无热原蒸汽灭菌在疫苗生产中的应用与效果验证

为保证生物制剂生产的安全性,采用空载热分布试验,满载热穿透试验和微生物挑战试验对无热原蒸汽灭菌柜进行验证。另取疫苗生产中常用的Earle's液、PBS液及0.2%水解乳蛋白各5批,均采用无热原注射用水配制,无热原蒸汽灭菌。选用"Fluids121℃"15分钟循环程序和"Fluids115℃"20分钟循环程序检测热原质与灭菌效果。灭菌试验验证结果显示,无热原蒸汽灭菌符合现行GMP的要求。     

蒸汽灭菌过程中液体装载非无菌可能性的评价

我们进行了脉动真空蒸汽灭菌柜的确认及验证工作,以葡萄糖肉汤培养基为例,我们进行了热穿透,热分布的数据分析,生物挑战实验确认,和培养基促生长实验确认,针对本公司脉动真空灭菌柜特定型号液体装载,我们设定的灭菌参数既能达到药典的无菌要求,又能保证培养基的促生长实验要求。     

高温灭菌操作中常见错误的分析

高温灭菌是指用热能杀死微生物。其原理是高温使原生质中的蛋白质变性、使酶失活,致使微生物死亡。高温灭菌主要有高压蒸汽灭菌法、干热灭菌法和灼烧灭菌法几种。如果操作不当,即达不到预期的灭菌效果。现就常见错误分析如下。1高压蒸汽灭菌蒸汽灭菌属湿热灭菌,由于湿热灭菌有潜能存在,被灭菌物体的温度比蒸汽的低,蒸汽在其表面凝结成水,放出潜能,可迅速提高被灭菌物体的温度。又由于水和水蒸汽比空气的热容量大、导热快、穿透力强,所以,与干热灭菌相比,灭菌需要的温度低、时间短。由于高压蒸汽灭菌法水蒸汽的温度随其所受压力的…     

对不同材料包扎的生产用容器灭菌效果的比较试验

为了改进长期以来细胞瓶以牛皮纸加无纺布包装后进行灭菌的方式,实验中依据国内外的有关资料和现行GMP的要求,结合生产的实际情况,以15L细胞瓶为对象,用不同材料(牛皮纸加无纺布、铝箔纸、两层无纺布、带砂芯的硅胶塞)包装后进行灭菌效果的比较试验及残留蒸汽冷凝水测量试验,结果显示用带砂芯的硅胶塞包装的细胞瓶在灭菌过程中瓶内实际温度均能达到设定要求,热穿透及微生物标的验证试验也符合《中华人民共和国药典》(三部)2005年版的标准要求,残留蒸汽冷凝水明显少于其它包装方式,有最好的实际应用价值。     

高压蒸汽灭菌对麦康凯琼脂培养基质量的影响

目的探讨高压蒸汽灭菌对麦康凯琼脂培养基主要质量指标(p H、性能)的影响。方法配制p H为6.80、7.00、7.10、7.20、7.30、7.40、7.50、7.60、7.70、7.80的麦康凯琼脂培养基,经高压蒸汽灭菌后进行p H测定,并将大肠埃希菌、金黄色葡萄球菌、鼠伤寒沙门菌和粪肠球菌接种于麦康凯琼脂培养基上,37℃培养24 h,观察不同p H对细菌生长的影响。结果高压蒸汽灭菌后麦康凯琼脂培养基p H降低0.30~0.50。p H为6.78~7.28时,大肠埃希菌生长率≥0.5;p H为6.93~7.39时,鼠伤寒沙门菌生长率≥0.5;不同p H的麦康凯琼脂培养基上金黄色葡萄球菌及粪肠球菌的生长指数均为0。结论高压蒸汽灭菌可影响麦康凯琼脂培养基的p H及性能。     

