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Dendritic cells (DCs) sense environmental cues and adopt either an immune-stimulatory or regulatory phenotype, thereby fine-tuning immune responses. Identifying endogenous regulators that determine DC function can thus inform the development of therapeutic strategies for modulating the immune response in different disease contexts. Tim-3 plays an important role in regulating immune responses by inhibiting the activation status and the T cell priming ability of DC in the setting of cancer. Bat3 is an adaptor protein that binds to the tail of Tim-3; therefore, we studied its role in regulating the functional status of DCs. In murine models of autoimmunity (experimental autoimmune encephalomyelitis) and cancer (MC38-OVA–implanted tumor), lack of Bat3 expression in DCs alters the T cell compartment—it decreases TH1, TH17 and cytotoxic effector cells, increases regulatory T cells, and exhausted CD8+tumor-infiltrating lymphocytes, resulting in the attenuation of autoimmunity and acceleration of tumor growth. We found that Bat3 expression levels were differentially regulated by activating versus inhibitory stimuli in DCs, indicating a role for Bat3 in the functional calibration of DC phenotypes. Mechanistically, loss of Bat3 in DCs led to hyperactive unfolded protein response and redirected acetyl–coenzyme A to increase cell intrinsic steroidogenesis. The enhanced steroidogenesis in Bat3-deficient DC suppressed T cell response in a paracrine manner. Our findings identified Bat3 as an endogenous regulator of DC function, which has implications for DC-based immunotherapies.

Surface radiation is crucial to atmospheric boundary layer development and air pollution formation. Several studies have revealed that surface radiation plays a vital role in developing the daytime convective boundary layer that controls the explosive growth of PM

This technical notes details the methodology behind the Electric Vehicles on the Grid Simulator. This tool is intended to help individual building energy managers, facility owners, distribution service operators, charging point operators, and fleet operators. This model-based simulator enables users to evaluate the potential electric vehicle (EV) load impacts on the low-voltage distribution grid at specific sites and plan for future capacity upgrades. Additionally, the tool can be used to quantify the effects of different vehicle-grid integration technologies to alleviate the peak capacity stress. The Monte Carlo simulation and linear programming are deployed to predict the EV charging and discharging load profiles and load impacts at specific sites, with the consideration of future EV penetration, EV charging and traveling behaviors, availability of charging facility availability, and site loads. Based on existing studies conducted in the United States, Europe, and China, the default EV charging and traveling behaviors are predefined for a quick assessment. Users are encouraged to modify the model inputs for the specific site to derive more accurate and contextualized results. This tool can also help manage an EV fleet’s smart charging and discharging at the low-voltage distribution grid.

Deep basins create a uniquely favorable condition for the formation of air pollution, and the Sichuan Basin (SCB) in Southwest China is such a basin featuring frequent heavy pollution. A wintertime heavy haze pollution event in SCB was studied with conventional and intensive observation data and the WRF-chem model to explore the three-dimensional distribution of PM2.5 for understanding the impact of regional pollutant emissions, basin circulations associated with plateaus, and downwind transport to the adjacent areas. It was found that the vertical structure of PM2.5 over SCB was characterized with a remarkable hollow sandwiched by high PM2.5 layers at heights of 1.5–3 km and the highly polluted near-surface layer. The southwesterlies passed over the Tibetan Plateau (TP) and Yunan-Guizhou Plateau (YGP) resulted in a lee vortex over SCB, which helped form and maintain heavy PM2.5 pollution. The basin PM2.5 was lifted into the free troposphere and transported outside of SCB. At the bottom of SCB, high PM2.5 concentrations were mostly located in the northwest and southern regions. Due to the blocking effect of the plateau terrain on the northeasterly winds, PM2.5 gradually increased from northeast to southwest in the basin. In the lower free troposphere, the high PM2.5 centers were distributed over the northwestern and southwestern SCB areas, as well as the central SCB region. For this event, the regional emissions from SCB contributed 75.4–94.6 % to the surface PM2.5 concentrations in SCB. The SCB emission export was the major source of the PM2.5 over the eastern regions of TP and the northern regions of YGP, with contribution rates of 72.7 % and 70.5 %, respectively, during the dissipation stage of heavy air pollution over SCB, which was regarded as the major pollutant sources affecting atmospheric environment changes in Southwest China.

