980 research outputs found

    Asthma in the elderly: what we know and what we have yet to know

    Get PDF
    In the past, asthma was considered mainly as a childhood disease. However, asthma is an important cause of morbidity and mortality in the elderly nowadays. In addition, the burden of asthma is more significant in the elderly than in their younger counterparts, particularly with regard to mortality, hospitalization, medical costs or health-related quality of life. Nevertheless, asthma in the elderly is still been underdiagnosed and undertreated. Therefore, it is an imperative task to recognize our current challenges and to set future directions. This project aims to review the current literature and identify unmet needs in the fields of research and practice for asthma in the elderly. This will enable us to find new research directions, propose new therapeutic strategies, and ultimately improve outcomes for elderly people with asthma. There are data to suggest that asthma in older adults is phenotypically different from young patients, with potential impact on the diagnosis, assessment and management in this population. The diagnosis of AIE in older populations relies on the same clinical findings and diagnostic tests used in younger populations, but the interpretation of the clinical data is more difficult. The challenge today is to encourage new research in AIE but to use the existing knowledge we have to make the diagnosis of AIE, educate the patient, develop a therapeutic approach to control the disease, and ultimately provide a better quality of life to our elderly patients

    Origin and Evolution of TRIM Proteins: New Insights from the Complete TRIM Repertoire of Zebrafish and Pufferfish

    Get PDF
    Tripartite motif proteins (TRIM) constitute a large family of proteins containing a RING-Bbox-Coiled Coil motif followed by different C-terminal domains. Involved in ubiquitination, TRIM proteins participate in many cellular processes including antiviral immunity. The TRIM family is ancient and has been greatly diversified in vertebrates and especially in fish. We analyzed the complete sets of trim genes of the large zebrafish genome and of the compact pufferfish genome. Both contain three large multigene subsets - adding the hsl5/trim35-like genes (hltr) to the ftr and the btr that we previously described - all containing a B30.2 domain that evolved under positive selection. These subsets are conserved among teleosts. By contrast, most human trim genes of the other classes have only one or two orthologues in fish. Loss or gain of C-terminal exons generated proteins with different domain organizations; either by the deletion of the ancestral domain or, remarkably, by the acquisition of a new C-terminal domain. Our survey of fish trim genes in fish identifies subsets with different evolutionary dynamics. trims encoding RBCC-B30.2 proteins show the same evolutionary trends in fish and tetrapods: they evolve fast, often under positive selection, and they duplicate to create multigenic families. We could identify new combinations of domains, which epitomize how new trim classes appear by domain insertion or exon shuffling. Notably, we found that a cyclophilin-A domain replaces the B30.2 domain of a zebrafish fintrim gene, as reported in the macaque and owl monkey antiretroviral TRIM5α. Finally, trim genes encoding RBCC-B30.2 proteins are preferentially located in the vicinity of MHC or MHC gene paralogues, which suggests that such trim genes may have been part of the ancestral MHC

    Regulation of MicroRNA Biogenesis: A miRiad of mechanisms

    Get PDF
    microRNAs are small, non-coding RNAs that influence diverse biological functions through the repression of target genes during normal development and pathological responses. Widespread use of microRNA arrays to profile microRNA expression has indicated that the levels of many microRNAs are altered during development and disease. These findings have prompted a great deal of investigation into the mechanism and function of microRNA-mediated repression. However, the mechanisms which govern the regulation of microRNA biogenesis and activity are just beginning to be uncovered. Following transcription, mature microRNA are generated through a series of coordinated processing events mediated by large protein complexes. It is increasingly clear that microRNA biogenesis does not proceed in a 'one-size-fits-all' manner. Rather, individual classes of microRNAs are differentially regulated through the association of regulatory factors with the core microRNA biogenesis machinery. Here, we review the regulation of microRNA biogenesis and activity, with particular focus on mechanisms of post-transcriptional control. Further understanding of the regulation of microRNA biogenesis and activity will undoubtedly provide important insights into normal development as well as pathological conditions such as cardiovascular disease and cancer

    The ATLAS fast tracKer system

    Get PDF
    The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited η-ϕ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation. © The ATLAS collaboratio

    Measurement of the total cross section and ρ -parameter from elastic scattering in pp collisions at √s=13 TeV with the ATLAS detector

    Get PDF

    Measurement of exclusive pion pair production in proton–proton collisions at √s=7 TeV with the ATLAS detector

    Get PDF

    Measurement of the nuclear modification factor of b-jets in 5.02 TeV Pb+Pb collisions with the ATLAS detector

    Get PDF

    Search for resonant WZ production in the fully leptonic final state in proton–proton collisions at √s=13 TeV with the ATLAS detector

    Get PDF

    Constraints on Higgs boson properties using WW∗(→ eνμν) jj production in 36.1fb-1 of √s=13 TeV pp collisions with the ATLAS detector

    Get PDF
    This article presents the results of two studies of Higgs boson properties using the WW∗(→ eνμν) jj final state, based on a dataset corresponding to 36.1 fb - 1 of s=13 TeV proton–proton collisions recorded by the ATLAS experiment at the Large Hadron Collider. The first study targets Higgs boson production via gluon–gluon fusion and constrains the CP properties of the effective Higgs–gluon interaction. Using angular distributions and the overall rate, a value of tan (α) = 0.0 ± 0.4 (stat.) ± 0.3 (syst.) is obtained for the tangent of the mixing angle for CP-even and CP-odd contributions. The second study exploits the vector-boson fusion production mechanism to probe the Higgs boson couplings to longitudinally and transversely polarised W and Z bosons in both the production and the decay of the Higgs boson; these couplings have not been directly constrained previously. The polarisation-dependent coupling-strength scale factors are defined as the ratios of the measured polarisation-dependent coupling strengths to those predicted by the Standard Model, and are determined using rate and kinematic information to be aL=0.91-0.18+0.10(stat.)-0.17+0.09(syst.) and aT= 1.2 ± 0.4 (stat.)-0.3+0.2(syst.). These coupling strengths are translated into pseudo-observables, resulting in κVV=0.91-0.18+0.10(stat.)-0.17+0.09(syst.) and ϵVV=0.13-0.20+0.28 (stat.)-0.10+0.08(syst.). All results are consistent with the Standard Model predictions
    corecore