高压热水浸提法提取金针菇中游离氨基酸的优化研究

研究了采用高压热水浸提法从金针菇中提取游离氨基酸的最适条件。通过单因素试验和正交试验,探讨了料液比、高压热水浸提时间及高压热水浸提温度对金针菇中游离氨基酸提取率的影响。试验结果表明,此法提取金针菇中游离氨基酸的最适条件为：料液比为1∶35（g/mL）、高压热水浸提温度为108℃、高压热水浸提时间为50min。在此条件下,金针菇中游离氨基酸的提取率为3.37%。     

压力蒸汽灭菌指示剂的筛选和效果验证

利用结晶物质在一定温度下熔融的特性,通过对几种灭菌指示剂内容物进行熔点测定,选出苯甲酸化学试剂和升华硫化学试剂作为高压灭菌指示剂和灭菌参考指示剂。试验表明,这两种指示剂终点明确,简便快速,价格便宜,能满足121℃高压灭菌的温度要求,可以对高压灭菌的日常监测提供依据。     

环氧乙烷混合气体消毒柜

消毒和灭菌是提高疗效的重要手段之一。现今消毒和灭菌方法大体可分四类;热灭菌、辐射灭菌、过滤除菌和化学灭菌,应用比较广泛的主要有高压蒸汽、气体、辐射三种方法。随着医学科学和其他科学技术的发展,医用电子仪器、光学内窥器械和医用高分子材料在医学上得到了广泛的应用,传统的高压蒸汽灭菌已无法解决这些器械、材料的灭菌消毒。从而环氧乙烷气体及其设备在消毒和灭菌方面具有更加广泛的实用价值。杂环类气体消毒剂系指以环氧乙烷为基础的一系列具有杀菌作用的衍生物。它的杀菌机制是由于对蛋白质分子的烷基化作用,干扰了微生物酶的正常代谢而使之死亡。无     

立式自动高压蒸汽灭菌器3Q验证方案研究

分析仪器(设备)验证方案包括:IQ(安装确认)、OQ(运行确认)及PQ(性能确认)三个步骤。通过对分析仪器(设备)的3Q验证,可以确保分析仪器设备的性能符合检测要求,从而保证检测结果的准确性。高压蒸汽灭菌器的仪器状态能直接影响到食品微生物检测结果,所以本文对微生物实验室用高压蒸汽灭菌器的验证方法及步骤进行研究,总结一套适用于微生物检测实验室的3Q验证方案。     

高压蒸汽灭菌对钛合金内植入物的疲劳的影响

分析了制约骨折手术成功的因素,一是钛合金内植人物经受长期反复高压蒸汽灭菌造成材料疲劳引起断裂;二是AO手术的引起应力集中和疲劳断裂。提出了发展骨内固定植入物的建议。     

Genome-based prediction of test cross performance in two subsequent breeding cycles

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.     

An empirical assessment of validation practices for molecular classifiers

Proposed molecular classifiers may be overfit to idiosyncrasies of noisy genomic and proteomic data. Cross-validation methods are often used to obtain estimates of classification accuracy, but both simulations and case studies suggest that, when inappropriate methods are used, bias may ensue. Bias can be bypassed and generalizability can be tested by external (independent) validation. We evaluated 35 studies that have reported on external validation of a molecular classifier. We extracted information on study design and methodological features, and compared the performance of molecular classifiers in internal cross-validation versus external validation for 28 studies where both had been performed. We demonstrate that the majority of studies pursued cross-validation practices that are likely to overestimate classifier performance. Most studies were markedly underpowered to detect a 20% decrease in sensitivity or specificity between internal cross-validation and external validation [median power was 36% (IQR, 21-61%) and 29% (IQR, 15-65%), respectively]. The median reported classification performance for sensitivity and specificity was 94% and 98%, respectively, in cross-validation and 88% and 81% for independent validation. The relative diagnostic odds ratio was 3.26 (95% CI 2.04-5.21) for cross-validation versus independent validation. Finally, we reviewed all studies (n = 758) which cited those in our study sample, and identified only one instance of additional subsequent independent validation of these classifiers. In conclusion, these results document that many cross-validation practices employed in the literature are potentially biased and genuine progress in this field will require adoption of routine external validation of molecular classifiers, preferably in much larger studies than in current practice.     

