Influence of elastase on alanine-rich peptide hydrogels

The self-assembly of the alanine-rich amphiphilic peptides Lys(Ala)6Lys (KA6K) and Lys(Ala)6Glu (KA6E)with homotelechelic or heterotelechelic charged termini respectively has been investigated in aqueous solution. These peptides contain hexa-alanine sequences designed to serve as substrates for the enzyme elastase. Electrostatic repulsion of the lysine termini in KA6K prevents self-assembly, whereas in contrast KA6E is observed, through electron microscopy, to form tape-like fibrils, which based on X-ray scattering contain layers of thickness equal to the molecular length. The alanine residues enable efficient packing of the side-chains in a beta-sheet structure, as revealed by circular dichroism, FTIR and X-ray diffraction experiments. In buffer, KA6E is able to form hydrogels at sufficiently high concentration. These were used as substrates for elastase, and enzyme-induced de-gelation was observed due to the disruption of the beta-sheet fibrillar network. We propose that hydrogels of the simple designed amphiphilic peptide KA6E may serve as model substrates for elastase and this could ultimately lead to applications in biomedicine and regenerative medicine.

Self-assembling amphiphilic peptides

The self-assembly of several classes of amphiphilic peptides is reviewed, and selected applications are discussed. We discuss recent work on the self-assembly of lipopeptides, surfactant-like peptides and amyloid peptides derived from the amyloid-β peptide. The influence of environmental variables such as pH and temperature on aggregate nanostructure is discussed. Enzyme-induced remodelling due to peptide cleavage and nanostructure control through photocleavage or photo-cross-linking are also considered. Lastly, selected applications of amphiphilic peptides in biomedicine and materials science are outlined.

Complex extreme learning machine applications in terahertz pulsed signals feature sets

This paper presents a novel approach to the automatic classification of very large data sets composed of terahertz pulse transient signals, highlighting their potential use in biochemical, biomedical, pharmaceutical and security applications. Two different types of THz spectra are considered in the classification process. Firstly a binary classification study of poly-A and poly-C ribonucleic acid samples is performed. This is then contrasted with a difficult multi-class classification problem of spectra from six different powder samples that although have fairly indistinguishable features in the optical spectrum, they also possess a few discernable spectral features in the terahertz part of the spectrum. Classification is performed using a complex-valued extreme learning machine algorithm that takes into account features in both the amplitude as well as the phase of the recorded spectra. Classification speed and accuracy are contrasted with that achieved using a support vector machine classifier. The study systematically compares the classifier performance achieved after adopting different Gaussian kernels when separating amplitude and phase signatures. The two signatures are presented as feature vectors for both training and testing purposes. The study confirms the utility of complex-valued extreme learning machine algorithms for classification of the very large data sets generated with current terahertz imaging spectrometers. The classifier can take into consideration heterogeneous layers within an object as would be required within a tomographic setting and is sufficiently robust to detect patterns hidden inside noisy terahertz data sets. The proposed study opens up the opportunity for the establishment of complex-valued extreme learning machine algorithms as new chemometric tools that will assist the wider proliferation of terahertz sensing technology for chemical sensing, quality control, security screening and clinic diagnosis. Furthermore, the proposed algorithm should also be very useful in other applications requiring the classification of very large datasets.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Effect of doxorubicin on cytokine production by lymphocytes and the Th1/Th2 balance

Doxorubicin (DOXO) is a potent chemotherapeutic used mainly against solid tumours; however, it has several side effects that can limit its clinical use. On the other hand, the effect of DOXO upon lymphocyte function is controversial. Some studies demonstrate that DOXO administration in vitro suppresses T-cell activation, while the cellular function has been shown to increase in vitro. The objective of this study was to investigate the effect of DOXO on lymphocyte cytokine production in rats. The animals were divided into: SAL (control, n = 10) and DOX (DOXO treated, n = 10). The DOX group received only one DOXO dose at 15 kg Kg(-1) by intraperitoneal injection. Forty-eight hours after DOXO administration, the animals were killed by decapitation. IL-2 production was significantly enhanced (p < 0.05) in lymphocytes from rats treated with DOXO (169.17 +/- 21.73 pg mL 10(5) cell) as compared to cells from SAL (45.92 +/- 10.53 pg mL 10(5) cell). The administration of DOXO decreased (<0.05) IL-4 production in the DOXO group (29.85 +/- 13.09 pg mL 10(5) cell) relative to the SAL group (75.08 +/- 15.31 pg mL 10(5) cell). The IL-2/IL-4 ratio was higher (<0.05) in the DOX group (5.99 +/- 0.44), as compared to SAL group (0.73 +/- 0.12). In conclusion, our results suggest that a dose of DOXO promotes an alteration in the Th1/Th2 balance, promoting a shift towards a Th1-dominant cytokine response. (C) 2010 Elsevier Masson SAS. All rights reserved.

