The effects of increasing PGE2 on translocation of labeled albumin into rat brain

Under pathophysiological conditions, infiltration of leukocyte plays a key role in the progressionof the neuroinflammatory reaction in the CNS. Prostaglandin E2 (PGE2) is known to accumulate at lesion sites of the post-ischemic brain. Although post-ischemic treatments with cyclooxygenase-2 inhibitors reduce blood-brain barrier (BBB) leukocyte infiltration, the direct effect of PGE2 on BBB has not been fully implemented. Therefore, the direct effect of increasing PGE2 infusion on translocation of labeled albumin into the brain was assessed. Under anesthesia rats were drilled stereo-taxicaly a burr hole in the right forebrain and PGE2 was infused into the forebrain and the hole was occluded. The animals were then injected with fluorescent labeled albumin (FA), via internal right jugular vein and decapitated at different infusion time points. The forebrain was removed and each forebrain hemisphere was homogenized and fluorescence intensities were measured in the supernatant. The fluorescence intensities measured in the right and left forebrain hemispheres of the control group (0.0 µg PGE2) were almost identical. Four hours after infusion of PGE2 at doses higher than 250 µg, fluorescence intensity increased in the right forebrain supernatant, even if it was not statistically significant. The fluorescence intensity was detectable in the brain supernatant 4 h after infusion of PGE2 in doses higher than 250 µg PGE2. The highest fluorescence intensity was 16 h after infusion of 500 µg PGE2, which returned to near control values after 48 h. Increased fluorescence intensity in the brain following PGE2 infusion is concluded to be associated with disruption of the BBB

A Linear Classifier Based on Entity Recognition Tools and a Statistical Approach to Method Extraction in the Protein-Protein Interaction Literature

We participated, in the Article Classification and the Interaction Method subtasks (ACT and IMT, respectively) of the Protein-Protein Interaction task of the BioCreative III Challenge. For the ACT, we pursued an extensive testing of available Named Entity Recognition and dictionary tools, and used the most promising ones to extend our Variable Trigonometric Threshold linear classifier. For the IMT, we experimented with a primarily statistical approach, as opposed to employing a deeper natural language processing strategy. Finally, we also studied the benefits of integrating the method extraction approach that we have used for the IMT into the ACT pipeline. For the ACT, our linear article classifier leads to a ranking and classification performance significantly higher than all the reported submissions. For the IMT, our results are comparable to those of other systems, which took very different approaches. For the ACT, we show that the use of named entity recognition tools leads to a substantial improvement in the ranking and classification of articles relevant to protein-protein interaction. Thus, we show that our substantially expanded linear classifier is a very competitive classifier in this domain. Moreover, this classifier produces interpretable surfaces that can be understood as "rules" for human understanding of the classification. In terms of the IMT task, in contrast to other participants, our approach focused on identifying sentences that are likely to bear evidence for the application of a PPI detection method, rather than on classifying a document as relevant to a method. As BioCreative III did not perform an evaluation of the evidence provided by the system, we have conducted a separate assessment; the evaluators agree that our tool is indeed effective in detecting relevant evidence for PPI detection methods.Comment: BMC Bioinformatics. In Pres

Characterization of Burkholderia cepacia genomovar I as a potential biocontrol agent of Ganoderma boninense in oil palm

Burkholderia is an important bacterial genus containing several species of ecological, biotechnological and pathological interest. Bacterial isolate can be gotten from soil, water, plants and even clinics. With their taxonomy undergoing constant revision and the phenotypic similarity of several species, correct identification of Burkholderia is difficult. Burkholderia cepacia complex (Bcc) consists of nine discrete genomic species and a genetic scheme based on the recA gene has greatly enhanced the identification of B. cepacia complex species. The objectives of this study were to identify Burkholderia strain UPM B3 which was isolated from oil palm roots to the species level based on Biolog® Identification System, and to carry out DNA fingerprinting for strain differentiation as well as differentiate between pathogenic and non-pathogenic human forms. Antagonistic activity of UPM B3 against Ganoderma boninense was alsoevaluated by using dual culture and poison food tests. Genotype characterization was carried out by amplification of the recA gene using specific primers, purified using QIA Quick polymerase chain reaction (PCR) purification kit and sequenced. Multiple sequence alignments were performed on closely related sequence accessions using CLUSTAL W software. Result of nucleotide sequencing followed by phylogenetic analysis of the recA fragments differentiated both putative and known Burkholderiaspecies and all members of the B. cepacia complex. Genomovar analysis confirmed that UPM B3, isolated from oil palm roots belongs to genomovar I and has antagonistic activity against G. boninense based on in vitro dual culture and poison food tests. From the phylogenetic tree, UPM B3 is a specific strain within B. cepacia complex species that belong to genovomar I which is associated with strains nonpathogenic to humans. Thus, B. cepacia strain UPM B3 has the potential to be used against G.boninense, the causal pathogen of basal stem rot (BSR) in oil palm

Construction of Novel Phytochelatins by Overlap Oligonucleotides

Synthetic phytochelatins are protein analogs of phytochelatin with similar heavy metal binding affinities that can be easily produced from a synthetic DNA template. We design synthetic phytochelatin [(Glu-Cys)n Gly] linked to hexahistidine by viral linker peptide and then followed by gene synthesis and cloning of it. Then peptide coding gene (synthetic phytochelatin with linker and hexahistidine) was designed exactly and constructed with step by step methods by overlapping oligonucleotides using T4 DNA Ligase. Finally, synthesized gene amplified by PCR, cloned in pTZ57R/T and transformed to Escherichia coli (DH5α). The results of sequencing show that some types of synthetic phytochelatin (EC4, EC12, and EC20) with linker and hexahistidine were constructed and cloned in vector

A multivariable optimal energy management strategy for standalone DC microgrids

Due to substantial generation and demand fluctuations in standalone green microgrids, energy management strategies are becoming essential for the power sharing and voltage regulation purposes. The classical energy management strategies employ the maximum power point tracking (MPPT) algorithms and rely on batteries in case of possible excess or deficit of energy. However, in order to realize constant current-constant voltage (IU) charging regime and increase the life span of batteries, energy management strategies require being more flexible with the power curtailment feature. In this paper, a coordinated and multivariable energy management strategy is proposed that employs a wind turbine and a photovoltaic array of a standalone DC microgrid as controllable generators by adjusting the pitch angle and the switching duty cycles. The proposed strategy is developed as an online nonlinear model predictive control (NMPC) algorithm. Applying to a sample standalone dc microgrid, the developed controller realizes the IU regime for charging the battery bank. The variable load demands are also shared accurately between generators in proportion to their ratings. Moreover, the DC bus voltage is regulated within a predefined range, as a design parameter