Oxidative variables and antioxidant enzymes activities in the mdx mouse brain

Dystrophin is a protein found at the plasmatic membrane in muscle and postsynaptic membrane of some neurons, where it plays an important role on synaptic transmission and plasticity. Its absence is associated with Duchenne`s muscular dystrophy (DMD), in which cognitive impairment is found. Oxidative stress appears to be involved in the physiopathology of DMD and its cognitive dysfunction. In this regard, the present study investigated oxidative parameters (lipid and protein peroxidation) and antioxidant enzymes activities (superoxide dismutase and catalase) in prefrontal cortex, cerebellum, hippocampus, striatum and cortex tissues from male dystrophic mdx and normal C57BL10 mice. We observed (I) reduced lipid peroxidation in striatum and protein peroxidation in cerebellum and prefrontal cortex; (2) increased superoxide dismutase activity in cerebellum, prefrontal cortex, hippocampus and striatum: and (3) reduced catalase activity in striatum. It seems by our results, that the superoxide dismutase antioxidant mechanism is playing a protective role against lipid and protein peroxidation in mdx mouse brain. (C) 2009 Elsevier Ltd. All rights reserved.

Serine-like proteolytic enzymes correlated with differential pathogenicity in patients with acute Acanthamoeba keratitis

P>Acute ocular infection due to free-living amoebae of the genus Acanthamoeba is characterized by severe pain, loss of corneal transparency and, eventually, blindness. Proteolytic enzymes secreted by trophozoites of virulent Acanthamoeba strains have an essential role in the mechanisms of pathogenesis, including adhesion, invasion and destruction of the corneal stroma. In this study, we analysed the relationship between the extracellular proteases secreted by clinical isolates of Acanthamoeba and the clinical manifestations and severity of disease that they caused. Clinical isolates were obtained from patients who showed typical symptoms of Acanthamoeba keratitis. Trophozoites were cultivated axenically, and extracellular proteins were collected from cell culture supernatants. Secreted enzymes were partially characterized by gelatin and collagen zymography. Acanthamoeba trophozoites secreted proteases with different molecular masses, proteolysis rates and substrate specificities, mostly serine-like proteases. Different enzymatic patterns of collagenases were observed, varying between single and multiple collagenolytic activities. Low molecular weight serine proteases were secreted by trophozoites associated with worse clinical manifestations. Consequently, proteolytic enzymes of some Acanthamoeba trophozoites could be related to the degree of their virulence and clinical manifestations of disease in the human cornea.

An artificial nanoemulsion carrying paclitaxel decreases the transplant heart vascular disease: A study in a rabbit graft model

Objective: In previous studies cholesterol-rich nanoemulsions (LDE) resembling low-density lipoprotein were shown to concentrate in atherosclerotic lesions of rabbits. Lesions were pronouncedly reduced by treatment with paclitaxel associated with LDE. This study aimed to test the hypothesis of whether LDE-paclitaxel is able to concentrate in grafted hearts of rabbits and to ameliorate coronary allograft vasculopathy after the transplantation procedure. Methods: Twenty-one New Zealand rabbits fed 0.5% cholesterol were submitted to heterotopic heart transplantation at the cervical position. All rabbits undergoing transplantation were treated with cyclosporin A (10 mg . kg(-1) . d(-1) by mouth). Eleven rabbits were treated with LDE-paclitaxel (4 mg/kg body weight paclitaxel per week administered intravenously for 6 weeks), and 10 control rabbits were treated with 3 mL/wk intravenous saline. Four control animals were injected with LDE labeled with [(14)C]-cholesteryl oleate ether to determine tissue uptake. Results: Radioactive LDE uptake by grafts was 4-fold that of native hearts. In both groups the coronary arteries of native hearts showed no stenosis, but treatment with LDE-paclitaxel reduced the degree of stenosis in grafted hearts by 50%. The arterial luminal area in grafts of the treated group was 3-fold larger than in control animals. LDE-paclitaxel treatment resulted in a 7-fold reduction of macrophage infiltration. In grafted hearts LDE-paclitaxel treatment reduced the width of the intimal layer and inhibited the destruction of the medial layer. No toxicity was observed in rabbits receiving LDE-paclitaxel treatment. Conclusions: LDE-paclitaxel improved posttransplantation injury to the grafted heart. The novel therapeutic approach for heart transplantation management validated here is thus a promising strategy to be explored in future clinical studies. (J Thorac Cardiovasc Surg 2011;141:1522-8)

Exercise training enhances rat pancreatic islets anaplerotic enzymes content despite reduced insulin secretion