China&rsquo, s government launched a policy in October 2017 to permit the distributed generators to peer-to-peer trade their electricity generation on the market. Several clauses in the policy document are, however, unclear and ambiguous. This work identifies three vital but not clearly detailed issues in the policy document: (1) participation eligibility, (2) the grid fee calculation method, and (3) subsidy rates. Then, we carry out a comprehensive analysis of the economic impacts of the trade policy based on a case study of an eastern city in China. Sensitivity analyses on the impacts of the subsidy rates, transmission and distribution prices (TDPs), and end-user regulated prices are conducted. The results show that the trading policy will benefit the photovoltaic (PV) generators with more revenue by 6&ndash, 11%, reduce the cost for end-users by 6&ndash, 12%, and decrease the revenue of the power grid company by 32&ndash, 55%.

Applying plant community diversity techniques and SPSS statistic analysis, we quantified the relationship between crown volume of 18 (Sophora japonica) tree communities and elevation along different elevation gradient in Ye County in the study. We concluded that there was a significantly positive correlation between crown volume of 18 (Sophora japonica) tree communities and elevation gradient (P Sophora japonica) tree communities increased along elevation from 50 m to 200 m in Ye County in 2018. Therefore, understanding dynamic connecting crown volume of 18 (Sophora japonica) communities and elevation can be not just applied to preserve of (Sophora japonica) tree communities, but also applied to sustainable of biodiversity and processes of tree community’s crown volume along elevation.

Surface radiation is crucial to atmospheric boundary layer development and air pollution formation. Several studies have revealed that surface radiation plays a vital role in developing the daytime convective boundary layer that controls the explosive growth of PM2.5 concentration; however, less attention has been paid to the effects of changing nighttime surface radiation on the near-surface temperature inversion layer and PM2.5 accumulation. In this study, we used long-term observations of meteorological and environmental data and atmospheric boundary layer measurements during a severe PM2.5 pollution event to investigate the effect of changes in nocturnal surface radiation on the increase in PM2.5 concentrations. The results showed that surface radiation cooling was enhanced (weakened) by decreased (increased) cloud cover fraction by changing longwave radiation at night; this strengthened (weakened) near-surface temperature inversion intensity and promoted (prevented) the accumulated increase in PM2.5. This observational study using 5-year data further confirmed the cloud radiative effect on the nighttime accumulation of PM2.5 with a significant negative correlation between nighttime averages of surface PM2.5 concentrations and cloud cover fractions. This reveals an important mechanism for the impact of surface radiation cooling modulated by cloud cover change on the nighttime accumulated increase in PM2.5. This finding extends our understanding of air pollutant accumulation at night with potential implications for atmospheric environment change.

Summary Identifying signals in the tumor microenvironment (TME) that shape CD8+ T cell phenotype can inform novel therapeutic approaches for cancer. Here, we identified a gradient of increasing glucocorticoid receptor (GR) expression and signaling from naive to dysfunctional CD8+ tumor-infiltrating lymphocytes (TILs). Conditional deletion of the GR in CD8+ TILs improved effector differentiation, reduced expression of the transcription factor TCF-1, and inhibited the dysfunctional phenotype, culminating in tumor growth inhibition. GR signaling transactivated the expression of multiple checkpoint receptors and promoted the induction of dysfunction-associated genes upon T cell activation. In the TME, monocyte-macrophage lineage cells produced glucocorticoids and genetic ablation of steroidogenesis in these cells as well as localized pharmacologic inhibition of glucocorticoid biosynthesis improved tumor growth control. Active glucocorticoid signaling associated with failure to respond to checkpoint blockade in both preclinical models and melanoma patients. Thus, endogenous steroid hormone signaling in CD8+ TILs promotes dysfunction, with important implications for cancer immunotherapy.

Identifying signals in the tumor microenvironment (TME) that promote CD8+ T cell dysfunction can inform improved therapeutic approaches for cancer. Here, we identify that Nr3c1, the gene encoding the glucocorticoid receptor (GR), is highly expressed in dysfunctional CD8+ tumor-infiltrating lymphocytes (TILs). The GR transactivates expression of multiple checkpoint receptors and loss of GR in CD8+ T cells limits dysfunctional phenotype in CD8+ TILs resulting in improved tumor growth control. We show that glucocorticoids can be produced in the TME and that they co-operate with the immunosuppressive cytokine IL-27 to promote the dysfunction gene program in CD8+ T cells. The presence of the glucocorticoid + IL27 signature in CD8+ TILs correlates with failure to respond to checkpoint blockade in melanoma patients, highlighting the relevance of this immunoregulatory glucocorticoid-cytokine circuit in tumor tissue.

