Mechanical ventilation modulates Toll-like receptor-3-induced lung inflammation via a MyD88-dependent, TLR4-independent pathway: a controlled animal study

<p>Abstract</p> <p>Background</p> <p>Mechanical ventilation augments lung inflammation resulting from exposure to microbial products. The objective of this study was to test the hypothesis that ventilator-associated immune modulation requires MyD88-dependent signaling. Because MyD88 is a critical adapter protein utilized for pro-inflammatory signaling by all Toll-like receptors (TLRs), with the exception of TLR3, as well as by the IL-1 and IL-18 receptors, MyD88 dependence would implicate generation of an endogenous soluble ligand recognized by one or more of these receptors during mechanical ventilation and would provide an opportunity for a potential future therapeutic intervention.</p> <p>Methods</p> <p>We compared the effect of mechanical ventilation on lung inflammation and permeability between poly(I:C) exposed mice with or without expression of MyD88. Poly(I:C) is a synthetic ligand for TLR3, the only MyD88-independent TLR, allowing isolation of the effect of MyD88 deletion on ventilator-augmentation of lung inflammation. Lung inflammation was assessed by cytokine concentration in lung tissue homogenate and polymorphonuclear cell (PMN) number in bronchoalveolar lavage fluid (BALF). Lung permeability was assessed by total protein, IgM, and intravenously injected FITC-dextran concentrations in BALF.</p> <p>Results</p> <p>We found that MyD88 was required for mechanical ventilation augmentation of TLR3-induced lung inflammation and permeability. Because TLR4 is the most commonly reported receptor for endogenous ligands generated during tissue injury, we performed a second experiment comparing wildtype and TLR4-/- mice. We found that mechanical ventilation increased TLR3-mediated inflammation and permeability independent of TLR4.</p> <p>Conclusion</p> <p>These data support the hypothesis that mechanical ventilation with moderate tidal volumes generates an endogenous ligand(s) recognized by MyD88-dependent receptor(s) other than TLR4, and that this mechanism can contribute to the development of ventilator-associated lung inflammation and injury. Identification of these ligands and/or receptors could lead to new pharmacological treatments for ARDS.</p

Psychophysiological Sensing and State Classification for Attention Management in Commercial Aviation

Attention-related human performance limiting states (AHPLS) can cause pilots to lose airplane state awareness (ASA), and their detection is important to improving commercial aviation safety. The Commercial Aviation Safety Team found that the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness, and that distraction of various forms was involved in all of them. Research on AHPLS, including channelized attention, diverted attention, startle / surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors has been implemented to simultaneously measure their physiological markers during high fidelity flight simulation human subject studies. Pilot participants were asked to perform benchmark tasks and experimental flight scenarios designed to induce AHPLS. Pattern classification was employed to distinguish the AHPLS induced by the benchmark tasks. Unimodal classification using pre-processed electroencephalography (EEG) signals as input features to extreme gradient boosting, random forest and deep neural network multiclass classifiers was implemented. Multi-modal classification using galvanic skin response (GSR) in addition to the same EEG signals and using the same types of classifiers produced increased accuracy with respect to the unimodal case (90 percent vs. 86 percent), although only via the deep neural network classifier. These initial results are a first step toward the goal of demonstrating simultaneous real time classification of multiple states using multiple sensing modalities in high-fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents

Mechanical ventilation interacts with endotoxemia to induce extrapulmonary organ dysfunction

INTRODUCTION: Multiple organ dysfunction syndrome (MODS) is a common complication of sepsis in mechanically ventilated patients with acute respiratory distress syndrome, but the links between mechanical ventilation and MODS are unclear. Our goal was to determine whether a minimally injurious mechanical ventilation strategy synergizes with low-dose endotoxemia to induce the activation of pro-inflammatory pathways in the lungs and in the systemic circulation, resulting in distal organ dysfunction and/or injury. METHODS: We administered intraperitoneal Escherichia coli lipopolysaccharide (LPS; 1 μg/g) to C57BL/6 mice, and 14 hours later subjected the mice to 6 hours of mechanical ventilation with tidal volumes of 10 ml/kg (LPS + MV). Comparison groups received ventilation but no LPS (MV), LPS but no ventilation (LPS), or neither LPS nor ventilation (phosphate-buffered saline; PBS). RESULTS: Myeloperoxidase activity and the concentrations of the chemokines macrophage inflammatory protein-2 (MIP-2) and KC were significantly increased in the lungs of mice in the LPS + MV group, in comparison with mice in the PBS group. Interestingly, permeability changes across the alveolar epithelium and histological changes suggestive of lung injury were minimal in mice in the LPS + MV group. However, despite the minimal lung injury, the combination of mechanical ventilation and LPS resulted in chemical and histological evidence of liver and kidney injury, and this was associated with increases in the plasma concentrations of KC, MIP-2, IL-6, and TNF-α. CONCLUSION: Non-injurious mechanical ventilation strategies interact with endotoxemia in mice to enhance pro-inflammatory mechanisms in the lungs and promote extra-pulmonary end-organ injury, even in the absence of demonstrable acute lung injury

Feature Extraction and Classification from Planetary Science Datasets enabled by Machine Learning