Endurance exercise has been shown to reduce pancreatic islets glucose-stimulated insulin secretion (GSIS). Anaplerotic/cataplerotic pathways are directly related to GSIS signaling. However, the effect of endurance training upon pancreatic islets anaplerotic enzymes is still unknown. In this sense, we tested the hypothesis that endurance exercise decreases GSIS by reducing anaplerotic/cataplerotic enzymes content. Male Wistar rats were randomly assigned to one of the four experimental groups as follows: control sedentary group (CTL), trained 1 day per week (TRE1x), trained 3 days per week (TRE3x) and trained 5 days per week (TRE5x) and submitted to an 8 weeks endurance-training protocol. After the training protocol, pancreatic islets were isolated and incubated with basal (2.8 mM) and stimulating (16.7 mM) glucose concentrations for GSIS measurement by radioimmunoassay. In addition, pyruvate carboxylase (PYC), pyruvate dehydrogenase (PDH), pyruvate dehydrogenase kinase 4 (PDK4), ATP-citrate lyase (ACL) and glutamate dehydrogenase (GDH) content were quantified by western blotting. Our data showed that 8 weeks of chronic endurance exercise reduced GSIS by 50% in a dose-response manner according to weekly exercise frequency. PYC showed significant twofold increase in TRE3x. PYC enhancement was even higher in TRE5x (p < 0.0001). PDH and PDK4 reached significant 25 and 50% enhancement, respectively compared with CTL. ACL and GDH also reported significant 50 and 75% increase, respectively. The absence of exercise-induced correlations among GSIS and anaplerotic/cataplerotic enzymes suggests that exercise may control insulin release by activating other signaling pathways. The observed anaplerotic and cataplerotic enzymes enhancement might be related to beta-cell surviving rather than insulin secretion.

A Road Following Approach Using Artificial Neural Networks Combinations

Navigation is a broad topic that has been receiving considerable attention from the mobile robotic community over the years. In order to execute autonomous driving in outdoor urban environments it is necessary to identify parts of the terrain that can be traversed and parts that should be avoided. This paper describes an analyses of terrain identification based on different visual information using a MLP artificial neural network and combining responses of many classifiers. Experimental tests using a vehicle and a video camera have been conducted in real scenarios to evaluate the proposed approach.

Ground-state energy of a classical artificial molecule

We study the ground-state energy of a classical artificial molecule formed by two-dimensional clusters (artificial atoms) of N/2 charged particles separated by a distance d. For the small molecules of N = 2 and 4, we obtain analytical expressions for this energy. For the larger ones, we calculate the ground-state energy using molecular dynamics simulation for N up to 128. From our numerical results, we are able to find out a function to approximate the ground-state energy of the molecules covering the range from atoms to molecules for any inter-atom distance d and for particle number from N = 8 to 128 within a difference less than one percent from the MD data.

The Mobility of Chondroitin Sulfate in Articular and Artificial Cartilage Characterized by (13)C Magic-Angle Spinning NMR Spectroscopy

We have studied the molecular dynamics of one of the major macromolecules in articular cartilage, chondroitin sulfate. Applying (13)C high-resolution magic-angle spinning NMR techniques, the NMR signals of all rigid macromolecules in cartilage can be suppressed, allowing the exclusive detection of the highly mobile chondroitin sulfate. The technique is also used to detect the chondroitin sulfate in artificial tissue-engineered cartilage. The tissue-engineered material that is based on matrix producing chondrocytes cultured in a collagen gel should provide properties as close as possible to those of the natural cartilage. Nuclear relaxation times of the chondroitin sulfate were determined for both tissues. Although T(1) relaxation times are rather similar, the T(2) relaxation in tissue-engineered cartilage is significantly shorter. This suggests that the motions of chondroitin sulfate in data:rat and artificial cartilage different. The nuclear relaxation times of chondroitin sulfate in natural and tissue-engineered cartilage were modeled using a broad distribution function for the motional correlation times. Although the description of the microscopic molecular dynamics of the chondroitin sulfate in natural and artificial cartilage required the identical broad distribution functions for the correlation times of motion, significant differences in the correlation times of motion that are extracted from the model indicate that the artificial tissue does not fully meet the standards of the natural ideal. This could also be confirmed by macroscopic biomechanical elasticity measurements. Nevertheless, these results suggest that NMR is a useful tool for the investigation of the quality of artificially engineered tissue. (C) 2010 Wiley Periodicals, Inc. Biopolymers 93: 520-532, 2010.

Micro/nanostructured carbon composite modified with a hybrid redox mediator and enzymes as a glucose biosensor

A carbon micro/nanostructured composite based on cup-stacked carbon nanotubes (CSCNTs) grown onto a carbon felt has been found to be an efficient matrix for enzyme immobilization and chemical signal transduction. The obtained CSCNT/felt was modified with a copper hexacyanoferrate/polypyrrole (CuHCNFe/Ppy) hybrid mediator, and the resulting composite electrode was applied to H(2)O(2) detection, achieving a sensitivity of 194 +/- 15 mu A mmol(-1) L. The results showed that the CSCNT/felt matrix significantly increased the sensitivity of CuHCNFe/Ppy-based sensors compared to those prepared on a felt unrecovered by CSCNTs. Our data revealed that the improved sensitivity of the as-prepared CuHCNFe/Ppy-CSCNT/felt composite electrode can be attributed to the electronic interactions taking place among the CuHCNFe nanocrystals, Ppy layer and CSCNTs. In addition, the presence of CSCNTs also seemed to favor the dispersion of CuHCNFe nanocrystals over the Ppy matrix, even though the CSCNTs were buried under the conducting polymer layer. The CSCNT/felt matrix also enabled the preparation of a glucose biosensor whose sensitivity could be tuned as a function of the number of glucose oxidase (GOx) layers deposited through a Layer-by-Layer technique with an sensitivity of 11 +/- 2 mu A mmol(-1) L achieved at 15 poly(diallyldimethylammoniumchloride)/GOx bilayers. (C) 2011 Elsevier Ltd. All rights reserved.

Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones

Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (similar to 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons. (C) 2008 Elsevier Masson SAS. All rights reserved.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.