Transcriptome analysis of the central nervous system of the mollusc Lymnaea stagnalis

Background: The freshwater snail Lymnaea stagnalis (L. stagnalis) has served as a successful model for studies in the field of Neuroscience. However, a serious drawback in the molecular analysis of the nervous system of L. stagnalis has been the lack of large-scale genomic or neuronal transcriptome information, thereby limiting the use of this unique model. Results: In this study, we report 7,712 distinct EST sequences (median length: 847 nucleotides) of a normalized L. stagnalis central nervous system (CNS) cDNA library, resulting in the largest collection of L. stagnalis neuronal transcriptome data currently available. Approximately 42% of the cDNAs can be translated into more than 100 consecutive amino acids, indicating the high quality of the library. The annotated sequences contribute 12% of the predicted transcriptome size of 20,000. Surprisingly, approximately 37% of the L. stagnalis sequences only have a tBLASTx hit in the EST library of another snail species Aplysia californica (A. californica) even using a low stringency e-value cutoff at 0.01. Using the same cutoff, approximately 67% of the cDNAs have a BLAST hit in the NCBI non-redundant protein and nucleotide sequence databases (nr and nt), suggesting that one third of the sequences may be unique to L. stagnalis. Finally, using the same cutoff (0.01), more than half of the cDNA sequences (54%) do not have a hit in nematode, fruitfly or human genome data, suggesting that the L. stagnalis transcriptome is significantly different from these species as well. The cDNA sequences are enriched in the following gene ontology functional categories: protein binding, hydrolase, transferase, and catalytic enzymes. Conclusion: This study provides novel molecular insights into the transcriptome of an important molluscan model organism. Our findings will contribute to functional analyses in neurobiology, and comparative evolutionary biology. The L. stagnalis CNS EST database is available at http://www.Lymnaea.org/. © 2009 Feng et al; licensee BioMed Central Ltd

How to achieve synergy between medical education and cognitive neuroscience? An exercise on prior knowledge in understanding

A major challenge in contemporary research is how to connect medical education and cognitive neuroscience and achieve synergy between these domains. Based on this starting point we discuss how this may result in a common language about learning, more educationally focused scientific inquiry, and multidisciplinary research projects. As the topic of prior knowledge in understanding plays a strategic role in both medical education and cognitive neuroscience it is used as a central element in our discussion. A critical condition for the acquisition of new knowledge is the existence of prior knowledge, which can be built in a mental model or schema. Formation of schemas is a central event in student-centered active learning, by which mental models are constructed and reconstructed. These theoretical considerations from cognitive psychology foster scientific discussions that may lead to salient issues and questions for research with cognitive neuroscience. Cognitive neuroscience attempts to understand how knowledge, insight and experience are established in the brain and to clarify their neural correlates. Recently, evidence has been obtained that new information processed by the hippocampus can be consolidated into a stable, neocortical network more rapidly if this new information fits readily into a schema. Opportunities for medical education and medical education research can be created in a fruitful dialogue within an educational multidisciplinary platform. In this synergetic setting many questions can be raised by educational scholars interested in evidence-based education that may be highly relevant for integrative research and the further development of medical education

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Do hypoxia/normoxia culturing conditions change the neuroregulatory profile of Wharton Jelly mesenchymal stem cells secretome?