A comparison of eight methods for the dual-endpoint evaluation of efficacy in a proof-of-concept HIV vaccine trial

To support the design of the world's first proof-of-concept (POC) efficacy trial of a cell-mediated immunity-based HIV vaccine, we evaluate eight methods for testing the composite null hypothesis of no-vaccine effect on either the incidence of HIV infection or the viral load set point among those infected, relative to placebo. The first two methods use a single test applied to the actual values or ranks of a burden-of-illness (BOI) outcome that combines the infection and viral load endpoints. The other six methods combine separate tests for the two endpoints using unweighted or weighted versions of the two-part z, Simes', and Fisher's methods. Based on extensive simulations that were used to design the landmark POC trial, the BOI methods are shown to have generally low power for rejecting the composite null hypothesis (and hence advancing the vaccine to a subsequent large-scale efficacy trial). The unweighted Simes' and Fisher's combination methods perform best overall. Importantly, this conclusion holds even after the test for the viral load component is adjusted for bias that can be introduced by conditioning on a postrandomization event (HIV infection). The adjustment is derived using a selection bias model based on the principal stratification framework of causal inference.     

Report of the EPAA-ECVAM workshop on the validation of Integrated Testing Strategies (ITS)

The use of Integrated Testing Strategies (ITS) permits the combination of diverse types of chemical and toxicological data for the purposes of hazard identification and characterisation. In November 2008, the European Partnership for Alternative Approaches to Animal Testing (EPAA), together with the European Centre for the Validation of Alternative Methods (ECVAM), held a workshop on Overcoming Barriers to Validation of Non-animal Partial Replacement Methods/Integrated Testing Strategies, in Ispra, Italy, to discuss the extent to which current ECVAM approaches to validation can be used to evaluate partial replacement in vitro test methods (i.e. as potential ITS components) and ITS themselves. The main conclusions of these discussions were that formal validation was only considered necessary for regulatory purposes (e.g. the replacement of a test guideline), and that current ECVAM approaches to validation should be adapted to accommodate such test methods. With these conclusions in mind, a follow-up EPAA-ECVAM workshop was held in October 2009, to discuss the extent to which existing validation principles are applicable to the validation of ITS test methods, and to develop a draft approach for the validation of such test methods and/or overall ITS for regulatory purposes. This report summarises the workshop discussions that started with a review of the current validation methodologies and the presentation of two case studies (skin sensitisation and acute toxicity), before covering the definition of ITS and their components, including their validation and regulatory acceptance. The following main conclusions/recommendations were made: that the validation of a partial replacement test method (for application as part of a testing strategy) should be differentiated from the validation of an in vitro test method for application as a stand-alone replacement, especially with regard to its predictive capacity; that, in the former case, the predictive capacity of the whole testing strategy (rather than of the individual test methods) would be more important, especially if the individual test methods had a high biological relevance; that ITS allowing for flexible and ad hoc approaches cannot be validated, whereas the validation of clearly defined ITS would be feasible, although practically quite difficult; and that test method developers should be encouraged to develop and submit to ECVAM not only full replacement test methods, but also partial replacement methods to be placed as parts of testing strategies. The added value from the formal validation of testing strategies, and the requirements needed in view of regulatory acceptance of the data, require further informed discussion within the EPAA forum on the basis of case studies provided by industry.     

Fuzzy-logic based strategy for validation of multiplex methods: example with qualitative GMO assays

This paper illustrates the advantages that a fuzzy-based aggregation method could bring into the validation of a multiplex method for GMO detection (DualChip^® GMO kit, Eppendorf). Guidelines for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation statistics are available and routinely used, for in-house and inter-laboratory testing, and decision-making. Fuzzy logic allows summarising the information obtained by independent validation statistics into one synthetic indicator of overall method performance. The microarray technology, introduced for simultaneous identification of multiple GMOs, poses specific validation issues (patterns of performance for a variety of GMOs at different concentrations). A fuzzy-based indicator for overall evaluation is illustrated in this paper, and applied to validation data for different genetically modified elements. Remarks were drawn on the analytical results. The fuzzy-logic based rules were shown to be applicable to improve interpretation of results and facilitate overall evaluation of the multiplex method.     

