Patterning in time and space: HoxB cluster gene expression in the developing chick embryo

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space.Fundacao para a Ciencia e a Tecnologia (FCT), Portugal [PTDC/SAU-OBD/105111/2008, UMINHO/BI/7/2014, SFRH/BPD/65652/2009]; Ciencia Program Contract; Programa Operacional Regional do Norte (ON. 2) [NORTE-07-0124-FEDER-000017]; FCT (National and FEDER COMPETE Program) [PTDC/SAU-BID/121459/2010, PTDC/SAU-OBD/099758/2008]; [PEst-OE/EQB/LA0023/2011]info:eu-repo/semantics/publishedVersio

Phenolic compounds and antimicrobial activity of olive (Olea europaea L. Cv. Cobrancosa) leaves.

We report the determination of phenolic compounds in olive leaves by reversedphase HPLC/DAD, and the evaluation of their in vitro activity against several microorganisms that may be causal agents of human intestinal and respiratory tract infections, namely Gram positive (Bacillus cereus, B. subtilis and Staphylococcus aureus), Gram negative bacteria (Pseudomonas aeruginosa, Escherichia coli and Klebsiella pneumoniae) and fungi (Candida albicans and Cryptococcus neoformans). Seven phenolic compounds were identified and quantified: caffeic acid, verbascoside, oleuropein, luteolin 7-O-glucoside, rutin, apigenin 7-O-glucoside and luteolin 4’-O-glucoside. At low concentrations olive leafs extracts showed an unusual combined antibacterial and antifungal action, which suggest their great potential as nutraceuticals, particulalry as a source of phenolic compounds

Development of an automatic identification algorithm for antibiogram analysis

Routinely, diagnostic and microbiology laboratories perform antibiogram analysis which can present some difficulties leading to misreadings and intra and inter-reader deviations. An Automatic Identification Algorithm (AIA) has been proposed as a solution to overcome some issues associated with the disc diffusion method, which is the main goal of this work. AIA allows automatic scanning of inhibition zones obtained by antibiograms. More than 60 environmental isolates were tested using susceptibility tests which were performed for 12 different antibiotics for a total of 756 readings. Plate images were acquired and classified as standard or oddity. The inhibition zones were measured using the AIA and results were compared with reference method (human reading), using weighted kappa index and statistical analysis to evaluate, respectively, inter-reader agreement and correlation between AIA-based and human-based reading. Agreements were observed in 88% cases and 89% of the tests showed no difference or a o4 mm difference between AIA and human analysis, exhibiting a correlation index of 0.85 for all images, 0.90 for standards and 0.80 for oddities with no significant difference between automatic and manual method. AIA resolved some reading problems such as overlapping inhibition zones, imperfect microorganism seeding, non-homogeneity of the circumference, partial action of the antimicrobial, and formation of a second halo of inhibition. Furthermore, AIA proved to overcome some of the limitations observed in other automatic methods. Therefore, AIA may be a practical tool for automated reading of antibiograms in diagnostic and microbiology laboratoriesinfo:eu-repo/semantics/acceptedVersio

Secondary metabolites of Pseudomonas aeruginosa lv strain decrease asian soybean rust severity in experimentally infected plants.

Asian Soybean Rust (ASR), a disease caused by Phakopsora pachyrhizi, causing yield losses up to 90%. The control is based on the fungicides which may generate resistant fungi. The activation of the plant defense system, should help on ASR control. In this study, secondary metabolites of Pseudomonas aeruginosa LV strain were applied on spore germination and the expression of defense genes in infected soybean plants. The F4A fraction and the pure metabolites were used. In vitro, 10 µg mL−1 of F4A reduced spore germination by 54%, while 100 µg mL−1 completely inhibited. Overexpression of phenylalanine ammonia lyase (PAL), O-methyltransferase (OMT) and pathogenesis related protein-2 (PR-2; glucanases) defense-related genes were detected 24 and 72 h after soybean sprouts were sprayed with an organocopper antimicrobial compound (OAC). Under greenhouse conditions, the best control was observed in plants treated with 60 µg mL−1 of PCA, which reduced ASR severity and lesion frequency by 75% and 43%, respectively. Plants sprayed with 2 and 20 µg mL−1 of F4A also decreased severity (41%) and lesion frequency (32%). The significant reduction in spore germination ASR in plant suggested that the strain of these metabolites are effective against P. pachyrhizi, and they can be used for ASR control

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p