Binary protein adsorption to DEAE sepharose FF

Equilibrium between ion exchangers and proteins is one of the most important factors in ion exchange chromatography. A model system was used to simulate the adsorption of human serum albumin (HSA) and ovalbumin (OVA) as a binary protein system to the DEAE Sepharose FF as an anion exchanger. Two models, one based on a competition between adsorbing molecules and the other a non competitive model have been compared to experimental results. Competitive adsorption was seen in experiments in which breakthrough curves and the profiles of adsorbed proteins in packed beds were determined. However, although the results for packed bed experiments were more closely predicted by the competitive model, some discrepancies were found, suggesting that when considering multicomponent protein adsorption to ion exchangers it may also be necessary to take account of factors such as the molecular size of adsorbing proteins and any potential inter protein interaction, which may hinder the development of a general model of multicomponent protein adsorption to ion exchangers.     

Study on the dissolution of heat-induced ovalbumin gel in alkaline solutions relevant to the removal of fouling deposits

Heat-induced whey protein concentrate gels (HIWPCG) have previously been used to simulate milk fouling and cleaning processes. The related research has generated considerable knowledge, which is of practical interest. In the current study, heat-induced ovalbumin gels (HIOVAG) have been employed to investigate the dissolution process (related to chemical cleaning process). Both HIOVAG and HIWPCG are sensitive to NaOH solution, which is a common cleaning fluid in food industry. In contrast to the HIWPCG behavior, HIOVAG dissolution presents no optimal NaOH concentration where the rate of dissolution is highest. The dissolution temperature was found to positively influence the dissolution process of HIOVAG, i.e. the dissolution rate increased with increasing dissolution temperature. In addition, ovalbumin (OVA) concentration in HIOVAG was found to be another important factor influencing the dissolution process. However, the stirring speed (convection) and heating time had no effect in the range tested, indicating that the process was internally limited.     

Measuring the Manipulation of T Helper Immune Responses by Schistosoma mansoni

Schistosoma mansoni uses different mechanisms to escape its host’s immunity. Understanding the ability of memory T cells to withstand this pathogen’s manipulation is important for the development of effective vaccines against this immunomodulatory pathogen. In this study, ovalbumin (OVA) transgenic S. mansoni is used as a tool to investigate whether fully differentiated Th1, Th2 and Th17 cells are able to withstand pathogen manipulation. Naïve T cells from OT-II T cell receptor transgenic mice with a specificity for OVA were differentiated into Th1, Th2, and Th17 polarised memory cells in vitro. These cells were adoptively transferred into recipient mice to investigate whether these polarised immune memory T cells are resilient in the face of pathogen-mediated manipulation. After transferring memory cells, mice were challenged with OVA-transduced S. mansoni eggs as well as wild-type controls. The in vitro differentiated Th1, Th2 and Th17 memory cells continued to produce the same cytokines when challenged by OVA-expressing S. mansoni eggs as to these they produced when transferred in vivo, suggesting that the Th phenotypes of the memory T cells remains unaltered in the face of stimulation by S. mansoni. The ability of memory T cells to remain resilient to manipulation by the parasite suggests that vaccines might be able to produce immune memory responses able to withstand S. mansoni immune manipulation and hence protect the host from infection.     

磺胺二甲嘧啶人工抗原的合成与鉴定

采用重氮化法将磺胺二甲嘧啶(SM2)与牛血清白蛋白(BSA)和卵清蛋白(OVA)交联合成人工抗原SM2-BSA与SM2-OVA,并通过紫外扫描、SDS-PAGE电泳、凝胶层析和红外光谱等方法扫描进一步检测合成效果.紫外扫描检测结果显示,SM2与BSA、OVA偶联成功,SM2-BSA与SM2-OVA的特征波长分别为2762、77 nm;经计算SM2-BSA与SM2-OVA的分子结合比例分别为5.3∶1和18.4∶1;SDS-PAGE电泳迁移率、凝胶层析出峰时间和红外光谱曲线特征均显示SM2与BSA、OVA偶联成功.     