The aerosol change over the Tibetan Plateau (TP) is poorly understood due to the scarcity of aerosol measurements over the TP. The aerosol optical properties were measured with a CE-318 sun photometer from January to December in 2017 at the Litang station (30.00°N, 100.16°E, 3950.5 m a.s.l.) over the eastern edge of the TP to characterize the variations in the aerosol optical properties and assess the applicability of MODIS AOD products at the eastern edge of TP. The analyses show that the annual mean aerosol optical depth at 440 nm (AOD440nm) is 0.08 ± 0.03. The mean annual Angstrom exponent between 440 and 870 nm (AE440–870nm) is 0.72 ± 0.23. The monthly-averaged AOD440nm exhibits a maximum (0.11 ± 0.04) in July and minimum (0.05 ± 0.02) in January, while the monthly mean AE440–870nm shows a maximum (1.08 ± 0.19) in July and minimum (0.48 ± 0.32) in February. The findings based on measured AOD440nm and AE440–870nm indicate low AOD, dominated by coarse particles in winter and fine particles in summer over the eastern TP edge. Three datasets of MODIS AOD products with 3 km spatial resolution as well as with 10 km spatial resolution based on Dark Target (DT) and Deep Blue (DB) algorithms are validated using the ground-based measurements over the eastern edge of the TP. Although the validations show a low accuracy of MODIS AOD products of the three datasets over this TP region, the MODIS AOD products based on the DB algorithm with 10 km resolution could be used in the atmospheric environment over the eastern edge of the TP based on the best match between AOD data and ground-based measurements, the lowest retrieval error, and the largest percentage falling within the expected error envelope.

Identifying signals in the tumor microenvironment (TME) that promote CD8+T cell dysfunction can inform the development of novel approaches to improve anti-tumor T cell responses. Here, we identified Nr3c1, the gene encoding the glucocorticoid receptor (GR), as one of the genes preferentially expressed by dysfunctional CD8+TILs. Glucocorticoids (GCs) are steroid hormones and ligands for the GR. Despite their widespread use, surprisingly little is known regarding the molecular circuitry by which glucocorticoids suppress immune responses. We demonstrate that glucocorticoids are synthesized de novo in the TME and activation of glucocorticoid signaling promotes features of dysfunction, including increased expression of checkpoint receptors like Tim3, PD1, Lag3 and TIGIT, and dampened effector function including decreased production of pro-inflammatory cytokines in both murine and human CD8+T cells. Deletion of GR in CD8+T cells in vivo resulted in loss of dysfunctional phenotype in CD8+TILs concomitant with improved tumor growth control. We thus identified glucocorticoid signaling as a component of immune suppression within the TME and uncovered a molecular mechanism by which it suppresses T cell responses. Glucocorticoids are the mainstay for treating the immune-related adverse events (IRAEs) that develop in patients receiving immune checkpoint blockade. Thus, having a better understanding of the mechanisms downstream of GCs could inform the application of glucocorticoids for suppressing immune responses.

Correlations between water cloud effective radius (CER) and aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) are examined over seven sub-regions in Eastern China for 2003–2012. Water phase cloud is defined as having a cloud top pressure greater than 800 hPa. Significant negative correlation coefficients ( r = −0.79 ∼ −0.94) between AOD and CER are derived over the East Sea and the South China Sea for grid cells with AOD r = 0.01–0.91) are calculated for cells with AOD > 0.3. In contrast, significant positive correlations ( r = 0.67–0.95) are derived over the Eastern China mainland and Yellow Sea. Further analysis for North China Plain shows that variations in wind speed and relative humidity may account for such positive correlations. Southerly winds carry high levels of pollutants and abundant water vapor, resulting in coincident increases in both AOD and CER in North China Plain, while the northerly winds transport dry and clean air from high latitudes, leading to decreases in AOD and CER. Both processes contribute to the positive correlations between AOD and CER over Eastern China, suggesting that the influence of background weather conditions need to be considered when studying the interactions between aerosol and cloud.

