重组人白细胞介素-6的纯化

重组人白细胞介素－６（ｒｈＩＬ－６）在工程菌ｐＢＶ２２０／ｒｈＩＬ－６／ＤＨ５ａ中以包涵体形式高效表达。ｒｈＩＬ－６经过工程菌体破碎、包涵体分离及抽提、复性、色谱分离后得到高度纯化。纯化产物纯度９５％,具有良好的生物学活性     

A formal model for analyzing drug combination effects and its application in TNF-α-induced NFκB pathway

Background

Drug combination therapy is commonly used in clinical practice. Many methods including Bliss independence method have been proposed for drug combination design based on simulations models or experiments. Although Bliss independence method can help to solve the drug combination design problem when there are only a small number of combinations, as the number of combinations increases, it may not be scalable. Exploration of system structure becomes important to reduce the complexity of the design problem.

Results

In this paper, we deduced a mathematical model which can simplify the serial structure and parallel structure of biological pathway for synergy evaluation of drug combinations. We demonstrated in steady state the sign of the synergism assessment factor derivative of the original system can be predicted by the sign of its simplified system. In addition, we analyzed the influence of feedback structure on survival ratio of the serial structure. We provided a sufficient condition under which the combination effect could be maintained. Furthermore, we applied our method to find three synergistic drug combinations on tumor necrosis factor α-induced NFκB pathway and subsequently verified by the cell experiment.

Conclusions

We identified several structural properties underlying the Bliss independence criterion, and developed a systematic simplification framework for drug combiation desgin by combining simulation and system reaction network topology analysis. We hope that this work can provide insights to tackle the challenging problem of assessment of combinational drug therapy effect in a large scale signaling pathway. And hopefully in the future our method could be expanded to more general criteria.     

A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains

Despite evidence of the clustering of metabolic syndrome components, current approaches for identifying unifying genetic mechanisms typically evaluate clinical categories that do not provide adequate etiological information. Here, we used data from 19,486 European American and 6,287 African American Candidate Gene Association Resource Consortium participants to identify loci associated with the clustering of metabolic phenotypes. Six phenotype domains (atherogenic dyslipidemia, vascular dysfunction, vascular inflammation, pro-thrombotic state, central obesity, and elevated plasma glucose) encompassing 19 quantitative traits were examined. Principal components analysis was used to reduce the dimension of each domain such that >55% of the trait variance was represented within each domain. We then applied a statistically efficient and computational feasible multivariate approach that related eight principal components from the six domains to 250,000 imputed SNPs using an additive genetic model and including demographic covariates. In European Americans, we identified 606 genome-wide significant SNPs representing 19 loci. Many of these loci were associated with only one trait domain, were consistent with results in African Americans, and overlapped with published findings, for instance central obesity and FTO. However, our approach, which is applicable to any set of interval scale traits that is heritable and exhibits evidence of phenotypic clustering, identified three new loci in or near APOC1, BRAP, and PLCG1, which were associated with multiple phenotype domains. These pleiotropic loci may help characterize metabolic dysregulation and identify targets for intervention.     

Impact of Repeated Exposures on Information Spreading in Social Networks

Clustered structure of social networks provides the chances of repeated exposures to carriers with similar information. It is commonly believed that the impact of repeated exposures on the spreading of information is nontrivial. Does this effect increase the probability that an individual forwards a message in social networks? If so, to what extent does this effect influence people’s decisions on whether or not to spread information? Based on a large-scale microblogging data set, which logs the message spreading processes and users’ forwarding activities, we conduct a data-driven analysis to explore the answer to the above questions. The results show that an overwhelming majority of message samples are more probable to be forwarded under repeated exposures, compared to those under only a single exposure. For those message samples that cover various topics, we observe a relatively fixed, topic-independent multiplier of the willingness of spreading when repeated exposures occur, regardless of the differences in network structure. We believe that this finding reflects average people’s intrinsic psychological gain under repeated stimuli. Hence, it makes sense that the gain is associated with personal response behavior, rather than network structure. Moreover, we find that the gain is robust against the change of message popularity. This finding supports that there exists a relatively fixed gain brought by repeated exposures. Based on the above findings, we propose a parsimonious model to predict the saturated numbers of forwarding activities of messages. Our work could contribute to better understandings of behavioral psychology and social media analytics.     

Establishment of New Genetic Markers and Methods for Sex Determination of Mouse and Human Cells using Polymerase Chain Reactions and Crude DNA Samples

Background: The currently available methods for sexing human or mouse cells have weaknesses. Therefore, it is necessary to establish new methods.Methods: We used bioinformatics approach to identify genes that have alleles on both the X and Y chromosomes of mouse and human genomes and have a region showing a significant difference between the X and Y alleles. We then used polymerase chain reactions (PCR) followed by visualization of the PCR amplicons in agarose gels to establish these genomic regions as genetic sex markers.Results: Our bioinformatics analyses identified eight mouse sex markers and 56 human sex markers that are new, i.e. are previously unreported. Six of the eight mouse markers and 14 of the 56 human markers were verified using PCR and ensuing visualization of the PCR amplicons in agarose gels. Most of the tested and untested sex markers possess significant differences in the molecular weight between the X- and Y-derived PCR amplicons and are thus much better than most, if not all, previously-reported genetic sex markers. We also established several simple and essentially cost-free methods for extraction of crude genomic DNA from cultured cells, blood samples, and tissues that could be used as template for PCR amplification.Conclusion: We have established new sex genetic markers and methods for extracting genomic DNA and for sexing human and mouse cells. Our work may also lend some methodological strategies to the identification of new genetic sex markers for other organismal species.     

Erythroid 5‐aminolevulinate synthase mediates the upregulation of membrane band 3 protein expression by iron

Iron deficiency leads to abnormal expression and function of band 3 protein in erythrocytes, but the underlying mechanisms remain elusive. The mRNA of erythroid‐specific 5‐aminolevulinate synthase (eALAS) contains an iron response element and the eALAS protein is an important mediator of iron utilization by erythrocytes. In this study, we investigated the effect of short hairpin RNA (shRNA) mediated silencing of eALAS on the expression of band 3 protein induced by iron. By real‐time RT‐PCR and Western blot we showed that at mRNA and protein level iron‐induced expression of band 3 protein was lower in eALAS‐shRNA transfected K562 cells than in control cells. Of note, the lowest expression was detected in K562 cells cultured in iron deficiency condition (p < 0.01). Thus either iron deficiency or depletion of eALAS could suppress the expression of erythroid band 3 protein. These results demonstrated for the first time that iron and the iron‐regulatory system regulate the expression of the erythrocyte membrane proteins. Copyright © 2010 John Wiley & Sons, Ltd.