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21.
Tian-Yuan Xiong Fang-Yang Huang Qi Liu Yong Peng Yuan-Ning Xu Jia-Fu Wei 《Annals of medicine》2020,52(7):361-366
Abstract
Background
Comorbidities are commonly seen in patients with coronavirus disease 2019 (COVID-19), but the clinical implication is not yet well-delineated. We aim to characterize the prevalence and clinical implications of comorbidities in patients with COVID-19. 相似文献22.
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目的 分析H型高血压患者的舌面诊图像颜色参数特征,探讨H型高血压患者的舌诊、面诊变化规律。方法 运用上海中医药大学自行研制的Smart TCM-1型中医舌面一体仪,采集高血压患者舌面诊图像,提取特征参数,分析健康对照组、H型高血压组与非H型高血压组患者舌面颜色参数特征。结果 ①在舌色各项参数中,H型高血压组舌尖部R值、B值、V值均显著小于健康对照组(P < 0.01);非H型高血压组舌尖部B值显著小于健康对照组(P < 0.01),S值较健康对照组显著增大(P < 0.05);H型高血压组舌尖部R、V值均明显小于非H型高血压组(P < 0.05)。在舌苔各项参数中,H型高血压组舌中H值、V值均明显小于健康对照组(P < 0.05);非H型高血压组舌中V值、舌右V值均显著小于健康对照组(P < 0.01);H型高血压组舌中H值明显小于非H型高血压组(P < 0.05),右侧舌苔S值明显大于非H型高血压组(P < 0.05)。②H型高血压组面色参数鼻G值、下颌G值、口唇R值、口唇V值均明显小于健康对照组(P < 0.05);非H型高血压组前额H值、目眶H值、脸颊H值、鼻H值、下颌H值、整体H值均明显大于健康对照组(P < 0.05);H型高血压组前额H值、目眶G值、目眶H值、脸颊H值、鼻G值、鼻H值、下颌R值、下颌G值、下颌H值、下颌V值、口唇R值、口唇G值、口唇V值、整体R值、整体G值、整体H值、整体V值均明显小于非H型高血压组(P < 0.05)。结论 H型高血压患者苔色偏黄,以舌中部为主,且舌右侧黄苔积聚较明显;H型高血压患者面色为黄中带红,口唇、下颌部更为晦暗。H型高血压患者的舌、面诊特征参数的变化,与高血压病阳亢湿盛病机相符。 相似文献
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The objective of the present study was to evaluate the clinical, radiological, and functional outcomes of a subscapularis transthoracic surgical approach and a posterolateral surgical approach with debridement, bone graft fusion, and internal fixation for the treatment of upper thoracic tuberculosis.There is currently debate over the best surgical approach for the treatment of upper thoracic tuberculosis. Traditionally, the subscapularis transthoracic approach has been preferred; however, the posterolateral approach has gained popularity in the past few years.A prospective, consecutive cohort of 43 upper thoracic tuberculosis patients with a mean age of 39 years (range: 20–52 years) was followed up for a minimum of 12 months (range: 12–60 months). Patients were randomly divided into 2 groups. Group A (n = 21) was treated by the subscapularis transthoracic approach and group B (n = 22) was treated by the posterolateral approach. All cases were evaluated for clinical, radiological, and functional outcomes. Intraoperative blood loss, operative duration, intraoperative and postoperative complications, hospital stay, the cure rate, fusion time, and the Frankel scale were used for clinical and functional evaluation, whereas the kyphosis angle was used for radiological evaluation.Grafted bones were fused by 10 months in all cases. There was no statistically significant difference between groups before surgery in terms of gender, age, segmental tuberculosis, erythrocyte sedimentation rate (ESR), Frankel scale, or Cobb''s angle (P > 0.05). The average operative duration for Group B was lower than that of Group A. There were no significant differences in intraoperative blood loss, intraoperative and postoperative complications, hospital stay, grafted bone fusion time, or cure rate between groups (P > 0.05). The Cobb''s angle correction rate for group B (68.5%) was significantly better than that of group A (30.9%). The neurological score showed significant postoperative improvement in both groups, with no significant difference between the groups.The subscapularis transthoracic approach and the posterolateral approach with debridement, bone graft fusion, and internal fixation are both sufficient and satisfactory for the surgical treatment of upper thoracic tuberculosis. However, the posterolateral approach is superior to the subscapularis transthoracic approach in terms of surgical trauma, operative time, and kyphosis correction. 相似文献
28.
当利用放射线对胸部恶性肿瘤进行治疗时,位于纵隔的心脏会不可幸免受到照射,从而诱发放射性心脏损伤(radiation-induced heart disease, RIHD)。随着手术以及放化疗技术的提升,肿瘤患者生存时间得到延长,使得RIHD这一放疗远期并发症被越来越多的报道。因此,学者们对于RIHD的研究逐渐升温。目前国内外学者关于该疾病尚未形成统一的认识,临床上缺乏有效阻止其发生的方法。动物模型研究可为临床该疾病治疗及预防提供可靠证据,为此本文回顾分析近年来放射性心脏损伤动物模型实验研究情况,旨在为后续实验开展及临床应用提供参考。 相似文献
29.
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning
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Yufei Wang Ziju Shen Zichao Long & Bin Dong 《Communications In Computational Physics》2020,28(5):2158-2179
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. 相似文献
30.
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。 相似文献