Acid rain and dust events are both serious environmental problems striking China nowadays. This study investigates the distribution and change of precipitation pH and discusses the influence of dust events on precipitation acidity qualitatively and quantitatively in China. Acid rain exhibits remarkable regionality with strong acidic in South China and the acidity gradually decreases from the South to the North. This distribution is decided not only by the concentration of SO2 in atmosphere but also has relationship to the occurrence of dust events. Comparing the monthly changes of precipitation pH in the semiarid region (which is influenced by dust events) with those in the humid region (which is acid rain areas), it is found that the variation trends are just opposite in the two regions and there is an obvious peak value of pH in spring in semiarid region which coincides with the increase of dust event days. Chemical analysis results of precipitation in Lanzhou (a semiarid city intruded by dust events frequently, especially in spring) indicate that the ratio of Ca2+ plus Mg2+ concentrations (indicators of soil dust) to the total cation concentrations is the highest in spring, and the Ca2+ and Mg2+ concentrations are 1.8 and 1.9 times higher in spring than in summer respectively. The acidity of precipitation can be restrained by dust events qualitatively by increasing alkaline materials in the atmosphere and precipitation. The analysis of daily dust events and precipitation data at 6 stations in Northwest China indicates that the pH of precipitation influenced by dust events is greater than the precipitation not influenced by dust events. The increase degrees are different between different stations and have lagging effects. The direct increases are from 0.03 to 0.91 for the precipitation pH. Dust events can promote the precipitation pH to a certain extent quantitatively. (C) 2013 Elsevier Ltd. All rights reserved.

Global energy interconnection based on “one Belt and one Road initiative” becomes core strategy of China State Grid and promotes the sustainable transformation of world energy system. Technically, mutual benefits from the inter-state transmission may exist between China and Arab States. The paper proposes an economic benefit assessment method of inter-state transmission project using chronological production cost simulation model. An index assessing economic benefit with consideration of generation revenue in energy sending end and load payment in energy receiving is established. In the case study, based on the load and generation status of Sinkiang and Gulf States in year 2015, inter-state transmission benefit is quantified. In the end, a preliminary transmission interconnection plan from China to Arab States is proposed.

One of the important issues of microgrid development is how to optimize the operation of the microgrid that contains different kinds of distributed generation. This paper presents the application of particle swarm algorithm, based on chaotic simulated annealing to optimize the operation of the microgrid. Considering the operation cost, environmental benefits and other performance indicators as the objective function, to establish the mathematical model of microgrid optimal operation, propose the method of microgrid optimal operation based on chaotic simulated annealing particle swarm algorithm, and applied it to solve the multi-objective and multi-constrained problems of microgrid optimal operation. The example analysis proved the effectiveness and feasibility of this algorithm.

Summary Reversing the dysfunctional T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we analyzed population and single-cell RNA profiles of CD8 + tumor-infiltrating lymphocytes (TILs) and used genetic perturbations to identify a distinct gene module for T cell dysfunction that can be uncoupled from T cell activation. This distinct dysfunction module is downstream of intracellular metallothioneins that regulate zinc metabolism and can be identified at single-cell resolution. We further identify Gata-3, a zinc-finger transcription factor in the dysfunctional module, as a regulator of dysfunction, and we use CRISPR-Cas9 genome editing to show that it drives a dysfunctional phenotype in CD8 + TILs. Our results open novel avenues for targeting dysfunctional T cell states while leaving activation programs intact.

Wind power forecasting system is useful to increase the wind energy penetration level. Latest statistics show that China has been the biggest wind energy market throughout the world. However, few studies have been published to introduce the wind energy forecasting technologies in China. This paper presents the performance evaluation and accuracy enhancement of a novel day-ahead wind power forecasting system in China. This system consists of a numerical weather prediction (NWP) model and artificial neural networks (ANNs). The NWP model is established by coupling the Global Forecasting system (GFS) with the Weather Research and Forecasting (WRF) system together to predict meteorological parameters. In addition, Kalman filter has been integrated in this system to reduce the systematic errors in wind speed from WRF and enhance the forecasting accuracy. The numerical results from a real world case are proven the effectiveness of this forecasting system in terms of the raw wind speed correction and wind power forecasting accuracy. The Normalized Root Mean Square Error (NRMSE) has a month average value of 16.47%, which is an acceptable error margin for allowing the use of the forecasted values in electric market operations. This forecasting system is profitable for increasing the wind energy penetration level in China.

