盐胁迫对蓝蓟种子萌发及早期幼苗的影响

研究了不同浓度盐(NaCl)处理对蓝蓟种子发芽势、发芽率及幼苗生长的影响。结果表明:(1)不同盐胁迫处理对蓝蓟种子的萌发具有显著影响。随着盐处理浓度的增加,发芽率呈下降趋势,蓝蓟在无盐环境(蒸馏水)和低盐环境中(0.05 mol/L)长势最好、发芽率最高、发芽速度最快。(2)将不同盐溶液处理5 d的未萌发种子转移到蒸馏水后,蓝蓟种子的萌发能力均可恢复,原来较高盐浓度(0.3 mol/L～0.5 mol/L)下的种子在恢复后,其萌发恢复率均在75%以上,发芽率基本上随着原浓度的升高呈上升的趋势。研究表明,NaCl处理对蓟种子没有造成伤害,其抑制萌发是通过渗透效应而不是离子毒害。     

Characterization of six microsatellite loci in Echium vulgare (Boraginaceae)

Echium vulgare is a tetraploid plant with a very low selfing rate in the field. We suspect that cryptic self incompatibility plays a role in this species. In order to show lower success of self pollen/selfed embryos, after pollination with a mixture of self and outcross pollen, a paternity analysis has to be done. For the purpose of such analysis we developed microsatellites in E. vulgare. In this study, we report on six microsatellite loci which are easy to score, polymorphic, with a number of alleles per locus ranging from two to eight and, therefore, suitable for paternity analysis.     

Raman based chemometric model development for glycation and glycosylation real time monitoring in a manufacturing scale CHO cell bioreactor process

The Quality by Design (QbD) approach to the production of therapeutic monoclonal antibodies (mAbs) emphasizes an understanding of the production process ensuring product quality is maintained throughout. Current methods for measuring critical quality attributes (CQAs) such as glycation and glycosylation are time and resource intensive, often, only tested offline once per batch process. Process analytical technology (PAT) tools such as Raman spectroscopy combined with chemometric modeling can provide real time measurements process variables and are aligned with the QbD approach. This study utilizes these tools to build partial least squares (PLS) regression models to provide real time monitoring of glycation and glycosylation profiles. In total, seven cell line specific chemometric PLS models; % mono-glycated, % non-glycated, % G0F-GlcNac, % G0, % G0F, % G1F, and % G2F were considered. PLS models were initially developed using small scale data to verify the capability of Raman to measure these CQAs effectively. Accurate PLS model predictions were observed at small scale (5 L). At manufacturing scale (2000 L) some glycosylation models showed higher error, indicating that scale may be a key consideration in glycosylation profile PLS model development. Model robustness was then considered by supplementing models with a single batch of manufacturing scale data. This data addition had a significant impact on the predictive capability of each model, with an improvement of 77.5% in the case of the G2F. The finalized models show the capability of Raman as a PAT tool to deliver real time monitoring of glycation and glycosylation profiles at manufacturing scale.     

Spatial pattern of ovule maturation in the inflorescence of Echium vulgare: demography, resource allocation and the constraints of architecture

Many of the flowers produeed bv a plant fail to mature seeds despite effective pollination. The role of inflorescence architecture governing patterns of abortion in plants has been underestimated. 1 he inflorescence of Echium vulgare L. comprises a raceme bearing lateral inflorescences, each of which is cymosc. Within each cyme, there is a correlation between the proximity of a flower to the main axis and its order of flowering; and (lie probability of it maturing seeds. These findings appear to result from a decrease in the availability of maternal resources as the flowering period progresses. No relationship could be shown between the position of the cyme on the main inflorescence and the number of seeds set per flower although position was correlated with the length of the cyme, the number of (lowers and the length of the subtending bract. The mctamcric units of E. vulgare appear to function largely independently in their assimilation of resources. Larger cymes not only bear more flowers, but also draw on a larger area of photosynthetic tissue for resources. This hypothesis is supported by the removal of the bract or of part of the cyme at the onset of flowering; cymes without bracts mature fewer ovules than controls while decapitated cymes mature a greater proportion of ovules.     

Chemometrics applications in biotech processes: a review

Biotech unit operations are often characterized by a large number of inputs (operational parameters) and outputs (performance parameters) along with complex correlations amongst them. A typical biotech process starts with the vial of the cell bank, ends with the final product, and has anywhere from 15 to 30 such unit operations in series. The aforementioned parameters can impact process performance and product quality and also interact amongst each other. Chemometrics presents one effective approach to gather process understanding from such complex data sets. The increasing use of chemometrics is fuelled by the gradual acceptance of quality by design and process analytical technology amongst the regulators and the biotech industry, which require enhanced process and product understanding. In this article, we review the topic of chemometrics applications in biotech processes with a special focus on recent major developments. Case studies have been used to highlight some of the significant applications.     