基于断言的SoC设计验证方法

随着SoC(System on-a-Chip)设计规模的指数增长,验证时的模拟时间也变得越来越长,已经到了令人无法忍受的地步.因此如何进行有效、充分的验证,尤其是功能验证已经成为SoC设计方法学中重要的内容.本文将要介绍的基于断言的验证(Assertion Based Verification,ABV)是SoC设计功能验证的一种有效的方法,能够有效地提高验证效率.     

An Approach to Speech Emotion Classification Using k-NN and SVMs

The interaction between humans and machines has become an issue of concern in recent years. Besides facial ex-pressions or gestures, speech has been evidenced as one of the foremost promising modalities for automatic emotion recognition. Effective computing means to support HCI (Human-Computer Interaction) at a psychological level, al-lowing PCs to adjust their reactions as per human requirements. Therefore, the recognition of emotion is pivotal in High-level interactions. Each Emotion has distinctive properties that form us to recognize them. The acoustic signal produced for identical expression or sentence changes is essentially a direct result of biophysical changes, (for example, the stress instigated narrowing of the larynx) set off by emotions. This connection between acoustic cues and emotions made Speech Emotion Recognition one of the moving subjects of the emotive computing area. The most motivation behind a Speech Emotion Recognition algorithm is to observe the emotional condition of a speaker from recorded Speech signals. The results from the application of k-NN and OVA-SVM for MFCC features without and with a feature selection approach are presented in this research. The MFCC features from the audio signal were initially extracted to characterize the properties of emotional speech. Secondly, nine basic statistical measures were calculated from MFCC and 117-dimensional features were consequently obtained to train the classifiers for seven different classes (Anger, Happiness, Disgust, Fear, Sadness, Disgust, Boredom and Neutral) of emotions. Next, Classification was done in four steps. First, all the 117-features are classified using both classifiers. Second, the best classifier was found and then features were scaled to [-1, 1] and classified. In the third step, the with or without feature scaling which gives better performance was derived from the results of the second step and the classification was done for each of the basic sta-tistical measures separately. Finally, in the fourth step, the combination of statistical measures which gives better per-formance was derived using the forward feature selection method Experiments were carried out using k-NN with different k values and a linear OVA-based SVM classifier with different optimal values. Berlin emotional speech da-tabase for the German language was utilized for testing the planned methodology and recognition rates as high as 60% accomplished for the recognition of emotion from voice signal for the set of statistical measures (median, maximum, mean, Inter-quartile range, skewness). OVA-SVM performs better than k-NN and the use of the feature selection technique gives a high rate.     

Intermediate role of α-keto acids in the formation of Strecker aldehydes

The ability of α-keto acids to covert amino acids into Strecker aldehydes was investigated in an attempt to both identify new pathways for Strecker degradation, and analyse the role of α-keto acids as intermediate compounds in the formation of Strecker aldehydes by oxidised lipids. The results obtained indicated that phenylalanine was converted into phenylacetaldehyde to a significant extent by all α-keto acids assayed; glyoxylic acid being the most reactive α-keto acid for this reaction. It has been proposed that the reaction occurs by formation of an imine between the keto group of the α-keto acid, and the amino group of the amino acid. This then undergoes an electronic rearrangement with the loss of carbon dioxide to produce a new imine. This final imine is the origin of both the Strecker aldehyde and the amino acid from which the α-keto acid is derived. When glycine was incubated in the presence of 4,5-epoxy-2-decenal, the amino acid was converted into glyoxylic acid, and this α-keto acid was then able to convert phenylalanine into phenylacetaldehyde. All these results suggest that Strecker aldehydes can be produced by amino acid degradation initiated by different reactive carbonyl compounds, included those coming from amino acids and proteins. In addition, α-keto acids may act as intermediates for the Strecker degradation of amino acids by oxidised lipids.     

Human IgE binding and in vitro digestion of S-OVA

S-OVA, a more thermostable form of ovalbumin (OVA), was formed from native OVA or egg white in vitro, by heating at high pH, and by storage at low temperatures. S-OVA showed a much lower reactivity against IgE than OVA, although this difference in IgE binding was minimized after simulated gastro intestinal digestion, despite S-OVA was more resistant to proteolysis, particularly to pepsin, than its native form. It is, therefore, likely that the transformation of OVA to S-OVA does not affect its ability to sensitise or trigger allergic reactions at the duodenal level. These results are discussed in the light of the described conformational changes reported to occur in the transition between OVA and S-OVA.