人巨细胞病毒感染诱导U251星形胶质瘤细胞凋亡及其差异蛋白的表达

目的分析人巨细胞病毒(HCMV)感染对人星形胶质瘤细胞凋亡的影响及其细胞内差异蛋白的表达。方法以HCMV AD169株感染U251细胞,复制HCMV体外感染模型,通过RT-PCR和免疫细胞化学技术检测HCMV IE蛋白和结构蛋白pp65的表达。用AnnexinⅤ-FITC和PI染色检测细胞凋亡,通过SELDI-TOF质谱分析感染细胞内差异蛋白的表达。结果HCMV感染后6 h,U251细胞经RT-PCR可扩增出242 bp的IE基因条带,感染后3 d,细胞核内有大量IE蛋白表达,核周及细胞浆内有大量pp65蛋白表达。病毒感染后3 d,约47%的细胞产生凋亡。HCMV感染后细胞内Caspase-8和磷脂酶A2的表达明显增加。结论HCMV感染可能通过上调Caspase-8和磷脂酶A2的表达而诱导U251星形胶质瘤细胞产生凋亡损伤。     

井间非均质渗透率分形预测

储集层渗透率空间分布既有严重的非均质性，又有统计自相似性。在预测泌阳凹陷双河油田４３７断块Ⅱ油组１小层井间渗透率非均质性时，首先根据取心井岩心实测渗透率与测井资料间的关系，建立渗透率解释模型；用该模型解释单井测井资料，得到逐点渗透率预测值，等序处理构成非均质渗透率序列，并研究豪斯特指数；根据井斜资料将井深校正为海拔高程，建立井间预测网格；用分形克里格法预测井间每个网格结点渗透率，用变序技术处理层状非均质分布问题，用权门槛技术解决泥质夹层预测问题，得到井间预测剖面；用取心井已知渗透率对预测结果进行交叉检验，计算单层平均预测误差（通过５口井资料的交叉检验，单层预测的平均误差为３５．１％）。将此预测结果用于该断块４６２注采井组分析，总结出７种储集层过渡类型，评价井组的单层连通情况，预测油水分布动态。预测成果还可用于识别厚油层内的夹层。图２表１参５（郭海莉摘）     

浅议传统潮绣纹饰图案的现代应用

文章以现代潮绣图案的风格特点为出发点,探讨潮绣图案构成在现今商业中的应用研究。通过在婚纱等服装中的视觉表现规律,使人们对潮绣在当今社会中的保护与研究得到更深层的理解。     

电力系统谐波对电能计量的影响

高压大功率电力电子电源容量的不断提高,给电力系统的电量计量带来了诸多问题.在分析电能表计量原理的基础上,对比分析了在谐波情况下电子式与电磁感应式电能表的计量差异,提出基于电力谐波的合理电能计量方法,并进行模拟验证.     

Droplet fate in indoor environments,or can we prevent the spread of infection?

Abstract Abstract When considering how people are infected and what can be done to prevent the infections, answers from many disciplines are sought: microbiology, epidemiology, medicine, engineering, and physics. There are many pathways to infection spread, and among the most significant from the epidemiological point of view is airborne transport. Microorganisms can become airborne when droplets are generated during speech, coughing, sneezing, vomiting, or atomization of feces during sewage removal. The fate of the droplets is governed by the physical principles of transport, with droplet size being the most important factor affecting their dispersion, deposition on surfaces and determining the survival of microorganisms within the droplets. In addition, physical characteristics of the indoor environment as well as the design and operation of building ventilation systems are of critical importance. Do we understand the mechanisms of infection spread and can we quantify the droplet dynamics under various indoor conditions? Unfortunately no, as this aspect of infection spread has attracted surprisingly little scientific interest. However, investigations of numerous cases in which a large number of people were infected show how critical the physics of microorganism spread can be. This paper reviews the state of knowledge regarding mechanisms of droplet spread and solutions available to minimize the spread and prevent infections.     