Guidance for performing multivariate data analysis of bioprocessing data: Pitfalls and recommendations

Biotech unit operations are often characterized by a large number of inputs (operational parameters) and outputs (performance parameters) along with complex correlations among them. A typical biotech process starts with the vial of the cell bank, ends with the final product, and has anywhere from 15 to 30 such unit operations in series. Besides the above‐mentioned operational parameters, raw material attributes can also impact process performance and product quality as well as interact among each other. Multivariate data analysis (MVDA) offers an effective approach to gather process understanding from such complex datasets. Review of literature suggests that the use of MVDA is rapidly increasing, fuelled by the gradual acceptance of quality by design (QbD) and process analytical technology (PAT) among the regulators and the biotech industry. Implementation of QbD and PAT requires enhanced process and product understanding. In this article, we first discuss the most critical issues that a practitioner needs to be aware of while performing MVDA of bioprocessing data. Next, we present a step by step procedure for performing such analysis. Industrial case studies are used to elucidate the various underlying concepts. With the increasing usage of MVDA, we hope that this article would be a useful resource for present and future practitioners of MVDA. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:967–973, 2014     

Chemometrics applications in biotech processes: assessing process comparability

A typical biotech process starts with the vial of the cell bank, ends with the final product and has anywhere from 15 to 30 unit operations in series. The total number of process variables (input and output parameters) and other variables (raw materials) can add up to several hundred variables. As the manufacturing process is widely accepted to have significant impact on the quality of the product, the regulatory agencies require an assessment of process comparability across different phases of manufacturing (Phase I vs. Phase II vs. Phase III vs. Commercial) as well as other key activities during product commercialization (process scale-up, technology transfer, and process improvement). However, assessing comparability for a process with such a large number of variables is nontrivial and often companies resort to qualitative comparisons. In this article, we present a quantitative approach for assessing process comparability via use of chemometrics. To our knowledge this is the first time that such an approach has been published for biotech processing. The approach has been applied to an industrial case study involving evaluation of two processes that are being used for commercial manufacturing of a major biosimilar product. It has been demonstrated that the proposed approach is able to successfully identify the unit operations in the two processes that are operating differently. We expect this approach, which can also be applied toward assessing product comparability, to be of great use to both the regulators and the industry which otherwise struggle to assess comparability.     

Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

牛至化学成分的研究

从药用植物牛至（Ｏｒｉｇａａｎｕｍ ｖｕｌｇａｒｅ Ｌ．）中分离并鉴定了８个化合物;乌素酸（１）、齐墩果酸（２）、原儿茶酸（３）、日本椴甙（４）、Ｓａｇｉｔｔａｔｏｓｉｄｅ Ａ（５）、胡萝卜甙（６）、β－谷甾醇（７）、豆甾醇（８）。２～５为首次从该种植物中分离得到。     

Chemometrics applications in biotechnology processes: Predicting column integrity and impurity clearance during reuse of chromatography resin

Separation media, in particular chromatography media, is typically one of the major contributors to the cost of goods for production of a biotechnology therapeutic. To be cost‐effective, it is industry practice that media be reused over several cycles before being discarded. The traditional approach for estimating the number of cycles a particular media can be reused for involves performing laboratory scale experiments that monitor column performance and carryover. This dataset is then used to predict the number of cycles the media can be used at manufacturing scale (concurrent validation). Although, well accepted and widely practiced, there are challenges associated with extrapolating the laboratory scale data to manufacturing scale due to differences that may exist across scales. Factors that may be different include: level of impurities in the feed material, lot to lot variability in feedstock impurities, design of the column housing unit with respect to cleanability, and homogeneity of the column packing. In view of these challenges, there is a need for approaches that may be able to predict column underperformance at the manufacturing scale over the product lifecycle. In case such an underperformance is predicted, the operators can unpack and repack the chromatography column beforehand and thus avoid batch loss. Chemometrics offers one such solution. In this article, we present an application of chemometrics toward the analysis of a set of chromatography profiles with the intention of predicting the various events of column underperformance including the backpressure buildup and inefficient deoxyribonucleic acid clearance. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2012     

黄瓜育成品种"春玉"RAPD指纹图谱分析

从300条随机引物中筛选出能稳定扩增的26个引物．对黄瓜育成品种“春玉”等21个实验材料进行扩增,在扩增出的173条谱带中,多态性带有80条,比例为46．24％。“春玉”在用引物E13扩增时有特异缺失条带,大小为400bp,可作为特征性指纹图谱,为其产权保护提供分子依据。利用各材料的DNA指纹可将不同参试材料鉴别出来。同时利用MEGA软件进行UPGMA聚类分析,将参试材料在相似系数0．706处分为4个组群。