Effect of quinidine on Na,H+, and water transport by the turtle and toad bladders

Summary The effect of quinidine on Na and H⁺ transport by the turtle bladder and water transport by the toad bladder was examined. Quinidine inhibited the short-circuit current and the potential difference in a dose-dependent fashion. The effect of quinidine on the short-circuit was not dependent on extracellular calcium concentration and was not reversible with removal of the drug. Quinidine inhibited H⁺ secretion in a dose-dependent fashion. The effect of quinidine on H⁺ secretion also was not dependent on extracellular calcium concentration and was not reversible, either with removal of the drug or with stimulation of H⁺ secretion with 5% CO₂. The effect of quinidine on Na or H⁺ transport could not be elicited by an equivalent dose of tetracaine, suggesting that the inhibitory effect of quinidine is not dependent on its anesthetic properties. Quinidine also inhibited vasopressin and cyclic AMP stimulated water flow in the toad bladder. Quinidine did not alter calcium uptake by the turtle bladder but increased calcium efflux by the turtle and toad bladders. These observations suggest that a rise in cytosolic calcium is responsible for the inhibitory effect of quinidine on Na, H⁺, and water transport.     

Structural investigation of the capsular polysaccharide of klebsiella serotype K26

The structure of the capsular polysaccharide from Klebsiella K26 has been determined by using the techniques of methylation, periodate oxidation, partial hydrolysis, and β-elimination. N.m.r. spectroscopy (¹H and ¹³C) was used to establish the nature of the anomeric linkages and to identify oligosaccharides obtained by the different degradative techniques employed.The polysaccharide is comprised of repeating units of the heptasaccharide shown.

     

Synthesis,semipreparative HPLC separation,biological evaluation,and 3D-QSAR of hydrazothiazole derivatives as human monoamine oxidase B inhibitors

The present study reports on synthesis in high yields (70–99%), HPLC enantioseparation, inhibitory activity against human monoamino oxidases, and molecular modeling including 3D-QSAR studies, of a large series of (4-aryl-thiazol-2-yl)hydrazones (1–45). Most of the synthesized compounds proved to be potent and selective inhibitors of hMAO-B isoform in the micromolar or nanomolar range, thus demonstrating that hydrazothiazole could be considered a good pharmacophore to design new hMAO-B inhibitors. Due to the presence in some derivatives of a chiral center, we also performed a semipreparative chromatographic enantioseparation of these compounds obtained by a stereoconservative pattern. The separated enantiomers were submitted to in vitro biological evaluation to point out the stereorecognition of the active site of the enzyme towards these structures. Finally, a 3D-QSAR study was carried out using Comparative Molecular Field Analysis (CoMFA), aiming to deduce rational guidelines for the further structural modification of these lead compounds.     

Prediction of Disease Causing Non-Synonymous SNPs by the Artificial Neural Network Predictor NetDiseaseSNP

We have developed a sequence conservation-based artificial neural network predictor called NetDiseaseSNP which classifies nsSNPs as disease-causing or neutral. Our method uses the excellent alignment generation algorithm of SIFT to identify related sequences and a combination of 31 features assessing sequence conservation and the predicted surface accessibility to produce a single score which can be used to rank nsSNPs based on their potential to cause disease. NetDiseaseSNP classifies successfully disease-causing and neutral mutations. In addition, we show that NetDiseaseSNP discriminates cancer driver and passenger mutations satisfactorily. Our method outperforms other state-of-the-art methods on several disease/neutral datasets as well as on cancer driver/passenger mutation datasets and can thus be used to pinpoint and prioritize plausible disease candidates among nsSNPs for further investigation. NetDiseaseSNP is publicly available as an online tool as well as a web service: http://www.cbs.dtu.dk/services/NetDiseaseSNP     

α-synuclein levels affect autophagosome numbers in vivo and modulate Huntington disease pathology

Huntington and Parkinson diseases (HD and PD) are two major neurodegenerative disorders pathologically characterized by the accumulation of the aggregate-prone proteins mutant huntingtin (in HD) and α-synuclein (in PD). Mutant huntingtin is an autophagy substrate and autophagy modulators affect HD pathology both in vitro and in vivo. In vitro, α-synuclein levels are able to modulate autophagy: α-synuclein overexpression inhibits autophagy, whereas downregulation promotes autophagy. Here, we review our recent studies showing that α-synuclein levels modulate mutant huntingtin toxicity in mouse models. This phenotypic modification is accompanied by the in vivo modulation of autophagosome numbers in mouse brains from both control and HD mice expressing different levels of α-synuclein.     

Capsaicin Modulates Proliferation,Migration, and Activation of Hepatic Stellate Cells

Capsaicin, the active component of chili pepper, has been reported to have antiproliferative and anti-inflammatory effects on a variety of cell lines. In the current study, we aimed to investigate the effects of capsaicin during HSC activation and maintenance. Activated and freshly isolated HSCs were treated with capsaicin. Proliferation was measured by incorporation of EdU. Cell cycle arrest and apoptosis were investigated using flow cytometry. The migratory response to chemotactic stimuli was evaluated by a modified Boyden chamber assay. Activation markers and inflammatory cytokines were determined by qPCR, immunocytochemistry, and flow cytometry. Our results show that capsaicin reduces HSC proliferation, migration, and expression of profibrogenic markers of activated and primary mouse HSCs. In conclusion, the present study shows that capsaicin modulates proliferation, migration, and activation of HSC in vitro.     

Mast cells impair the development of protective anti-tumor immunity

Mast cells have emerged as critical intermediaries in the regulation of peripheral tolerance. Their presence in many precancerous lesions and tumors is associated with a poor prognosis, suggesting mast cells may promote an immunosuppressive tumor microenvironment and impede the development of protective anti-tumor immunity. The studies presented herein investigate how mast cells influence tumor-specific T cell responses. Male MB49 tumor cells, expressing HY antigens, induce anti-tumor IFN-??⁺ T cell responses in female mice. However, normal female mice cannot control progressive MB49 tumor growth. In contrast, mast cell-deficient c-Kit^Wsh (W^sh) female mice controlled tumor growth and exhibited enhanced survival. The role of mast cells in curtailing the development of protective immunity was shown by increased mortality in mast cell-reconstituted W^sh mice with tumors. Confirmation of enhanced immunity in female W^sh mice was provided by (1) higher frequency of tumor-specific IFN-??⁺ CD8⁺ T cells in tumor-draining lymph nodes compared with WT females and (2) significantly increased ratios of intratumoral CD4⁺ and CD8⁺ T effector cells relative to tumor cells in W^sh mice compared to WT. These studies are the first to reveal that mast cells impair both regional adaptive immune responses and responses within the tumor microenvironment to diminish protective anti-tumor immunity.     

Identifying DNA splice sites using hypernetworks with artificial molecular evolution

Identifying DNA splice sites is a main task of gene hunting. We introduce the hyper-network architecture as a novel method for finding DNA splice sites. The hypernetwork architecture is a biologically inspired information processing system composed of networks of molecules forming cells, and a number of cells forming a tissue or organism. Its learning is based on molecular evolution. DNA examples taken from GenBank were translated into binary strings and fed into a hypernetwork for training. We performed experiments to explore the generalization performance of hypernetwork learning in this data set by two-fold cross validation. The hypernetwork generalization performance was comparable to well known classification algorithms. With the best hypernetwork obtained, including local information and heuristic rules, we built a system (HyperExon) to obtain splice site candidates. The HyperExon system outperformed leading splice recognition systems in the list of sequences tested.