Distribution of mosquitoes in the South East of Argentina and first report on the analysis based on 18S rDNA and COI sequences

Although Mar del Plata is the most important city on the Atlantic coast of Argentina, mosquitoes inhabiting such area are almost uncharacterized. To increase our knowledge in their distribution, we sampled specimens of natural populations. After the morphological identification based on taxonomic keys, sequences of DNA from small ribosomal subunit (18S rDNA) and cytochrome c oxidase I (COI) genes were obtained from native species and the phylogenetic analysis of these sequences were done. Fourteen species from the genera Uranotaenia, Culex, Ochlerotatus and Psorophora were found and identified. Our 18S rDNA and COI-based analysis indicates the relationships among groups at the supra-species level in concordance with mosquito taxonomy. The introduction and spread of vectors and diseases carried by them are not known in Mar del Plata, but some of the species found in this study were reported as pathogen vectors

Protein disulphide isomerase-assisted functionalization of proteinaceous substrates

Protein disulphide isomerase (PDI) is an enzyme that catalyzes thiol-disulphide exchange reactions among a broad spectrum of substrates, including proteins and low-molecular thiols and disulphides. As the first protein-folding catalyst reported, the study of PDI has mainly involved the correct folding of several cysteine-containing proteins. Its application on the functionalization of protein-based materials has not been extensively reported. Herein, we review the applications of PDI on the modification of proteinaceous substrates and discuss its future potential. The mechanism involved in PDI functionalization of fibrous protein substrates is discussed in detail. These approaches allow innovative applications in textile dyeing and finishing, medical textiles, controlled drug delivery systems and hair or skin care products.We thank to FCT 'Fundacao para a Ciencia e Tecnologia' (scholarship SFRH/BD/38363/2007) for providing Margarida Fernandes the grant for PhD studies

Wound dressings for a proteolytic-rich environment

Wound dressings have experienced continuous and significant changes over the years based on the knowledge of the biochemical events associated with chronic wounds. The development goes from natural materials used to just cover and conceal the wound to interactive materials that can facilitate the healing process, addressing specific issues in non-healing wounds. These new types of dressings often relate with the proteolytic wound environment and the bacteria load to enhance the healing. Recently, the wound dressing research is focusing on the replacement of synthetic polymers by natural protein materials to delivery bioactive agents to the wounds. This article provides an overview on the novel protein-based wound dressings such as silk fibroin keratin and elastin. The improved properties of these dressings, like the release of antibiotics and growth factors, are discussed. The different types of wounds and the effective parameters of healing process will be reviewed

Evaluation of decomposition kinetics of poly (ether-ether-ketone) by thermogravimetric analysis

The non-isothermal thermogravimetric methods have been used extensively for the determination of kinetic parameters in polymers. The poly (ether ketones) are used as matrix in advanced high performance composites due its high thermal stability, excellent environmental performance and superior mechanical properties. In this work, the non-isothermal decomposition kinetics of the polymer poly (ether ether ketone) (PEEK) was evaluated in nitrogen and synthetic air atmospheres, using the Flynn-Wall-Ozawa and Coats Redfern models. The results showed that the necessary time for the material decomposes in 5% is approximately 216 years if it is submitted to temperatures of 350 degrees C in nitrogen atmosphere. On the other hand, if the material is submitted to air atmosphere, this decomposition time drops to about 1,05 years in the same temperature and for the same conversion rate. The decomposition kinetics study by Coats Redfern showed that the D3 mechanism (three-dimensional diffusion (Jander equation)) had better adjustment to the decomposition kinetics of the material in nitrogen atmosphere, while in synthetic air the R1 mechanism (phase boundary controlled reaction (one-dimensional movement)) has better adjustment to the decomposition kinetics of the material.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)UNESP, Univ Estadual Paulista, Fac Engn Guaratingueta, Dept Mat & Tecnol, Guaratingueta, SP, BrazilIAE, DCTA, Div Mat, Sao Jose Dos Campos, SP, BrazilUNESP, Univ Estadual Paulista, Fac Engn Guaratingueta, Dept Mat & Tecnol, Guaratingueta, SP, Brazi

Fixed-time artificial insemination in beef cattle

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: The study was designed to test the effect of fixed-time artificial insemination (fixed-AI) after the slightly modified Ovsynch protocol on the pregnancy rate in beef cattle in Finnish field conditions. The modification was aimed to optimize the number of offsprings per AI dose. Methods: Ninety Charolais cows and heifers were entered into the program an average of 1.8 times. Thus, 164 animal cases were included. Animals were administered 10-12 μg of buserelin. Seven days later animals without a corpus luteum (CL) were rejected (20.7%) while the remaining 130 cases with a CL were administered prostaglandin F2α, followed 48 h later with a second injection of buserelin (8-10 μg). Fixed-AI was performed 16-20 hours after the last injection. Results: The pregnancy rate was 51.5 % (67/130). The pregnancy rate after a short interval (50-70 d) from calving to entering the program was significantly higher than that after a long interval (>70 d). Conclusion: This protocol seems to give acceptable pregnancy results in beef herds and its effect on saving labour is notable

Lung Epithelial Injury by B. Anthracis Lethal Toxin Is Caused by MKK-Dependent Loss of Cytoskeletal Integrity

Bacillus anthracis lethal toxin (LT) is a key virulence factor of anthrax and contributes significantly to the in vivo pathology. The enzymatically active component is a Zn2+-dependent metalloprotease that cleaves most isoforms of mitogen-activated protein kinase kinases (MKKs). Using ex vivo differentiated human lung epithelium we report that LT destroys lung epithelial barrier function and wound healing responses by immobilizing the actin and microtubule network. Long-term exposure to the toxin generated a unique cellular phenotype characterized by increased actin filament assembly, microtubule stabilization, and changes in junction complexes and focal adhesions. LT-exposed cells displayed randomly oriented, highly dynamic protrusions, polarization defects and impaired cell migration. Reconstitution of MAPK pathways revealed that this LT-induced phenotype was primarily dependent on the coordinated loss of MKK1 and MKK2 signaling. Thus, MKKs control fundamental aspects of cytoskeletal dynamics and cell motility. Even though LT disabled repair mechanisms, agents such as keratinocyte growth factor or dexamethasone improved epithelial barrier integrity by reducing cell death. These results suggest that co-administration of anti-cytotoxic drugs may be of benefit when treating inhalational anthrax

A new method for class prediction based on signed-rank algorithms applied to Affymetrix® microarray experiments

<p>Abstract</p> <p>Background</p> <p>The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix^®technology provides both a quantitative fluorescence signal and a decision (<it>detection call</it>: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients.</p> <p>Results</p> <p>After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM).</p> <p>Conclusion</p> <p>This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks particularly promising through international cooperative projects like the "Microarray Quality Control project of US FDA" MAQC as a predictive classifier for diagnostic, prognostic and response to treatment. Finally, it can be used as a powerful tool to mine published data generated on Affymetrix systems and more generally classify samples with binary feature values.</p