Teste preliminar, in vitro, de microrganismos endofíticos para o controle de Cylindrocladium candelabrum e Botrytis cinerea.

Resumo

Genome-Wide SNP-genotyping array to study the evolution of the human pathogen Vibrio vulnificus Biotype 3

Vibrio vulnificus is an aquatic bacterium and an important human pathogen. Strains Of V. vulnificus are classified into three different biotypes. The newly emerged biotype 3 has been found to be clonal and restricted to Israel. In the family Vibrionaceae , horizontal gene transfer is the main mechanism responsible for the emergence of new pathogen groups. To better understand the evolution of the bacterium, and in particular to trace the evolution of biotype 3, we performed genome-wide SNP genotyping of 254 clinical and environmental V. vulnificus isolates with worldwide distribution recovered over a 30-year period, representing all phylogeny groups. A custom single-nucleotide polymorphism (SNP) array implemented on the Illumina GoldenGate platform was developed based on 570 SNPs randomly distributed throughout the genome. In general, the genotyping results divided the V. vulnificus species into three main phylogenetic lineages and an additional subgroup, clade B, consisting of environmental and clinical isolates from Israel. Data analysis suggested that 69% of biotype 3 SNPs are similar to SNPs from clade B, indicating that biotype 3 and clade B have a common ancestor. The rest of the biotype 3 SNPs were scattered along the biotype 3 genome, probably representing multiple chromosomal segments that may have been horizontally inserted into the clade B recipient core genome from other phylogroups or bacterial species sharing the same ecological niche. Results emphasize the continuous evolution of V. vulnificus and support the emergence of new pathogenic groups within this species as a recurrent phenomenon. Our findings contribute to a broader understanding of the evolution of this human pathogen

A Molecular Study on the Prevalence and Virulence Potential of Aeromonas spp. Recovered from Patients Suffering from Diarrhea in Israel

Background: Species of the genus Aeromonas are native inhabitants of aquatic environments and have recently been considered emerging human pathogens. Although the gastrointestinal tract is by far the most common anatomic site from which aeromonads are recovered, their role as etiologic agents of bacterial diarrhea is still disputed. Aeromonas-associated diarrhea is a phenomenon occurring worldwide; however, the exact prevalence of Aeromonas infections on a global scale is unknown. Methodology/Principal Findings: The prevalence and virulence potential of Aeromonas in patients suffering from diarrhea in Israel was studied using molecular methods. 1,033 diarrheal stools were sampled between April and September 2010 and Aeromonas species were identified in 17 (,2%) patients by sequencing the rpoD gene. Aeromonas species identity and abundance was: A. caviae (65%), A. veronii (29%) and Aeromonas taiwanensis (6%). This is the first clinical record of A. taiwanensis as a diarrheal causative since its recent discovery from a wound infection in a patient in Taiwan. Most of the patients (77%) from which Aeromonas species were isolated were negative for any other pathogens. The patients ranged from 1 to 92 years in age. Aeromonas isolates were found to possess different virulence-associated genes: ahpB (88%), pla/ lip/lipH3/apl-1 (71%), act/hlyA/aerA (35%), alt (18%), ast (6%), fla (65%), lafA (41%), TTSS ascV (12%), TTSS ascF-ascG (12%), TTSS-dependent ADP-ribosylating toxins aexU (41%) and aexT (6%) in various combinations. Most of the identified strain

Analysis of equations of state for polymers

AbstractIn the literature there are several studies comparing the accuracy of various models in describing the PvT behavior of polymers. However, most of these studies do not provide information about the quality of the estimated parameters or the sensitivity of the prediction of thermodynamic properties to the parameters of the equations. Furthermore, there are few studies exploring the prediction of thermal expansion and compression coefficients. Based on these observations, the objective of this study is to deepen the analysis of Tait, HH (Hartmann-Haque), MCM (modified cell model) and SHT (simplified hole theory) equations of state in predicting the PvT behavior of polymers, for both molten and solid states. The results showed that all equations of state provide an adequate description of the PvT behavior in the molten state, with low standard deviations in the estimation of parameters, adequate sensitivity of their parameters and plausible prediction of specific volume, thermal expansion and isothermal compression coefficients. In the solid state the Tait equation exhibited similar performance to the molten state, while HH showed satisfactory results for amorphous polymers and difficulty in adjusting the PvT curve for semicrystalline polymers.</p

Profiles of Volatile Biomarkers Detect Tuberculosis from Skin

Tuberculosis (TB) is an infectious disease that threatens >10 million people annually. Despite advances in TB diagnostics, patients continue to receive an insufficient diagnosis as TB symptoms are not specific. Many existing biodiagnostic tests are slow, have low clinical performance, and can be unsuitable for resource-limited settings. According to the World Health Organization (WHO), a rapid, sputum-free, and cost-effective triage test for real-time detection of TB is urgently needed. This article reports on a new diagnostic pathway enabling a noninvasive, fast, and highly accurate way of detecting TB. The approach relies on TB-specific volatile organic compounds (VOCs) that are detected and quantified from the skin headspace. A specifically designed nanomaterial-based sensors array translates these findings into a point-of-care diagnosis by discriminating between active pulmonary TB patients and controls with sensitivity above 90%. This fulfills the WHO's triage test requirements and poses the potential to become a TB triage test

A Novel Medical E-Nose Signal Analysis System

It has been proven that certain biomarkers in people’s breath have a relationship with diseases and blood glucose levels (BGLs). As a result, it is possible to detect diseases and predict BGLs by analysis of breath samples captured by e-noses. In this paper, a novel optimized medical e-nose system specified for disease diagnosis and BGL prediction is proposed. A large-scale breath dataset has been collected using the proposed system. Experiments have been organized on the collected dataset and the experimental results have shown that the proposed system can well solve the problems of existing systems. The methods have effectively improved the classification accuracy