Background
Group 2 innate lymphoid cells (ILC2s) were closely associated with asthma. However, there were no perspective studies about the effects of glucocorticoid on ILC2s in asthma patients. Our ...objective was to perform a perspective study and evaluate the ILC2 activity after glucocorticoid therapy in asthma patients.
Methods
The asthma and asthma with allergic rhinitis patients were treated with glucocorticoid for 3 months. The circulating ILC2 levels were evaluated. The effects of glucocorticoid on ILC2s and possible signalling pathways were investigated in vitro.
Results
The patients were well‐controlled, and the high ILC2 levels were significantly decreased at 1 and 3 months after treatment. Peripheral blood monocytes from allergic patients produced dramatic IL‐5, IL‐13 and IL‐9 in response to IL‐25, IL‐33 plus IL‐2, and glucocorticoid significantly decreased their levels. Moreover, ILC2s were identified to be the predominant source of IL‐5, IL‐13 and IL‐9, and glucocorticoid treatment was able to reverse their high levels. STAT3, STAT5, STAT6, JAK3 and MEK signalling pathways were proved to be involved in regulating ILC2 activity under the glucocorticoid treatment.
Conclusion
The data suggested that glucocorticoid administration could be effective in treating asthma by regulating ILC2s via MEK/JAK‐STAT signalling pathways. This provides a new understanding of glucocorticoid application in regard to allergic diseases.
High circulating ILC2s were found in asthma and asthma with allergic rhinitis patients, and significantly decreased after treatment of glucocorticoid. High levels of IL‐5, IL‐13 and IL‐9 in response to epithelium‐derived cytokines were mostly produced by the increased ILC2s from asthma patients. Glucocorticoid treatment is able to reverse the high levels of IL‐5 and IL‐13 produced by ILC2s via STAT3, STAT5 and STAT6 signalling pathways.
Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation ...activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO2 flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO2 fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO2 exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate's temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE.
There is need for a validated short, simple instrument to quantify chronic obstructive pulmonary disease (COPD) impact in routine practice to aid health status assessment and communication between ...patient and physician. Current health-related quality of life questionnaires provide valid assessment of COPD, but are complex, which limits routine use. The aim of the present study was to develop a short validated patient-completed questionnaire, the COPD Assessment Test (CAT), assessing the impact of COPD on health status. 21 candidate items identified through qualitative research with COPD patients were used in three prospective international studies (Europe and the USA, n = 1,503). Psychometric and Rasch analyses identified eight items fitting a unidimensional model to form the CAT. Items were tested for differential functioning between countries. Internal consistency was excellent: Cronbach's alpha = 0.88. Test re-test in stable patients (n = 53) was very good (intra-class correlation coefficient 0.8). In the sample from the USA, the correlation with the COPD-specific version of the St George's Respiratory Questionnaire was r = 0.80. The difference between stable (n = 229) and exacerbation patients (n = 67) was five units of the 40-point scale (12%; p<0.0001). The CAT is a short, simple questionnaire for assessing and monitoring COPD. It has good measurement properties, is sensitive to differences in state and should provide a valid, reliable and standardised measure of COPD health status with worldwide relevance.
In order to improve the accuracy of emotional recognition by end-to-end automatic learning of emotional features in spatial and temporal dimensions of electroencephalogram (EEG), an EEG emotional ...feature learning and classification method using deep convolution neural network (CNN) was proposed based on temporal features, frequential features, and their combinations of EEG signals in DEAP dataset. The shallow machine learning models including bagging tree (BT), support vector machine (SVM), linear discriminant analysis (LDA), and Bayesian linear discriminant analysis (BLDA) models and deep CNN models were used to make emotional binary classification experiments on DEAP datasets in valence and arousal dimensions. The experimental results showed that the deep CNN models which require no feature engineering achieved the best recognition performance on temporal and frequency combined features in both valence and arousal dimensions, which is 3.58% higher than the performance of the best traditional BT classifier in valence dimension and 3.29% higher than that of BT classifier in arousal dimension.
