Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Antithrombotic therapy and survival in patients with malignant disease

A broad range of studies suggest a two-way relationship between cancer and venous thromboembolism (VTE). Patients with cancer have consistently been shown to be at elevated risk for VTE; this risk is partly driven by an intrinsic hypercoagulable state elicited by the tumour itself. Conversely, thromboembolic events in patients without obvious risk factors are often the first clinical manifestation of an undiagnosed malignancy. The relationship between VTE and cancer is further supported by a number of trials and meta-analyses which, when taken together, strongly suggest that antithrombotic therapy can extend survival in patients with cancer by a mechanism that extends beyond its effect in preventing VTE. Moreover, accumulating evidence from in vitro and in vivo studies has shown that tumour growth, invasion, and metastasis are governed, in part, by elements of the coagulation system. On 22 May 2009, a group of health-care providers based in the United Kingdom met in London, England, to examine recent advances in cancer-associated thrombosis and its implications for UK clinical practice. As part of the discussion, attendees evaluated evidence for and against an effect of antithrombotic therapy on survival in cancer. This paper includes a summary of the data presented at the meeting and explores potential mechanisms by which antithrombotic agents might exert antitumour effects. The summary is followed by a consensus statement developed by the group

The Resonance Frequency Shift, Pattern Formation, and Dynamical Network Reorganization via Sub-Threshold Input

We describe a novel mechanism that mediates the rapid and selective pattern formation of neuronal network activity in response to changing correlations of sub-threshold level input. The mechanism is based on the classical resonance and experimentally observed phenomena that the resonance frequency of a neuron shifts as a function of membrane depolarization. As the neurons receive varying sub-threshold input, their natural frequency is shifted in and out of its resonance range. In response, the neuron fires a sequence of action potentials, corresponding to the specific values of signal currents, in a highly organized manner. We show that this mechanism provides for the selective activation and phase locking of the cells in the network, underlying input-correlated spatio-temporal pattern formation, and could be the basis for reliable spike-timing dependent plasticity. We compare the selectivity and efficiency of this pattern formation to a supra-threshold network activation and a non-resonating network/neuron model to demonstrate that the resonance mechanism is the most effective. Finally we show that this process might be the basis of the phase precession phenomenon observed during firing of hippocampal place cells, and that it may underlie the active switching of neuronal networks to locking at various frequencies

Omalizumab efficacy in cases of chronic spontaneous urticaria is not explained by the inhibition of sera activity in effector cells

Omalizumab (OmAb) is a humanized anti-IgE antibody approved for the treatment of chronic spontaneous urticaria (CSU). OmAb's mechanism of action is known to include actions on free IgE and on pre-bound IgE. However, OmAb is equally and rapidly effective against autoimmune and non-autoimmune urticaria where IgE involvement is not clear, suggesting the involvement of additional mechanisms of action. In this study, we sought to investigate the ability of OmAb to inhibit mast cell and basophil degranulation induced by sera from CSU patients. For this purpose, we performed a comparison between the in vitro incubation of sera from CSU patients treated with OmAb and the in vivo administration of OmAb in a clinical trial. We found that OmAb added in vitro to sera from CSU patients did not modify the ability of the sera to induce cell degranulation. Similarly, the sera from patients treated with OmAb in the context of the clinical trial who had a good clinical outcome maintained the capacity to activate mast cells and basophils. Thus, we conclude that the beneficial activity of OmAb does not correlate with the ability of patient sera to induce cell degranulation

Information in small neuronal ensemble activity in the hippocampal CA1 during delayed non-matching to sample performance in rats

<p>Abstract</p> <p>Background</p> <p>The matrix-like organization of the hippocampus, with its several inputs and outputs, has given rise to several theories related to hippocampal information processing. Single-cell electrophysiological studies and studies of lesions or genetically altered animals using recognition memory tasks such as delayed non-matching-to-sample (DNMS) tasks support the theories. However, a complete understanding of hippocampal function necessitates knowledge of the encoding of information by multiple neurons in a single trial. The role of neuronal ensembles in the hippocampal CA1 for a DNMS task was assessed quantitatively in this study using multi-neuronal recordings and an artificial neural network classifier as a decoder.</p> <p>Results</p> <p>The activity of small neuronal ensembles (6-18 cells) over brief time intervals (2-50 ms) contains accurate information specifically related to the matching/non-matching of continuously presented stimuli (stimulus comparison). The accuracy of the combination of neurons pooled over all the ensembles was markedly lower than those of the ensembles over all examined time intervals.</p> <p>Conclusion</p> <p>The results show that the spatiotemporal patterns of spiking activity among cells in the small neuronal ensemble contain much information that is specifically useful for the stimulus comparison. Small neuronal networks in the hippocampal CA1 might therefore act as a comparator during recognition memory tasks.</p

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

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT