Rapid induction of autoantibodies during ARDS and septic shock

<p>Abstract</p> <p>Background</p> <p>Little is known about the induction of humoral responses directed against human autoantigens during acute inflammation. We utilized a highly sensitive antibody profiling technology to study autoantibodies in patients with acute respiratory distress syndrome (ARDS) and severe sepsis, conditions characterized by intensive immune activation leading to multiple organ dysfunction.</p> <p>Methods</p> <p>Using Luciferase Immunoprecipitation Systems (LIPS), a cohort of control, ARDS and sepsis patients were tested for antibodies to a panel of autoantigens. Autoantibody titers greater than the mean plus 3 SD of the 24 control samples were used to identify seropositive samples. Available longitudinal samples from different seropositive ARDS and sepsis patient samples, starting from within the first two days after admission to the intensive care, were then analyzed for changes in autoantibody over time.</p> <p>Results</p> <p>From screening patient plasma, 57% of ARDS and 46% of septic patients without ARDS demonstrated at least one statistically significant elevated autoantibody compared to the controls. Frequent high titer antibodies were detected against a spectrum of autoantigens including potassium channel regulator, gastric ATPase, glutamic decarboxylase-65 and several cytokines. Analysis of serial samples revealed that several seropositive patients had low autoantibodies at early time points that often rose precipitously and peaked between days 7-14. Further, the use of therapeutic doses of corticosteroids did not diminish the rise in autoantibody titers. In some cases, the patient autoantibody titers remained elevated through the last serum sample collected.</p> <p>Conclusion</p> <p>The rapid induction of autoantibodies in ARDS and severe sepsis suggests that ongoing systemic inflammation and associated tissue destruction mediate the break in tolerance against these self proteins.</p

On Coupling FCA and MDL in Pattern Mining

International audiencePattern Mining is a well-studied field in Data Mining and Machine Learning. The modern methods are based on dynamically updating models, among which MDL-based ones ensure high-quality pattern sets. Formal concepts also characterize patterns in a condensed form. In this paper we study MDL-based algorithm called Krimp in FCA settings and propose a modified version that benefits from FCA and relies on probabilistic assumptions that underlie MDL. We provide an experimental proof that the proposed approach improves quality of pattern sets generated by Krimp

How the other half lives: CRISPR-Cas's influence on bacteriophages

CRISPR-Cas is a genetic adaptive immune system unique to prokaryotic cells used to combat phage and plasmid threats. The host cell adapts by incorporating DNA sequences from invading phages or plasmids into its CRISPR locus as spacers. These spacers are expressed as mobile surveillance RNAs that direct CRISPR-associated (Cas) proteins to protect against subsequent attack by the same phages or plasmids. The threat from mobile genetic elements inevitably shapes the CRISPR loci of archaea and bacteria, and simultaneously the CRISPR-Cas immune system drives evolution of these invaders. Here we highlight our recent work, as well as that of others, that seeks to understand phage mechanisms of CRISPR-Cas evasion and conditions for population coexistence of phages with CRISPR-protected prokaryotes.Comment: 24 pages, 8 figure

Dietary Pattern Trajectories from 6 to 12 Months of Age in a Multi-Ethnic Asian Cohort

10.3390/nu8060365Nutrients86365GUSTO (Growing up towards Healthy Outcomes

Gas-cushioned droplet impacts with a thin layer of porous media

The authors are grateful to Dr. Manish Tiwari for introducing them to experiments involving droplet impacts with textured substrates. PDH is grateful for the use of the Maxwell High-Performance Computing Cluster of the University of Aberdeen IT Service. RP is grateful for the use of the High-Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia.Peer reviewedPostprin

Stress effects on stability and diffusion behavior of sulfur impurity in nickel: A first-principles study