Introduction: The use of human umbilical cord Wharton Jelly-derived mesenchymal stem cells (hWJ-MSCs) has been considered a new potential source for future safe applications in regenerative medicine. Indeed, the application of hWJ-MSCs into different animal models of disease, including those from the central nervous system, has shown remarkable therapeutic benefits mostly associated with their secretome. Conventionally, hWJ-MSCs are cultured and characterized under normoxic conditions (21 % oxygen tension), although the oxygen levels within tissues are typically much lower (hypoxic) than these standard culture conditions. Therefore, oxygen tension represents an important environmental factor that may affect the performance of mesenchymal stem cells in vivo. However, the impact of hypoxic conditions on distinct mesenchymal stem cell characteristics, such as the secretome, still remains unclear. Methods: In the present study, we have examined the effects of normoxic (21 % O2) and hypoxic (5 % O2) conditions on the hWJ-MSC secretome. Subsequently, we address the impact of the distinct secretome in the neuronal cell survival and differentiation of human neural progenitor cells. Results: The present data indicate that the hWJ-MSC secretome collected from normoxic and hypoxic conditions displayed similar effects in supporting neuronal differentiation of human neural progenitor cells in vitro. However, proteomic analysis revealed that the use of hypoxic preconditioning led to the upregulation of several proteins within the hWJ-MSC secretome. Conclusions: Our results suggest that the optimization of parameters such as hypoxia may lead to the development of strategies that enhance the therapeutic effects of the secretome for future regenerative medicine studies and applications. © 2015 Teixeira et al.Portuguese Foundation for Science and Technology (FCT) (Ciência 2007 program and IF Development Grant (AJS); and pre-doctoral fellowships to FGT (SFRH/69637/ 2010) and SIA (SFRH/BD/81495/2011); Canada Research Chairs (LAB) and a SSE Postdoctoral Fellowship (KMP); The National Mass Spectrometry Network (RNEM) (REDE/1506/REM/2005); co-funded by Programa Operacional Regional do Norte (ON.2 – O Novo Norte), ao abrigo do Quadro de Referência Estratégico Nacional (QREN), através do Fundo Europeu de Desenvolvimento Regional (FEDER).info:eu-repo/semantics/publishedVersio

Genome-Wide Association Analysis of Oxidative Stress Resistance in Drosophila melanogaster

Background: Aerobic organisms are susceptible to damage by reactive oxygen species. Oxidative stress resistance is a quantitative trait with population variation attributable to the interplay between genetic and environmental factors. Drosophila melanogaster provides an ideal system to study the genetics of variation for resistance to oxidative stress. Methods and Findings: We used 167 wild-derived inbred lines of the Drosophila Genetic Reference Panel for a genomewide association study of acute oxidative stress resistance to two oxidizing agents, paraquat and menadione sodium bisulfite. We found significant genetic variation for both stressors. Single nucleotide polymorphisms (SNPs) associated with variation in oxidative stress resistance were often sex-specific and agent-dependent, with a small subset common for both sexes or treatments. Associated SNPs had moderately large effects, with an inverse relationship between effect size and allele frequency. Linear models with up to 12 SNPs explained 67–79 % and 56–66 % of the phenotypic variance for resistance to paraquat and menadione sodium bisulfite, respectively. Many genes implicated were novel with no known role in oxidative stress resistance. Bioinformatics analyses revealed a cellular network comprising DNA metabolism and neuronal development, consistent with targets of oxidative stress-inducing agents. We confirmed associations of seven candidate genes associated with natural variation in oxidative stress resistance through mutational analysis. Conclusions: We identified novel candidate genes associated with variation in resistance to oxidative stress that hav

Identification of Neural Outgrowth Genes using Genome-Wide RNAi

While genetic screens have identified many genes essential for neurite outgrowth, they have been limited in their ability to identify neural genes that also have earlier critical roles in the gastrula, or neural genes for which maternally contributed RNA compensates for gene mutations in the zygote. To address this, we developed methods to screen the Drosophila genome using RNA-interference (RNAi) on primary neural cells and present the results of the first full-genome RNAi screen in neurons. We used live-cell imaging and quantitative image analysis to characterize the morphological phenotypes of fluorescently labelled primary neurons and glia in response to RNAi-mediated gene knockdown. From the full genome screen, we focused our analysis on 104 evolutionarily conserved genes that when downregulated by RNAi, have morphological defects such as reduced axon extension, excessive branching, loss of fasciculation, and blebbing. To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. The algorithms were essential for the analysis of the thousands of images generated by the screening process and will become a valuable tool for future genome-wide screens in primary neurons. Our analysis revealed unexpected, essential roles in neurite outgrowth for genes representing a wide range of functional categories including signalling molecules, enzymes, channels, receptors, and cytoskeletal proteins. We also found that genes known to be involved in protein and vesicle trafficking showed similar RNAi phenotypes. We confirmed phenotypes of the protein trafficking genes Sec61alpha and Ran GTPase using Drosophila embryo and mouse embryonic cerebral cortical neurons, respectively. Collectively, our results showed that RNAi phenotypes in primary neural culture can parallel in vivo phenotypes, and the screening technique can be used to identify many new genes that have important functions in the nervous system