In this paper we present two examples of recent investigations that we have undertaken, applying Machine Learning (ML) neural networks (NN) to image datasets from outer planet missions to achieve feature recognition. Our first investigation was to recognize ice blocks (also known as rafts, plates, polygons) in the chaos regions of fractured ice on Europa. We used a transfer learning approach, adding and training new layers to an industry-standard Mask R-CNN (Region-based Convolutional Neural Network) to recognize labeled blocks in a training dataset. Subsequently, the updated model was tested against a new dataset, achieving 68% precision. In a different application, we applied the Mask R-CNN to recognize clouds on Titan, again through updated training followed by testing against new data, with a precision of 95% over 369 images. We evaluate the relative successes of our techniques and suggest how training and recognition could be further improved. The new approaches we have used for planetary datasets can further be applied to similar recognition tasks on other planets, including Earth. For imagery of outer planets in particular, the technique holds the possibility of greatly reducing the volume of returned data, via onboard identification of the most interesting image subsets, or by returning only differential data (images where changes have occurred) greatly enhancing the information content of the final data stream

Meeting report : 1st international functional metagenomics workshop May 7–8, 2012, St. Jacobs, Ontario, Canada

This report summarizes the events of the 1st International Functional Metagenomics Workshop. The workshop was held on May 7 and 8 in St. Jacobs, Ontario, Canada and was focused on building a core international functional metagenomics community, exploring strategic research areas, and identifying opportunities for future collaboration and funding. The workshop was initiated by researchers at the University of Waterloo with support from the Ontario Genomics Institute (OGI), Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Waterloo

Measurement of the CP-violating phase \phi s in Bs->J/\psi\pi+\pi- decays

Measurement of the mixing-induced CP-violating phase phi_s in Bs decays is of prime importance in probing new physics. Here 7421 +/- 105 signal events from the dominantly CP-odd final state J/\psi pi+ pi- are selected in 1/fb of pp collision data collected at sqrt{s} = 7 TeV with the LHCb detector. A time-dependent fit to the data yields a value of phi_s=-0.019^{+0.173+0.004}_{-0.174-0.003} rad, consistent with the Standard Model expectation. No evidence of direct CP violation is found.Comment: 15 pages, 10 figures; minor revisions on May 23, 201

Differential branching fraction and angular analysis of the decay B0→K∗0μ+μ−

The angular distribution and differential branching fraction of the decay B 0→ K ∗0 μ + μ − are studied using a data sample, collected by the LHCb experiment in pp collisions at s√=7 TeV, corresponding to an integrated luminosity of 1.0 fb−1. Several angular observables are measured in bins of the dimuon invariant mass squared, q 2. A first measurement of the zero-crossing point of the forward-backward asymmetry of the dimuon system is also presented. The zero-crossing point is measured to be q20=4.9±0.9GeV2/c4 , where the uncertainty is the sum of statistical and systematic uncertainties. The results are consistent with the Standard Model predictions

Opposite-side flavour tagging of B mesons at the LHCb experiment

The calibration and performance of the oppositeside flavour tagging algorithms used for the measurements of time-dependent asymmetries at the LHCb experiment are described. The algorithms have been developed using simulated events and optimized and calibrated with B + →J/ψK +, B0 →J/ψK ∗0 and B0 →D ∗− μ + νμ decay modes with 0.37 fb−1 of data collected in pp collisions at √ s = 7 TeV during the 2011 physics run. The oppositeside tagging power is determined in the B + → J/ψK + channel to be (2.10 ± 0.08 ± 0.24) %, where the first uncertainty is statistical and the second is systematic

Model-independent search for CP violation in D0→K−K+π−π+ and D0→π−π+π+π− decays

A search for CP violation in the phase-space structures of D0 and View the MathML source decays to the final states K−K+π−π+ and π−π+π+π− is presented. The search is carried out with a data set corresponding to an integrated luminosity of 1.0 fb−1 collected in 2011 by the LHCb experiment in pp collisions at a centre-of-mass energy of 7 TeV. For the K−K+π−π+ final state, the four-body phase space is divided into 32 bins, each bin with approximately 1800 decays. The p-value under the hypothesis of no CP violation is 9.1%, and in no bin is a CP asymmetry greater than 6.5% observed. The phase space of the π−π+π+π− final state is partitioned into 128 bins, each bin with approximately 2500 decays. The p-value under the hypothesis of no CP violation is 41%, and in no bin is a CP asymmetry greater than 5.5% observed. All results are consistent with the hypothesis of no CP violation at the current sensitivity

Observation of two new Ξb−\Xi_b^- baryon resonances

Two structures are observed close to the kinematic threshold in the $\Xi_b^0 \pi^-$ mass spectrum in a sample of proton-proton collision data, corresponding to an integrated luminosity of 3.0 fb$^{-1}$ recorded by the LHCb experiment. In the quark model, two baryonic resonances with quark content $bds$ are expected in this mass region: the spin-parity $J^P = \frac{1}{2}^+$ and $J^P=\frac{3}{2}^+$ states, denoted $\Xi_b^{\prime -}$ and $\Xi_b^{*-}$. Interpreting the structures as these resonances, we measure the mass differences and the width of the heavier state to be $m(\Xi_b^{\prime -}) - m(\Xi_b^0) - m(\pi^{-}) = 3.653 \pm 0.018 \pm 0.006$ MeV$/c^2$, $m(\Xi_b^{*-}) - m(\Xi_b^0) - m(\pi^{-}) = 23.96 \pm 0.12 \pm 0.06$ MeV$/c^2$, $\Gamma(\Xi_b^{*-}) = 1.65 \pm 0.31 \pm 0.10$ MeV, where the first and second uncertainties are statistical and systematic, respectively. The width of the lighter state is consistent with zero, and we place an upper limit of $\Gamma(\Xi_b^{\prime -}) < 0.08$ MeV at 95% confidence level. Relative production rates of these states are also reported.Comment: 17 pages, 2 figure