A systematic investigation regarding the effect of stress on the stability and diffusion behavior of S impurity in Ni was carried out via first-principles methods. A comparison of the formation energy of S in Ni indicated that S more easily forms as a solution atom with increasing S concentration in Ni supercells, but the binding energy showed that as the concentration of S that dissolved into Ni increased, the structure became less stable. The diffusion barrier via the octahedral-tetrahedral-octahedral site path was always lower than that via the octahedral-octahedral site path. The diffusion barrier of single S decreased with increase in tensile stress. S diffusion accelerated under applied tensile stress, which was disadvantageous in suppressing S retention in Ni. These results implied that even at a low concentration, dissolved S still had a tendency of precipitating from the Ni matrix, to further increase the stability of the system. (C) 2014 Elsevier B. V. All rights reserved

Entity linking of tweets based on dominant entity candidates

© 2018, Springer-Verlag GmbH Austria, part of Springer Nature. Entity linking, also known as semantic annotation, of textual content has received increasing attention. Recent works in this area have focused on entity linking on text with special characteristics such as search queries and tweets. The semantic annotation of tweets is specially proven to be challenging given the informal nature of the writing and the short length of the text. In this paper, we propose a method to perform entity linking on tweets built based on one primary hypothesis. We hypothesize that while there are formally many possible entity candidates for an ambiguous mention in a tweet, as listed on the disambiguation page of the corresponding entity on Wikipedia, there are only few entity candidates that are likely to be employed in the context of Twitter. Based on this hypothesis, we propose a method to identify such dominant entity candidates for each ambiguous mention and use them in the annotation process. Particularly, our proposed work integrates two phases (i) dominant entity candidate detection, which applies community detection methods for finding the dominant candidates of ambiguous mentions; and (ii) named entity disambiguation that links a tweet to entities in Wikipedia by only considering the identified dominant entity candidates. Our investigations show that: (1) there are only very few entity candidates for each ambiguous mention in a tweet that need to be considered when performing disambiguation. This helps us limit the candidate search space and hence noticeably reduce the entity linking time; (2) limiting the search space to only a subset of disambiguation options will not only improve entity linking execution time but will also lead to improved accuracy of the entity linking process when the main entity candidates of each mention are mined from a temporally aligned corpus. We show that our proposed method offers competitive results with the state-of-the-art methods in terms of precision and recall on widely used gold standard datasets while significantly reducing the time for processing each tweet

Cross section balance in the 14N + 159Tb reaction and the origin of fast alpha particles

Exclusive cross sections have been obtained from particle-K X-ray coincidence data measured at 236 MeV for ejectiles ranging from 4 He to 15 N. Production cross sections for primary fragments and alpha particle multiplicities associated with different channels have been deduced. The major fraction of the alpha particles appears to originate from inelastic (damped) processes in which only light particles with Z < 2 are emitted

Towards personalised allele-specific CRISPR gene editing to treat autosomal dominant disorders

Abstract CRISPR/Cas9 holds immense potential to treat a range of genetic disorders. Allele-specific gene disruption induced by non-homologous end-joining (NHEJ) DNA repair offers a potential treatment option for autosomal dominant disease. Here, we successfully delivered a plasmid encoding S. pyogenes Cas9 and sgRNA to the corneal epithelium by intrastromal injection and acheived long-term knockdown of a corneal epithelial reporter gene, demonstrating gene disruption via NHEJ in vivo. In addition, we used TGFBI corneal dystrophies as a model of autosomal dominant disease to assess the use of CRISPR/Cas9 in two allele-specific systems, comparing cleavage using a SNP-derived PAM to a guide specific approach. In vitro, cleavage via a SNP-derived PAM was found to confer stringent allele-specific cleavage, while a guide-specific approach lacked the ability to distinguish between the wild-type and mutant alleles. The failings of the guide-specific approach highlights the necessity for meticulous guide design and assessment, as various degrees of allele-specificity are achieved depending on the guide sequence employed. A major concern for the use of CRISPR/Cas9 is its tendency to cleave DNA non-specifically at “off-target” sites. Confirmation that S. pyogenes Cas9 lacks the specificity to discriminate between alleles differing by a single base-pair regardless of the position in the guide is demonstrated