The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio

A unified model for BAM function that takes into account type Vc secretion and species differences in BAM composition

Transmembrane proteins in the outer membrane of Gram-negative bacteria are almost exclusively β-barrels. They are inserted into the outer membrane by a conserved and essential protein complex called the BAM (for β-barrel assembly machinery). In this commentary, we summarize current research into the mechanism of this protein complex and how it relates to type V secretion. Type V secretion systems are autotransporters that all contain a β-barrel transmembrane domain inserted by BAM. In type Vc systems, this domain is a homotrimer. We argue that none of the current models are sufficient to explain BAM function particularly regarding type Vc secretion. We also find that current models based on the well-studied model system Escherichia coli mostly ignore the pronounced differences in BAM composition between different bacterial species. We propose a more holistic view on how all OMPs, including autotransporters, are incorporated into the lipid bilayer

Perspectives on the use of transcriptomics to advance biofuels

As a field within the energy research sector, bioenergy is continuously expanding. Although much has been achieved and the yields of both ethanol and butanol have been improved, many avenues of research to further increase these yields still remain. This review covers current research related with transcriptomics and the application of this high-throughput analytical tool to engineer both microbes and plants with the penultimate goal being better biofuel production and yields. The initial focus is given to the responses of fermentative microbes during the fermentative production of acids, such as butyric acid, and solvents, including ethanol and butanol. As plants offer the greatest natural renewable source of fermentable sugars within the form of lignocellulose, the second focus area is the transcriptional responses of microbes when exposed to plant hydrolysates and lignin-related compounds. This is of particular importance as the acid/base hydrolysis methods commonly employed to make the plant-based cellulose available for enzymatic hydrolysis to sugars also generates significant amounts of lignin-derivatives that are inhibitory to fermentative bacteria and microbes. The article then transitions to transcriptional analyses of lignin-degrading organisms, such as Phanerochaete chrysosporium, as an alternative to acid/base hydrolysis. The final portion of this article will discuss recent transcriptome analyses of plants and, in particular, the genes involved in lignin production. The rationale behind these studies is to eventually reduce the lignin content present within these plants and, consequently, the amount of inhibitors generated during the acid/base hydrolysis of the lignocelluloses. All four of these topics represent key areas where transcriptomic research is currently being conducted to identify microbial genes and their responses to products and inhibitors as well as those related with lignin degradation/formation.clos

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us

Supernova remnants (SNRs) arise from the interaction between the ejecta of a supernova (SN) explosion and the surrounding circumstellar and interstellar medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However, to understand SNRs as a whole, large samples of SNRs must be assembled and studied. Here, we describe the radio, optical, and X-ray techniques which have been used to identify and characterize almost 300 Galactic SNRs and more than 1200 extragalactic SNRs. We then discuss which types of SNRs are being found and which are not. We examine the degree to which the luminosity functions, surface-brightness distributions and multi-wavelength comparisons of the samples can be interpreted to determine the class properties of SNRs and describe efforts to establish the type of SN explosion associated with a SNR. We conclude that in order to better understand the class properties of SNRs, it is more important to study (and obtain additional data on) the SNRs in galaxies with extant samples at multiple wavelength bands than it is to obtain samples of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin. Final version available at https://doi.org/10.1007/978-3-319-20794-0_90-

Respiratory viral pathogens among Singapore military servicemen 2009 - 2012: Epidemiology and clinical characteristics

10.1186/1471-2334-14-204BMC Infectious Diseases141-BIDM

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

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