Blood lactate vs. exhaustive exercise to evaluate aerobic fitness

This study compared the predictive power of a lactate-related index determined during submaximal cycle exercise to that of an exhaustive cycle ergometer test for evaluating the endurance exercise capacity of soldiers. The subjects (n = 48 males) performed a continuous exercise test to voluntary exhaustion on the cycle ergometer. Power output (PO) increased by 50 W steps each fourth min, with determinations of heart rate (HR), RPE and blood lactate concentrations (HLa) just prior to each PO increase. The PO at a 4 mmol L(-1) HLa concentration (WOBLA) was interpolated; based on the time to exhaustion the maximal PO that could be maintained for 6 min (Wmax6) was calculated from previously documented formulae. Subjects were timed during a 3000 m cross-country run. Both the cycle test and the run were performed again 3 months later, as was an additional 3000 m run with full military equipment weighing about 21 kg. All 3000 m times were significantly correlated (p less than 0.05) with both Wmax6 and WOBLA; similar predictive power was demonstrated for both Wmax6 and WOBLA, suggesting that accuracy in evaluation would not be sacrificed by substituting the submaximal for the exhaustive exercise test. HR and RPE-related indices showed markedly lower predictive power. The results extend the previously documented relationship between HLa during treadmill ergometry and running performance to include the use of cycle ergometry for the evaluation of running performance. The results also proved applicable to running performance while load carrying.     

Validation of chemometric models for the determination of deoxynivalenol on maize by mid-infrared spectroscopy

Validation methods for chemometric models are presented, which are a necessity for the evaluation of model performance and prediction ability. Reference methods with known performance can be employed for comparison studies. Other validation methods include test set and cross validation, where some samples are set aside for testing purposes. The choice of the testing method mainly depends on the size of the original dataset. Test set validation is suitable for large datasets (>50), whereas cross validation is the best method for medium to small datasets (<50). In this study the K-nearest neighbour algorithm (KNN) was used as a reference method for the classification of contaminated and blank corn samples. A Partial least squares (PLS) regression model was evaluated using full cross validation. Mid-Infrared spectra were collected using the attenuated total reflection (ATR) technique and the fingerprint range (800–1800 cm⁻¹) of 21 maize samples that were contaminated with 300 – 2600 μg/kg deoxynivalenol (DON) was investigated. Separation efficiency after principal component analysis/cluster analysis (PCA/CA) classification was 100%. Cross validation of the PLS model revealed a correlation coefficient of r=0.9926 with a root mean square error of calibration (RMSEC) of 95.01. Validation results gave an r=0.8111 and a root mean square error of cross validation (RMSECV) of 494.5 was calculated. No outliers were reported. Presented at the 25^th Mykotoxin Workshop in Giessen, Germany, May 19–21, 2003     

ILLUMINA Golden Gate DNA甲基化芯片的KL-FCM聚类分析

DNA甲基化作为一种重要的表观遗传修饰,其甲基化水平被发现与疾病的发生发展密切相关,对其进行聚类分析有希望发现新的疾病亚型并建立有效的疾病预测预后方法。传统的聚类分析方法之一模糊C-均值（FCM：Fuzzy C-means）适用于特征空间呈球形或椭球形分布的场景,缺乏普适性。而Illumina Golden Gate平台通过计算基因的各甲基化位点的甲基化百分比描述其甲基化程度,其值位于（0,1）之间,服从混合贝塔分布,不能直接采用FCM进行聚类分析。鉴于此,本文提出基于KL特征测度的KL-FCM聚类算法,采用各样本间的K-L距离作为样本划分时的度量准则。最后,本文基于KL-FCM算法实现IRIS测试数据集和基因的DNA甲基化水平数据的聚类分析。实验结果表明该方法可以以更低的计算负荷获得优于k-均值（k-means）和传统FCM的分类效果。