抑郁症患者血浆OFQ含量的影响因素。结果与正常人比较,抑郁症组OFQ含量明显升高(t=8．70,P＜0．0001)；OFQ含量与HAMD评分呈正相关(r=0．63,P＜0．01)；OFQ含量主要与抑郁情绪、夸大、失眠、自卑感、自杀、强迫症状、教育水平、关注身体健康等因素相关,而年龄、性别、职业、病程、曾用药等其他因素与OFQ含量无明显相关。结论通过测量血浆OFQ含量可作为抑郁症诊断的参考指标。     

动脉栓塞对骨盆肿瘤手术疗效的影响

[目的]探讨供血动脉栓塞对骨盆肿瘤手术疗效的影响。[方法]本组16例，脊索瘤7例，骨巨细胞瘤3例，骨转移瘤3例，骨肉瘤2例，神经纤维瘤1例。术前1d行肿瘤血管造影并用明胶海绵进行供血动脉栓塞。与对照组（结扎双侧髂内动脉骨盆肿瘤切除术）比较，观察其对术中出血量、手术时间、住院时间、术后下床时间、伤口愈合时间及术后各种功能恢复的影响。[结果]骨盆肿瘤切除术前肿瘤供血动脉栓塞与结扎双侧髂内动脉比较，除术中出血量外（P〉0．05），手术、住院、术后下床及伤口愈合时间在统计学上均有非常显著性差异（P〈0．001），而且结扎双侧髂内动脉可能对患者的性功能、排便功能等存在着不良的影响。[结论]肿瘤供血动脉栓塞骨盆肿瘤切除术可大大缩短手术、住院、术后下床、伤口愈合时间，且能更好地保护盆腔内外各组织器官的血运，从而避免其功能的损害。