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Adults of the human parasitic trematode Schistosoma mansoni, which causes
hepatosplenic/intestinal complications in humans, synthesize
glycoconjugates containing the Lewis x (Lex) Galbeta1-->4(Fucalpha1--
>3)GlcNAcbeta1-->R, but not sialyl Lewis x (sLex), antigen. We now
report on our analyses of Lexand sLexexpression in S.haematobium and
S.japonicum, which are two other major species of human schistosomes that
cause disease, and the possible autoimmunity to these antigens in infected
individuals. Antigen expression was evaluated by both ELISA and Western
blot analyses of detergent extracts of parasites using monoclonal
antibodies. Several high molecular weight glycoproteins in both S.
haematobium and S. japonicum contain the Lexantigen, but no sialyl
Lexantigen was detected. In addition, sera from humans and rodents infected
with S.haematobium and S.japonicum contain antibodies reactive with Lex.
These results led us to investigate whether Lexantigens are expressed in
other helminths, including the parasitic trematode Fasciola hepatica , the
parasitic nematode Dirofilaria immitis (dog heartworm), the ruminant
nematode Haemonchus contortus , and the free-living nematode Caenorhabditis
elegans . Neither Lexnor sialyl-Lexis detectable in these other helminths.
Furthermore, none of the helminths, including schistosomes, express Lea,
Leb, Ley, or the H- type 1 antigen. However, several glycoproteins from all
helminths analyzed are bound by Lotus tetragonolobus agglutinin , which
binds Fucalpha1-->3GlcNAc, and Wisteria floribunda agglutinin, which
binds GalNAcbeta1-->4GlcNAc (lacdiNAc or LDN). Thus, schistosomes may be
unique among helminths in expressing the Lexantigen, whereas many different
helminths may express alpha1,3-fucosylated glycans and the LDN motif.
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A high yield of nifedipine-chitosan microspheres could be obtained using an emulsification phase-separation method. A high level of entrapment of nifedipine in the microspheres was achieved. The microspheres exhibited excellent swelling properties. Differential scanning calorimetry, X-ray diffractometry, and scanning electron microscopy confirmed that at 1.84% loading, nifedipine was dispersed molecularly. The microspheres exhibited faster release at low loadings compared to high loadings. Fitting the data to the coupled Fickian/case II equation, showed that at low loadings polymer relaxation coefficients (k2) were high. As the polymer content increased in the microspheres, the value of n (diffusional exponent characteristic of the release mechanism) approached one, which is indicative of zero order. 相似文献
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Rajarajan K Sakshi S Taria S Prathima PT Radhakrishna A Anuragi H Ashajyothi M Bharati A Handa AK Arunachalam A 《Molecular biology reports》2022,49(10):9453-9463
Molecular Biology Reports - Pongamia is considered an important biofuel species worldwide. Drought stress in the early growth stages of Pongamia influences negatively on the germination and... 相似文献
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Background
Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the presence of microarray data. Several data fusion techniques are available to integrate genomics or proteomics data, but only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. To improve clinical management, these data should be fully exploited. This requires efficient algorithms to integrate these data sets and design a final classifier.LS-SVM classifiers and generalized eigenvalue/singular value decompositions are successfully used in many bioinformatics applications for prediction tasks. While bringing up the benefits of these two techniques, we propose a machine learning approach, a weighted LS-SVM classifier to integrate two data sources: microarray and clinical parameters.Results
We compared and evaluated the proposed methods on five breast cancer case studies. Compared to LS-SVM classifier on individual data sets, generalized eigenvalue decomposition (GEVD) and kernel GEVD, the proposed weighted LS-SVM classifier offers good prediction performance, in terms of test area under ROC Curve (AUC), on all breast cancer case studies.Conclusions
Thus a clinical classifier weighted with microarray data set results in significantly improved diagnosis, prognosis and prediction responses to therapy. The proposed model has been shown as a promising mathematical framework in both data fusion and non-linear classification problems. 相似文献20.
Wagdy M. Eldehna Dina H. EL-Naggar Ahmed R. Hamed Hany S. Ibrahim Hazem A. Ghabbour Hatem A. Abdel-Aziz 《Journal of enzyme inhibition and medicinal chemistry》2018,33(1):309-318
Triple-negative breast cancer (TNBC) is a highly aggressive malignancy with limited treatment options due to its heterogeneity and the lack of well-defined molecular targets. In our endeavour towards the development of novel anti-TNBC agents, herein we report a one-pot three-component synthesis of novel spirooxindoles 6a–p, and evaluation of their potential anti-proliferative activity towards TNBC MDA-MB-231 cells. Spirooxindoles 6a, 6e and 6i emerged as the most potent analogues with IC50 =?6.70, 6.40 and 6.70?µM, respectively. Compounds 6a and 6e induced apoptosis in MDA-MB-231 cells, as evidenced by the up-regulation of the Bax and down-regulation of the Bcl-2, besides boosting caspase-3 levels. Additionally, 6e displayed significant increase in the percent of annexin V-FITC positive apoptotic cells from 1.34 to 44%. Furthermore, spirooxindoles 6e and 6i displayed good inhibitory activity against EGFR (IC50 =?120 and 150?nM, respectively). Collectively, these data demonstrated that 6e might be a potential lead compound for the development of effective anti-TNBC agents. 相似文献