The Didymellaceae is one of the most species-rich families in the fungal kingdom, and includes species that inhabit a wide range of ecosystems. The taxonomy of Didymellaceae has recently been revised ...on the basis of multi-locus DNA sequence data. In the present study, we investigated 108 Didymellaceae isolates newly obtained from 40 host plant species in 27 plant families, and various substrates from caves, including air, water and carbonatite, originating from Argentina, Australia, Canada, China, Hungary, Israel, Italy, Japan, South Africa, the Netherlands, the USA and former Yugoslavia. Among these, 68 isolates representing 32 new taxa are recognised based on the multi-locus phylogeny using sequences of LSU, ITS, rpb2 and tub2, and morphological differences. Within the Didymellaceae, five genera appeared to be limited to specific host families, with other genera having broader host ranges. In total 19 genera are recognised in the family, with Heracleicola being reduced to synonymy under Ascochyta. This study has significantly improved our understanding on the distribution and biodiversity of Didymellaceae, although the placement of several genera still need to be clarified.
We make use of a catalog of 1600 Pan-STARRS1 groups produced by the probability friends-of-friends algorithm to explore how the galaxy properties, i.e., the specific star formation rate (SSFR) and ...quiescent fraction, depend on stellar mass and group-centric radius. The work is the extension of Lin et al. In this work, powered by a stacking technique plus a background subtraction for contamination removal, a finer correction and more precise results are obtained than in our previous work. We find that while the quiescent fraction increases with decreasing group-centric radius, the median SSFRs of star-forming galaxies in groups at fixed stellar mass drop slightly from the field toward the group center. This suggests that the main quenching process in groups is likely a fast mechanism. On the other hand, a reduction in SSFRs by ∼0.2 dex is seen inside clusters as opposed to the field galaxies. If the reduction is attributed to the slow quenching effect, the slow quenching process acts dominantly in clusters. In addition, we also examine the density-color relation, where the density is defined by using a sixth-nearest-neighbor approach. Comparing the quiescent fractions contributed from the density and radial effect, we find that the density effect dominates the massive group or cluster galaxies, and the radial effect becomes more effective in less massive galaxies. The results support mergers and/or starvation as the main quenching mechanisms in the group environment, while harassment and/or starvation dominate in clusters.
Multistage coupling of laser-wakefield accelerators is essential to overcome laser energy depletion for high-energy applications such as TeV-level electron-positron colliders. Current staging schemes ...feed subsequent laser pulses into stages using plasma mirrors while controlling electron beam focusing with plasma lenses. Here a more compact and efficient scheme is proposed to realize the simultaneous coupling of the electron beam and the laser pulse into a second stage. A partly curved channel, integrating a straight acceleration stage with a curved transition segment, is used to guide a fresh laser pulse into a subsequent straight channel, while the electrons continue straight. This scheme benefits from a shorter coupling distance and continuous guiding of the electrons in plasma while suppressing transverse beam dispersion. Particle-in-cell simulations demonstrate that the electron beam from a previous stage can be efficiently injected into a subsequent stage for further acceleration while maintaining high capture efficiency, stability, and beam quality.