Inhibitory activity of limonene against Leishmania parasites in vitro and in vivo

Limonene is a monoterpene that has antitumoral, antibiotic and antiprotozoal activity. In this study we demonstrate the activity of limonene against Leishmania species in vitro and in vivo. Limonene killed Leishmania amazonensis promastigotes and amastigotes with 50% inhibitory concentrations of 252.0 +/- 49.0 and 147.0 +/- 46.0 mu M, respectively. Limonene was also effective against Leishmania major, Leishmania braziliensis and Leishmania chagasi promastigotes. The treatment of L. amazonensis-infected macrophages with 300 mu M limonene resulted in 78% reduction in infection rates. L. amazonensis-infected mice treated topically or intrarectally with limonene had significant reduction of lesion sizes. A significant decrease in the parasite load was shown in the lesions treated topically with limonene by histopathological examination. The intrarectal treatment was highly effective in decreasing the parasite burden, healing established lesions and suppressing the dissemination of ulcers. Limonene presents low toxicity in humans and has been shown to be effective as an agent for enhancing the percutaneous permeation of drugs. Our results suggest that limonene should be tested in different experimental models of infection by Leishmania. (C) 2009 Elsevier Masson SAS. All rights reserved.

A hands-on approach for fitting long-term survival models under the GAMLSS framework

In many data sets from clinical studies there are patients insusceptible to the occurrence of the event of interest. Survival models which ignore this fact are generally inadequate. The main goal of this paper is to describe an application of the generalized additive models for location, scale, and shape (GAMLSS) framework to the fitting of long-term survival models. in this work the number of competing causes of the event of interest follows the negative binomial distribution. In this way, some well known models found in the literature are characterized as particular cases of our proposal. The model is conveniently parameterized in terms of the cured fraction, which is then linked to covariates. We explore the use of the gamlss package in R as a powerful tool for inference in long-term survival models. The procedure is illustrated with a numerical example. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Identification of a novel ligand binding motif in the transthyretin channel

The design of therapeutic compounds targeting transthyretin (TTR) is challenging due to the low specificity of interaction in the hormone binding site. Such feature is highlighted by the interactions of TTR with diclofenac, a compound with high affinity for TTR, in two dissimilar modes, as evidenced by crystal structure of the complex. We report here structural analysis of the interactions of TTR with two small molecules, 1-amino-5-naphthalene sulfonate (1,5-AmNS) and 1-anilino-8-naphthalene sulfonate (1,8-ANS). Crystal structure of TTR: 1,8-ANS complex reveals a peculiar interaction, through the stacking of the naphthalene ring between the side-chain of Lys15 and Leu17. The sulfonate moiety provides additional interaction with Lys15` and a water-mediated hydrogen bond with Thr119`. The uniqueness of this mode of ligand recognition is corroborated by the crystal structure of TTR in complex with the weak analogue 1,5-AmNS, the binding of which is driven mainly by hydrophobic partition and one electrostatic interaction between the sulfonate group and the Lys15. The ligand binding motif unraveled by 1,8-ANS may open new possibilities to treat TTR amyloid diseases by the elucidation of novel candidates for a more specific pharmacophoric pattern. (C) 2009 Published by Elsevier Ltd.

THE EXTENT OF MULTIDISCIPLINARY AUTHORSHIP OF ARTICLES ON SCIENTOMETRICS AND BIBLIOMETRICS IN BRAZIL

The publications in scientometrics and bibliometrics with Brazilian authorship expanded exponentially in the 1990-2006 period, reaching 13 times in the Web of Science database and 19.5 times in the Google Scholar database. This increase is rather superior to that of the total Brazilian scientific production in the same time period (5.6 times in the Web of Science). Some characteristics to be noticed in this rise are: 1) The total number of articles during this period was 197; in that, 78% were published in 57 Brazilian journals and 22% in 13 international journals. 2) The national and international articles averaged 4.3 and 5.9 citations/article, respectively; two journals stood out among these, the national Ciencia da Informacao (44 articles averaging 6.7 citations/article) and the international Scientometrics (32 articles averaging 6.2 citations/article). 3) The articles encompass an impressive participation of authors from areas other than information science; only one-fourth of the authors are bound to the information science field, the remaining ones being distributed among the areas of humanities/business administration, biology/biomedicine, health and hard sciences. The occurrence of adventitious authors at this level of multidisciplinarity is uncommon in science. However, the possible benefits of such patterns are not clear in view of a fragmented intercommunication among the authors, as noticed through the citations. The advantages of changing this trend and of using other scientometric and bibliometric databases, such as SciELO, to avoid an almost exclusive use of the Web of Science database, are discussed.

Surface active ionic liquids: Study of the micellar properties of 1-(1-alkyl)-3-methylimidazolium chlorides and comparison with structurally related surfactants

The impetus for the increasing interest in studying surface active ionic liquids (SAILs; ionic liquids with long-chain ""tails"") is the enormous potential for their applications, e.g., in nanotechnology and biomedicine. The progress in these fields rests on understanding the relationship between surfactant structure and solution properties, hence applications. This need has prompted us to extend our previous study on 1-(1-hexadecyl)-3-methylimidazolium chloride to 1-(1-alkyl)-3-methylimidazolium chlorides, with alkyl chains containing 10, 12, and 14 carbons. In addition to investigating relevant micellar properties, we have compared the solution properties of the imidazolium-based surfactants with: 1-(1-alkyl)pyridinium chlorides, and benzyl (2-acylaminoethyl)dimethylammonium chlorides. The former series carries a heterocyclic ring head-group, but does not possess a hydrogen that is as acidic as H2 of the imidazolium ring. The latter series carries an aromatic ring, a quaternary nitrogen and (a hydrogen-bond forming) amide group. The properties of the imidazolium and pyridinium surfactants were determined in the temperature range from 15 to 75 degrees C. The techniques employed were conductivity, isothermal titration calorimetry, and static light scattering. The results showed the important effects of the interactions in the interfacial region on the micellar properties over the temperature range studied. (C) 2011 Elsevier Inc. All rights reserved.