Probing the subtropical lowermost stratosphere and the tropical upper troposphere and tropopause layer for inorganic bromine

We report measurements of CH4 (measured in situ by the Harvard University Picarro Cavity Ringdown Spectrometer (HUPCRS) and NOAA Unmanned Aircraft System Chromatograph for Atmospheric Trace Species (UCATS) instruments), O3 (measured in situ by the NOAA dual-beam ultraviolet (UV) photometer), NO2, BrO (remotely detected by spectroscopic UV–visible (UV–vis) limb observations; see the companion paper of Stutz et al., 2016), and of some key brominated source gases in whole-air samples of the Global Hawk Whole Air Sampler (GWAS) instrument within the subtropical lowermost stratosphere (LS) and the tropical upper troposphere (UT) and tropopause layer (TTL). The measurements were performed within the framework of the NASA-ATTREX (National Aeronautics and Space Administration – Airborne Tropical Tropopause Experiment) project from aboard the Global Hawk (GH) during six deployments over the eastern Pacific in early 2013. These measurements are compared with TOMCAT/SLIMCAT (Toulouse Off-line Model of Chemistry And Transport/Single Layer Isentropic Model of Chemistry And Transport) 3-D model simulations, aiming at improvements of our understanding of the bromine budget and photochemistry in the LS, UT, and TTL. Changes in local O3 (and NO2 and BrO) due to transport processes are separated from photochemical processes in intercomparisons of measured and modeled CH4 and O3. After excellent agreement is achieved among measured and simulated CH4 and O3, measured and modeled [NO2] are found to closely agree with  ≤  15 ppt in the TTL (which is the detection limit) and within a typical range of 70 to 170 ppt in the subtropical LS during the daytime. Measured [BrO] ranges between 3 and 9 ppt in the subtropical LS. In the TTL, [BrO] reaches 0.5 ± 0.5 ppt at the bottom (150 hPa∕355 K∕14 km) and up to about 5 ppt at the top (70 hPa∕425 K∕18.5 km; see Fueglistaler et al., 2009 for the definition of the TTL used), in overall good agreement with the model simulations. Depending on the photochemical regime, the TOMCAT∕SLIMCAT simulations tend to slightly underpredict measured BrO for large BrO concentrations, i.e., in the upper TTL and LS. The measured BrO and modeled BrO ∕ Bryinorg ratio is further used to calculate inorganic bromine, Bryinorg. For the TTL (i.e., when [CH4]  ≥  1790 ppb), [Bryinorg] is found to increase from a mean of 2.63 ± 1.04 ppt for potential temperatures (θ) in the range of 350–360 K to 5.11 ± 1.57 ppt for θ  = 390 − 400 K, whereas in the subtropical LS (i.e., when [CH4]  ≤  1790 ppb), it reaches 7.66 ± 2.95 ppt for θ in the range of 390–400 K. Finally, for the eastern Pacific (170–90° W), the TOMCAT/SLIMCAT simulations indicate a net loss of ozone of −0.3 ppbv day−1 at the base of the TTL (θ  =  355 K) and a net production of +1.8 ppbv day−1 in the upper part (θ  =  383 K)

Substrate Profiling of Tobacco Etch Virus Protease Using a Novel Fluorescence-Assisted Whole-Cell Assay

Site-specific proteolysis of proteins plays an important role in many cellular functions and is often key to the virulence of infectious organisms. Efficient methods for characterization of proteases and their substrates will therefore help us understand these fundamental processes and thereby hopefully point towards new therapeutic strategies. Here, a novel whole-cell in vivo method was used to investigate the substrate preference of the sequence specific tobacco etch virus protease (TEVp). The assay, which utilizes protease-mediated intracellular rescue of genetically encoded short-lived fluorescent substrate reporters to enhance the fluorescence of the entire cell, allowed subtle differences in the processing efficiency of closely related substrate peptides to be detected. Quantitative screening of large combinatorial substrate libraries, through flow cytometry analysis and cell sorting, enabled identification of optimal substrates for TEVp. The peptide, ENLYFQG, identical to the protease's natural substrate peptide, emerged as a strong consensus cleavage sequence, and position P3 (tyrosine, Y) and P1 (glutamine, Q) within the substrate peptide were confirmed as being the most important specificity determinants. In position P1′, glycine (G), serine (S), cysteine (C), alanine (A) and arginine (R) were among the most prevalent residues observed, all known to generate functional TEVp substrates and largely in line with other published studies stating that there is a strong preference for short aliphatic residues in this position. Interestingly, given the complex hydrogen-bonding network that the P6 glutamate (E) is engaged in within the substrate-enzyme complex, an unexpectedly relaxed residue preference was revealed for this position, which has not been reported earlier. Thus, in the light of our results, we believe that our assay, besides enabling protease substrate profiling, also may serve as a highly competitive platform for directed evolution of proteases and their substrates

NLRP3 Inflammasome: Key Mediator of Neuroinflammation in Murine Japanese Encephalitis

Background: Japanese Encephalitis virus (JEV) is a common cause of acute and epidemic viral encephalitis. JEV infection is associated with microglial activation resulting in the production of pro-inflammatory cytokines including Interleukin-1 b (IL-1b) and Interleukin-18 (IL-18). The Pattern Recognition Receptors (PRRs) and the underlying mechanism by which microglia identify the viral particle leading to the production of these cytokines is unknown. Methodology/Principal Findings: For our studies, we have used murine model of JEV infection as well as BV-2 mouse microglia cell line. In this study, we have identified a signalling pathway which leads to the activation of caspase-1 as the key enzyme responsible for the maturation of both IL-1b and IL-18 in NACHT, LRR and PYD domains-containing protein-3 (NLRP3) dependent manner. Depletion of NLRP3 results in the reduction of caspase-1 activity and subsequent production of these cytokines. Conclusion/Significance: Our results identify a mechanism mediated by Reactive Oxygen Species (ROS) production and potassium efflux as the two danger signals that link JEV infection to caspase-1 activation resulting in subsequent IL-1b an

Enhancing Chemotherapy Response with Bmi-1 Silencing in Ovarian Cancer

Undoubtedly ovarian cancer is a vexing, incurable disease for patients with recurrent cancer and therapeutic options are limited. Although the polycomb group gene, Bmi-1 that regulates the self-renewal of normal stem and progenitor cells has been implicated in the pathogenesis of many human malignancies, yet a role for Bmi-1 in influencing chemotherapy response has not been addressed before. Here we demonstrate that silencing Bmi-1 reduces intracellular GSH levels and thereby sensitizes chemoresistant ovarian cancer cells to chemotherapeutics such as cisplatin. By exacerbating ROS production in response to cisplatin, Bmi-1 silencing activates the DNA damage response pathway, caspases and cleaves PARP resulting in the induction apoptosis in ovarian cancer cells. In an in vivo orthotopic mouse model of chemoresistant ovarian cancer, knockdown of Bmi-1 by nanoliposomal delivery significantly inhibits tumor growth. While cisplatin monotherapy was inactive, combination of Bmi-1 silencing along with cisplatin almost completely abrogated ovarian tumor growth. Collectively these findings establish Bmi-1 as an important new target for therapy in chemoresistant ovarian cancer

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p