Expression of Lex antigen in Schistosoma japonicum and S.haematobium and immune responses to Lex in infected animals: lack of Lex expression in other trematodes and nematodes

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.      

Nifedipine loaded chitosan microspheres prepared by emulsification phase-separation

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.     

The effects of herbivory by a mega- and mesoherbivore on tree recruitment in sand forest, South Africa

Herbivory by megaherbivores on woody vegetation in general is well documented; however studies focusing on the individual browsing effects of both mega- and mesoherbivore species on recruitment are scarce. We determined these effects for elephant Loxodonta africana and nyala Tragelaphus angasii in the critically endangered Sand Forest, which is restricted to east southern Africa, and is conserved mainly in small reserves with high herbivore densities. Replicated experimental treatments (400 m(2)) in a single forest patch were used to exclude elephant, or both elephant and nyala. In each treatment, all woody individuals were identified to species and number of stems, diameter and height were recorded. Results of changes after two years are presented. Individual tree and stem densities had increased in absence of nyala and elephant. Seedling recruitment (based on height and diameter) was inhibited by nyala, and by elephant and nyala in combination, thereby preventing recruitment into the sapling stage. Neither nyala or elephant significantly reduced sapling densities. Excluding both elephant and nyala in combination enhanced recruitment of woody species, as seedling densities increased, indicating that forest regeneration is impacted by both mega- and mesoherbivores. The Sand Forest tree community approached an inverse J-shaped curve, with the highest abundance in the smaller size classes. However, the larger characteristic tree species in particular, such as Newtonia hildebrandtii, were missing cohorts in the middle size classes. When setting management goals to conserve habitats of key importance, conservation management plans need to consider the total herbivore assemblage present and the resulting browsing effects on vegetation. Especially in Africa, where the broadest suite of megaherbivores still persists, and which is currently dealing with the 'elephant problem', the individual effects of different herbivore species on recruitment and dynamics of forests and woodlands are important issues which need conclusive answers.     

Transmembrane protein 2 (Tmem2) is required to regionally restrict atrioventricular canal boundary and endocardial cushion development

The atrioventricular canal (AVC) physically separates the atrial and ventricular chambers of the heart and plays a crucial role in the development of the valves and septa. Defects in AVC development result in aberrant heart morphogenesis and are a significant cause of congenital heart malformations. We have used a forward genetic screen in zebrafish to identify novel regulators of cardiac morphogenesis. We isolated a mutant, named wickham (wkm), that was indistinguishable from siblings at the linear heart tube stage but exhibited a specific loss of cardiac looping at later developmental stages. Positional cloning revealed that the wkm locus encodes transmembrane protein 2 (Tmem2), a single-pass transmembrane protein of previously unknown function. Expression analysis demonstrated myocardial and endocardial expression of tmem2 in zebrafish and conserved expression in the endocardium of mouse embryos. Detailed phenotypic analysis of the wkm mutant identified an expansion of expression of known myocardial and endocardial AVC markers, including bmp4 and has2. By contrast, a reduction in the expression of spp1, a marker of the maturing valvular primordia, was observed, suggesting that an expansion of immature AVC is detrimental to later valve maturation. Finally, we show that immature AVC expansion in wkm mutants is rescued by depleting Bmp4, indicating that Tmem2 restricts bmp4 expression to delimit the AVC primordium during cardiac development.     

Whole plant response of Pongamia pinnata to drought stress tolerance revealed by morpho-physiological,biochemical and transcriptome analysis

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...     

Predicting breast cancer using an expression values weighted clinical classifier

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.