An improved understanding of the anti-tumor CD8(+) T cell response after checkpoint blockade would enable more informed and effective therapeutic strategies. Here we examined the dynamics of the effector response of CD8(+) tumor-infiltrating lymphocytes (TILs) after checkpoint blockade therapy. Bulk and single-cell RNA profiles of CD8(+) TILs following combined Tim-3+PD-1 blockade in preclinical models revealed significant changes in the transcriptional profile of PD-1(−) TILs. These cells could be divided into subsets bearing characterstics of naïve-, effector-, and memory-precursor-like cells. Effector- and memory-precursor-like TILs contained tumor-antigen specific cells, exhibited proliferative and effector capacity and expanded in response to different checkpoint blockade therapies across different tumor models. The memory-precursor-like subset shared features with CD8(+) T cells associated with response to checkpoint blockade in patients, and was compromised in the absence of Tcf7. Expression of Tcf7/Tcf1 was requisite for the efficacy of diverse immunotherapies, highlighting the importance of this transcriptional regulator in the development of effective CD8(+) T cell responses upon immunotherapy.

Reversing the dysfunctional (also known as “exhausted”) T cell state that arises in cancer and chronic viral infections is the focus of therapeutic interventions; however, current therapies are effective in only some patients and for only some tumor types. To gain a deeper molecular understanding of the dysfunctional T cell state, we leveraged mouse models to analyze RNA profiles of CD8+ tumor-infiltrating lymphocytes (TILs) at various functional states. In a comparative study we identified metallothioneins, regulators of zinc metabolism, as drivers of T cell dysfunction and used genetic perturbation to identify, for the first time, a distinct gene module for T cell dysfunction that is uncoupled from T cell activation and associated with a CD8+ Treg signature. An analysis of TILs at single-cell resolution revealed that our dysfunction module negatively correlates with activation signatures also at the single-cell level, indicating that our uncoupled signatures for T cell dysfunction and activation can represent cell-intrinsic states. Clustering of the single-cells revealed a previously uncharacterized subpopulation of CD8+ TILs that was strongly enriched for our novel dysfunction signature, but not for activation signatures. This subpopulation was depleted of cells from a metallothionein KO mouse model in which T cell dysfunction was not observed, implying that we have indeed identified a phenotypically dysfunctional subpopulation. Using CRISPR/Cas9 genome editing we validate that Gata-3, a transcription factor expressed specifically in our identified subpopulation, is a driver of the dysfunctional phenotype in CD8+ TILs. Our results open novel avenues for specifically targeting the dysfunctional T cell state while leaving T cell activation programs intact. Citation Format: Meromit Singer, Chao Wang, Le Cong, Nemanja D. Marjanovic, Monika S. Kowalczyk, Huiyuan Zhang, Jackson Nyman, Kaori Sakuishi, Sema Kurtulus, David Gennert, Junrong Xia, John YH Kwon, James Nevin, Rebecca H. Herbst, Itai Yanai, Orit Rozenblatt-Rosen, Vijay K. Kuchroo, Aviv Regev, Ana C. Anderson. A distinct gene module for T cell dysfunction uncoupled from T cell activation and controlled by metallothioneins. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2016 Oct 20-23; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2017;5(3 Suppl):Abstract nr A10.

Due to the intermittence and fluctuation of wind resource, the integration of large wind farms in a power grid introduces an additional stochastic component to power system scheduling. This always brings challenges to maintain the stability of power system. Integrating gas turbine units with wind farms can compensate their output fluctuation. In this paper, a methodology for the operation scheduling of a hybrid power system that consists of a large wind farm and gas turbine units is presented. A statistical model based on numerical weather prediction is used to forecast power output of the wind farm for the next 24 hours at quarter-hour intervals. Forecasts of wind power are used for optimizing the operation scheduling. In order to study the dynamic performance of the proposed hybrid power system, dynamic modeling of this hybrid power system is addressed. Wind farm and gas turbine units are integrated through an AC bus, and then connected to a power grid. An aggregated model of the wind farm and detailed models of gas turbine units are developed, and are implemented using MATLAB/Simulink. Simulation studies are carried out to evaluate the system performance using real weather data. The simulation results show that the proposed hybrid power system can compensate fluctuating wind power effectively and make wind power more reliable.Copyright © 2012 by ASME

