MSCs 2种分离培养方法及其培养液中的 VEGF、SDF-1α浓度比较

目的：通过2种分离培养方法所得骨髓间充质干细胞（MSCs）的生长特征和微环境中细胞因子的比较,提供一种可以快速、安全、高效地为临床和实验提供大量优质MSCs的方法。方法提取C57BL／c小鼠的骨髓,分别作密度梯度离心法和全骨髓贴壁培养分离法分离培养MSCs ,通过流式细胞仪检测细胞表面CD29＋、CD31－、CD34－、CD45－表达水平,并比较各自所得细胞的生长曲线;ELISA检测培养液中的血管内皮生长因子（VEGF）、SDF‐1α浓度并比较二者的差异。结果与密度梯度离心法比较,全骨髓贴壁分离法所得原代细胞有较快的生长速度,较短的生长周期;培养液中VEGF和SDF‐1α浓度也稍高于密度梯度离心法。结论全骨髓贴壁培养法可以快速、方便、有效地为临床和实验提供大量MSCs ,所得细胞的培养环境优于密度梯度离心法,减少了对细胞功能的损害。     

Can nurses exclude middle-ear effusion without otoscopy in young asymptomatic children in primary care?

Objective. Scandinavian guidelines recommend controlling middle-ear effusion (MEE) after acute otitis media. The study aim was to determine whether nurses without otoscopic experience can reliably exclude MEE with tympanometry or spectral gradient acoustic reflectometry (SG-AR) at asymptomatic visits. Design. Three nurses were taught to perform examinations with tympanometry and SG-AR. Pneumatic otoscopy by the study physician served as the diagnostic standard. Setting. Study clinic at primary health care level. Patients. A total of 156 children aged 6–35 months. Main outcome measures. Predictive values (with 95% confidence interval) for tympanometry and SG-AR, and the clinical usefulness, i.e. the proportion of visits where nurses obtained the exclusive test result from both ears of the child. Results. At 196 visits, the negative predictive value of type A and C1 tympanograms (tympanometric peak pressure > −200 daPa) was 95% (91–97%). Based on type A and C1 tympanograms, the nurse could exclude MEE at 81/196 (41%) of visits. The negative predictive value of SG-AR level 1 result was 86% (79–91%). Based on SG-AR level 1 results, the nurse could exclude MEE at 29/196 (15%) of visits. Conclusion. Tympanograms with tympanometric peak pressure > −200 daPa (types A and C1) obtained by nurses are reliable test results in excluding MEE. However, these test results were obtained at less than half of the asymptomatic visits and, thus, the usefulness of excluding MEE by nurses depends on the clinical setting.     

密度梯度离心联合上游法的精液处理在供精体外受精胚胎移植中的应用

目的:观察供精体外受精-胚胎移植术(D-IVF)中采用密度梯度离心法联合上游法处理精液后的胚胎情况。方法:回顾本院2013年1月-2014年7月D-IVF 135个周期,观察冷冻精液复苏后经采用密度梯度离心法联合上游法处理后精子总活动率、前向运动精子活动率等精液情况,以及受精以后的受精率、卵裂率、临床妊娠率,对照组为同期46个因丈夫梗阻性无精行ICSI的周期。结果:处理后精子总活动率、前向运动精子活动率均大大提高,但是精子密度却大大下降,处理前后比较差异均有统计学意义(P0.05);受精以后的实验室资料和对照组比较,各项参数差异无统计学意义(P0.05)。结论:密度梯度离心法联合上游法的精液处理方法在D-IVF中是一种稳定可行的方法。     

SHR大鼠前额叶、纹状体突触体的提取方法

目的 介绍SHR大鼠前额叶、纹状体突触体的提取方法。方法 采用Percoll密度梯度离心法制备突触体,透射电镜观察其形态和结构完整性。结果 本实验所获取的突触体形态上呈连续膜封闭的椭圆结构,周围有完整的膜包围;突触前成分可见一个或多个线粒体和大量突触小囊泡;突触间隙清晰可见,且突触后部分特征性的致密部结构完整,形态清晰,密度较高。突触体突触前膜、突触间隙、突触后膜保存完好,突触体分布密度较高,具有典型的突触体形态结构特征。结论 本实验提供了一种耗时少,产出率高,结构完整、形态典型且可运用于精细化研究的突触体制备新技术,补充了传统技术的不足,为神经系统疾病的研究提供技术支持。     

Fast and effective removal of contamination from scalp electrical recordings

ObjectiveTo present a new, automated and fast artefact-removal approach which significantly reduces the effect of contamination in scalp electrical recordings.MethodWe used spectral and temporal characteristics of different sources recorded during a typical scalp electrical recording in order to improve a fast and effective artefact removal approach. Our experiments show that correlation coefficient and spectral gradient of brain components differ from artefactual components. We trained two binary support vector machine classifiers such that one separates brain components from muscle components, and the other separates brain components from mains power and environmental components. We compared the performance of the proposed approach with seven currently used alternatives on three datasets, measuring mains power artefact reduction, muscle artefact reduction and retention of brain neurophysiological responses.ResultsThe proposed approach significantly reduces the main power and muscle contamination from scalp electrical recording without affecting brain neurophysiological responses. None of the competitors outperformed the new approach.ConclusionsThe proposed approach is the best choice for artefact reduction of scalp electrical recordings. Further improvements are possible with improved component analysis algorithms.SignificanceThis paper provides a definitive answer to an important question: Which artefact removal algorithm should be used on scalp electrical recordings?