A model for diagnosis of pulmonary infections in solid-organ transplant recipients

Background

Opportunistic pulmonary infections are a major cause of morbidity and mortality among solid organ transplant recipients. The diagnosis of these infections is challenging because of the broad spectrum of bacteria, fungi and viruses affecting these patients and the lack of specific signs and symptoms. Treatment directed at the offending organism started as soon as possible improves survival.

Objective

To develop a decision support system for the diagnosis of pulmonary infections in solid-organ transplant recipients. The model's goal is to improve the accuracy of the diagnosis and thus the appropriateness of empirical treatment.

Design

The model is built using a Bayesian network (also known as causal probabilistic network). The network is based on pathogen segments which are the main building blocks of the model. Segments share common risk factors, such as time after transplantation, latent infections of donor/recipient and organ transplanted. The segments are linked at symptoms, signs and diagnostic tests common to all pathogens. The outputs of the model are predicted probabilities of infectious pathogens. To populate the model with data we have mainly abstracted data from the literature, using a systematic approach. The structure of the model and its adaptation for decision support will be presented.

Evaluation

The first evaluation phase assessed the model's diagnosis in a series of 20 representative cases of opportunistic infections. A match between the case's diagnosis and the model's prediction was achieved in 17/20 of cases. The next evaluation phase will consist of a prospective observational study comparing the accuracy of the model's diagnosis vs. that of the physician within 24 h of episode onset, as compared with a gold-standard diagnosis ascribed to the patients at the end of the infectious episode by two independent experts. Data for this phase are currently collected prospectively.     

氟-18-左旋氧氟沙星的标记与动物实验研究

炎症显像是核素影像诊断的重要研究领域,但其中正电子核素标记的药物报道不多.为探索合成一种可特异性在炎症部位浓集、且可鉴别是否为细菌性感染的正电子核素标记的显像剂,我们研究制备了18F标记的Levofloxacin(LVFX)用于炎症显像.标记方法采用经典的Hamacher法(氟离子亲核取代)标记LVFX,放射化学纯大于98%,放射性得率约40%,热原检测为阴性.结果表明标记方法简单迅速,标记物稳定.研究了18F-LVFX在正常炎症动物模型内的生物分布以及炎症动物模型的显像.生物分布和显像结果均表明18F-LVFX在炎症组织内有较高的摄取,炎症组织与正常组织间有显著性差异(P＜0.05),该标记物主要通过肾脏和肝脏排泄.研究表明18F-LVFX是一种潜在的炎症显像剂.     

院内感染系统中的数据预处理

在医院中院内感染是一个不可忽视的问题。医院内每天产生大量的数据，迫切需要挖掘出这些数据中与院内感染有关的因素。而数据预处理技术的好坏直接影响到数据挖掘的结果。介绍了针对院内感染数据挖掘系统，在关联规则挖掘前的数据预处理技术。     

An overview of recent applications of Game Theory to bioinformatics

The goal of this work is to provide a comprehensive review of different Game Theory applications that have been recently used to predict the behavior of non-rational agents in interaction situations arising from computational biology.In the first part of the paper, we focus on evolutionary games and their application to modelling the evolution of virulence. Here, the notion of Evolutionary Stable Strategy (ESS) plays an important role in modelling mutation mechanisms, whereas selection mechanisms are explained by means of the concept of replicator dynamics.In the second part, we describe a couple of applications concerning cooperative games in coalitional form, namely microarray games and Multi-perturbation Shapley value Analysis (MSA), for the analysis of genetic data. In both of the approaches, the Shapley value is used to assess the power of genes in complex regulatory pathways.     

Lpconvergence of a process identification algorithm

In this paper, we study the phenomena of the epidemic spreading process in small-world networks, where recovery responses are practically delayed. We propose and investigate three novel linear delayed SIR models for different cases of recovery response. Because the recovery strategies respond with some time-delays as happens in practice, it is found that the unsuitable recovery strength may not suppress the prevalent epidemics and even lead to oscillations. Therefore, it is strongly suggested that the administrative authorities should apply control strategies of recovery as soon as possible on the small prevalent viruses before they spread into a disaster of infections.