The increasing penetration of wind power leads to the reduction of conventional power plants proportion and brings challenges to maintain the frequency stability of power system. The participation of wind generation in primary frequency control has become a serious concern under study. This paper presents two methods, pitch angle control and speed control to enable frequency control in dynamic process. Detailed models are built in MATLAB/SIMULINK and simulation results are compared. Based on the analysis, a new modified strategy incorporating pitch angle control and speed control to optimize frequency control of wind turbines is proposed in this paper. Blocks of the two methods are connected and switched by relay element. It's tested through simulations by using MATLAB. And the effectiveness of the suggested method is demonstrated by simulation results. The control method proposed in this paper helps improve the stability of system frequency and allows more penetration of wind power in grid.

In this paper the wind speed forecasting in a wind farm, applying the algorithm of support vector regression (SVR) to the mean 10-minute time series is presented. By comparing its performance with an back propagation neural network model through simulation results, we could find following facts: firstly, both algorithms are applicable for prediction the wind speed time series in future; secondly, the prediction effect of support vector regression outperforms the back propagation neural network model as indicated by the prediction graph and by the mean square errors and mean absolute errors. Finally, we selected three different stages of the wind speed curve to analyze, the results show that the proposed algorithm fit the original wind speed curve well at the whole process, but the back propagation neural network is inapplicability for the rise stage when the ascent rate suddenly become flatness of the original wind speed curve.

As shown in many recent works, the load-frequency behavior can be represented by system frequency response models especially for an islanding process. In this paper, a frequency response model incorporating an under-frequency load-shedding scheme is presented for islanding power system simulations. The model was applied for a practical power system with both hydro and fossil-fired power generators. The governing system models are involved in the model, which have great impact on the system dynamics. Parameter identification method is used to find and verify the model parameters. Similar responses were observed between the simulations and the accident records. The simulation results showed disadvantages of the primary frequency control systems of hydro power generators at the beginning of the load disturbances. An closed fossil fired power plant is proposed to serve against the load disturbances and improved stability was observed according to the system simulation results.

Many researches have focused on the stability analysis of power systems based on frequency response models. A constant gain value is often used to represent a governing system of a prime mover, which may be proper for a classic hydraulic governor but not suitable for modern digital electro-hydraulic (DEH) control systems. PID controllers, pressure or load feedbacks, frequency deviation feed-forwards and coordinated boiler-turbine controls are used widely for practical generation units to optimize the response characteristics of the units. Few studies have considered the effects of most elements mentioned above on the dynamic analysis of power systems. Most typical governing systems are modeled in this paper. Their effects are studied for power system stability analysis. Some of the elements are verified to be critical for the system dynamics and are proposed for power system modeling on dynamic stabilities. The results may help for power system modeling or grid stability analysis.

Accuracy parameters of system model are of great importance in stability and security evaluation or simulation for power system. Some of the conventional methods may have inadequate adaptability or effectiveness for identification of different power systems. A new framework for power system identification is proposed based on an improved genetic algorithm with a logarithmic fitness function and an adaptive search space. The framework can be used for most power system models (linear or nonlinear) and can easily be performed on different models just by rebuilding corresponding map lists between the system parameters and the model coefficients. The numerical experiment and practical experiment of a 600MW steam turbine unit are conducted to examine the performance of the framework. The identification results have demonstrated the effectiveness of the proposed framework.