ABSTRACT
We present results from the search for a stochastic gravitational-wave background (GWB) as predicted by the theory of General Relativity using six radio millisecond pulsars from the Data ...Release 2 (DR2) of the European Pulsar Timing Array (EPTA) covering a timespan up to 24 yr. A GWB manifests itself as a long-term low-frequency stochastic signal common to all pulsars, a common red signal (CRS), with the characteristic Hellings-Downs (HD) spatial correlation. Our analysis is performed with two independent pipelines, ENTERPRISE, and TEMPONEST+FORTYTWO, which produce consistent results. A search for a CRS with simultaneous estimation of its spatial correlations yields spectral properties compatible with theoretical GWB predictions, but does not result in the required measurement of the HD correlation, as required for GWB detection. Further Bayesian model comparison between different types of CRSs, including a GWB, finds the most favoured model to be the common uncorrelated red noise described by a power law with $A = 5.13_{-2.73}^{+4.20} \times 10^{-15}$ and $\gamma = 3.78_{-0.59}^{+0.69}$ (95 per cent credible regions). Fixing the spectral index to γ = 13/3 as expected from the GWB by circular, inspiralling supermassive black hole binaries results in an amplitude of $A =2.95_{-0.72}^{+0.89} \times 10^{-15}$. We implement three different models, BAYESEPHEM, LINIMOSS, and EPHEMGP, to address possible Solar system ephemeris (SSE) systematics and conclude that our results may only marginally depend on these effects. This work builds on the methods and models from the studies on the EPTA DR1. We show that under the same analysis framework the results remain consistent after the data set extension.
We present the laboratory and ambient photoacoustic (PA) measurement of aerosol light absorption coefficients at ultraviolet wavelength (i.e., 355 nm) and compare with measurements at 405, 532, 870, ...and 1047 nm. Simultaneous measurements of aerosol light scattering coefficients were achieved by the integrating reciprocal nephelometer within the PA's acoustic resonator. Absorption and scattering measurements were carried out for various laboratory-generated aerosols, including salt, incense, and kerosene soot to evaluate the instrument calibration and gain insight on the spectral dependence of aerosol light absorption and scattering. Ambient measurements were obtained in Reno, Nevada, between 18 December 2009 and 18 January 2010. The measurement period included days with and without strong ground level temperature inversions, corresponding to highly polluted (freshly emitted aerosols) and relatively clean (aged aerosols) conditions. Particulate matter (PM) concentrations were measured and analyzed with other tracers of traffic emissions. The temperature inversion episodes caused very high concentration of PM2.5 and PM10 (particulate matter with aerodynamic diameters less than 2.5 μm and 10 μm, respectively) and gaseous pollutants: carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO2). The diurnal change of absorption and scattering coefficients during the polluted (inversion) days increased approximately by a factor of two for all wavelengths compared to the clean days. The spectral variation in aerosol absorption coefficients indicated a significant amount of absorbing aerosol from traffic emissions and residential wood burning. The analysis of single scattering albedo (SSA), Ångström exponent of absorption (AEA), and Ångström exponent of scattering (AES) for clean and polluted days provides evidences that the aerosol aging and coating process is suppressed by strong temperature inversion under cloudy conditions. In general, measured UV absorption coefficients were found to be much larger for biomass burning aerosol than for typical ambient aerosols.
Toll‐like receptors (TLRs) activate biochemical pathways that evoke activation of innate immunity, which leads to dendritic cell (DC) maturation and initiation of adaptive immune responses that ...provoke allograft rejection. We aimed to prolong allograft survival by selectively inhibiting expression of the common adaptors of TLR signaling, namely MyD88 and TRIF, using siRNA. In vitro we demonstrated that blocking expression of MyD88 and TRIF led to reduced DC maturation. In vivo treatment of recipients with MyD88 and TRIF siRNA significantly prolonged allograft survival in the BALB/c > C57BL6 cardiac transplant model. Moreover, the combination of MyD88 and TRIF siRNA along with a low dose of rapamycin further extended the allograft survival (88.8 ± 7.1 days). Tissue histopathology demonstrated an overall reduction in lymphocyte interstitium infiltration, vascular obstruction and hemorrhage in mice treated with MyD88 and TRIF siRNA vector plus rapamycin. Furthermore, treatment was associated with an increase in the numbers of CD4+CD25+FoxP3+ regulatory T cells and Th2 deviation. To our knowledge, this study is the first demonstration of prolonging the survival of allogeneic heart grafts through gene silencing of TLR signaling adaptors, highlighting the therapeutic potential of siRNA in clinical transplantation.
The authors highlight the therapeutic potential of siRNA in specifically knocking down the TLR adaptors MyD88 and TRIF and preventing heart graft rejection.
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