Planet Boundary Layer sulfur dioxide (PBL-SO2) derived from Ozone Monitoring Instrument (OMI) are compared with in-situ measurements from Differential Optical Absorption Spectroscopy (DOAS) and gas analyzer observations at three sites in Beijing (Jan-Dec, 2007) and Hebei province (Jan-May, 2007). We use an Air Mass Factor (AMF) lookup table, which was calculated via Linearized Discrete Ordinate Radiative Transfer (LIDORT) model, to convert OMI PBL-SO2 slant column density to vertical column density. Co-locate Lidar (UV) aerosol extinction profiles are used to correct the effect of aerosol. Results show that, AMF decreases less than 3% with the increasing solar zenith angle from 0° to 45°, AMF is more sensitive to surface albedo and the viewing zenith angle. AMF reduces by 6% with the increasing Ozone density from 275DU to 325DU. Normally, absorption aerosol reduces AMF and scattering aerosol increases AMF, aerosol profiles are critical to AMF estimation. Under very clear conditions, from winter to later spring, OMI observed SO2 values are underestimated by 3.6ppbv to 20ppbv, but in reasonable agreement with in-situ measurements. Because of the effects of Sub-pixel cloud contamination, long slant path (higher solar zenith angles or viewing zenith angles), differences in aerosol types and large Aerosol Optical Depth (AOD), direct comparisons between the OMI retrieval and the in situ measurements show that the correlation is low and the differences vary with months, while averaging over half a month can significantly reduces the bias.

Covalent attachment of activated products of the third component of complement to antigen enhances its immunogenicity, but the mechanism is not clear. This effect is mediated by specific receptors, mCR1 (CD35) and mCR2 (CD21), expressed primarily on B cells and follicular dendritic cells in mice. To dissect the role of mCR1 and mCR2 in the humoral response, we have disrupted the Cr2 locus to generate mice deficient in both receptors. The deficient mice (Cr2−/−) were found to have a reduction in the CD5+ population of peritoneal B-1 cells, although their serum IgM levels were within the range of normal mice. Moreover, Cr2−/− mice had a severe defect in their humoral response to T-dependent antigens that was characterized by a reduction in serum antibody titers and in the number and size of germinal centers within splenic follicles. Reconstitution of the deficient mice with bone marrow from MHC-matched Cr2+/+ donors corrected the defect, demonstrating that the defect was due to B cells themselves. These results indicate an obligatory role of B cell complement receptors in responses of the B cells to protein antigens.

SummaryFoxp3+ T regulatory (Treg) cells regulate immune responses and maintain self-tolerance. Recent work shows that Treg cells are comprised of many subpopulations with specialized regulatory functions. Here we identified Foxp3+ T cells expressing the coinhibitory molecule TIGIT as a distinct Treg cell subset that specifically suppresses proinflammatory T helper 1 (Th1) and Th17 cell, but not Th2 cell responses. Transcriptional profiling characterized TIGIT+ Treg cells as an activated Treg cell subset with high expression of Treg signature genes. Ligation of TIGIT on Treg cells induced expression of the effector molecule fibrinogen-like protein 2 (Fgl2), which promoted Treg-cell-mediated suppression of T effector cell proliferation. In addition, Fgl2 was necessary to prevent suppression of Th2 cytokine production in a model of allergic airway inflammation. TIGIT expression therefore identifies a Treg cell subset that demonstrates selectivity for suppression of Th1 and Th17 cell but not Th2 cell responses.

SUMMARY Interleukin-27 (IL-27) is an immunoregulatory cytokine that suppresses inflammation through multiple mechanisms, including induction of IL-10, but the transcriptional network mediating its diverse functions remains unclear. Combining temporal RNA profiling with computational algorithms, we predict 79 transcription factors induced by IL-27 in T cells. We validate 11 known and discover 5 positive (Cebpb, Fosl2, Tbx21, Hlx, and Atf3) and 2 negative (Irf9 and Irf8) Il10 regulators, generating an experimentally refined regulatory network for Il10. We report two central regulators, Prdm1 and Maf, that cooperatively drive the expression of signature genes induced by IL-27 in type 1 regulatory T cells, mediate IL-10 expression in all T helper cells, and determine the regulatory phenotype of colonic Foxp3+ regulatory T cells. Prdm1/Maf double-knockout mice develop spontaneous colitis, phenocopying ll10-deficient mice. Our work provides insights into IL-27-driven transcriptional networks and identifies two shared Il10 regulators that orchestrate immunoregulatory programs across T helper cell subsets., Graphical Abstract, In Brief Zhang et al. construct a transcriptional network for IL-27-mediated Il10 production in CD4 T cells, characterize the function of 16 Il10 regulators, and uncover the role of two transcription factors, Prdm1 and Maf, in driving Il10 production in all T helper cells and in maintaining immune homeostasis in the colon.