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To investigate the prevalence and clinical significance of the dense fine speckled (DFS) pattern in a large‐scale cohort of Chinese patients. Data on the antinuclear antibody (ANA) and extractable nuclear antigen (ENA) autoantibody obtained from 165 498 patients who attended Peking Union Medical College Hospital from January 2019 to December 2021 were retrospectively analysed. The prevalence of the DFS pattern was 1.14%, and it mainly appeared in young patients (≤24 years old). A higher positive rate of the DFS pattern was observed in patients with dermatosis (18.12%) and systemic autoimmune rheumatic diseases (SARDs) (13.53%). The DFS pattern titre was mostly low or medium (≤1:160). A higher titre was associated with an increased risk of SARDs (p <.001), dermatosis (p =.015) and pulmonary disease (p =.016). In 37 patients with ENA autoantibody positivity, anti‐SSA antibody was the most common (2.55%). If the low titre (<1:160) or the DFS pattern with negative ENA autoantibody were to be used as exclusion criteria for SARDs, the diagnosis would have been missed in 42 or 77 patients, respectively. The prevalence of the DFS pattern was low in ANA test samples and was more common in patients with dermatosis and SARDs, but the titre was usually higher in patients with SARDs. There was no evidence that the DFS pattern could be used as an exclusion criterion for SARDs diagnosis. The DFS pattern was associated with certain pathological states, which may inform the clinical significance of the DFS pattern. [ABSTRACT FROM AUTHOR]

[Display omitted] • G-CSF enhances the immunosuppressive function of MDSCs in the donor's peripheral blood. • MDSCs in grafts undergoing transplantation in hematologic patients affect patient prognosis. • The equilibrium range of absolute values of total MDSCs in the patient's graft was (1.7–4.3) × 107/kg. • The transfer of grafts with high levels of MDSCs to the patient's body is beneficial for the development speed of MDSCs. To discuss the effects of mobilization of healthy donors with granulocyte colony-stimulating factor (G-CSF) on the absolute values and functions of myeloid-derived suppressor cells (MDSCs) and subpopulations of M-MDSCs and P-MDSCs in their peripheral blood. In addition, this study also aims to investigate the impacts of the adoptively transferred MDSCs from the grafts to the patients on their prognosis and immune reconstitution. The selection of 72 donors and 72 patients were conducted for allogeneic hematopoietic stem cell transplantation (allo-HSCT) from August 2022 to December 2022 at Lu Daopei Hospital in Beijing, China. Statistical calculations were performed by Wilcoxon signed-rank test, Kruskal Wallis test, χ2 test, Kaplan Meier test, and log-rank test to analyze the data. G-CSF induced significant amplification of MDSCs in the peripheral blood of donors in percentage and absolute values. Whether the level of P-MDSCs in patients conducted for the adoptive transfer of P - MDSCs is higher than 3.7× 107/kg or lower than 1.4× 107/kg leads to a poor prognosis of the patients. Ensuring a balanced state of MDSCs is crucial for effective immunotherapy. Transferring a high level of MDSCs from the graft to the patient's body is advantageous for the development of MDSCs while simultaneously inhibiting the proliferation of lymphocyte subgroups. [ABSTRACT FROM AUTHOR]

PM 2.5 is the main component of most haze, and the presence of high concentrations of PM 2.5 in the air for an extended time can cause serious effects on human health, so there is an urgent need for research work related to PM 2.5. Traditional PM 2.5 monitoring uses ground-based monitoring stations with low spatial resolution. Other studies have retrieved the Moderate Resolution Imaging Spectroradiometer aerosol optical depth product by the dark-target algorithm. However, the estimated PM 2.5 concentration on the ground will produce missing values, which will lead to the reduction of spatial and temporal resolution. Based on this, this study proposes a machine learning algorithm to estimate PM 2.5 by using the fifth generation reanalysis (ERA5) data set published by the European Center for Medium-range Weather Forecasts (ECMWF). In this study, two different methods of back propagation neural network (BPNN) and random forest (RF) were used to develop the models. Firstly, the meteorological parameters (precipitable water vapor, water vapor pressure and relative humidity, etc.) and pollution parameters (O 3 , CO, NO 2 , SO 2 , PM 10 , and PM 2.5) were used to establish PM 2.5 model in 2021. The results showed that the R2 and RMSE for BPNN and RF were 0.94/0.96 and 10.37/8.77 µg/m3, respectively. Then, due to the lack and the low spatial resolution of the pollution parameters, using only the ERA5 meteorological data with the high spatiotemporal resolution to develop the PM 2.5 model in winter, the R2 of the RF model (0.93) was 0.05 higher and the RMSE (12.50 µg/m3) was 4.19 µg/m3 lower than that of the BPNN model, which indicates that it is feasible to develop the PM 2.5 model using only meteorological parameters. Finally, using the RF model of the second stage and ERA5 meteorological data with a spatial resolution of 0.05° (obtained by cubic spline interpolation) to generate the hourly PM 2.5 map of Beijing and compare it with China High Air Pollutants dataset, the R2 and RMSE of Beijing were 0.78 µg/m3 and 14.85 µg/m3, respectively. On this basis, it is found that the areas with high PM 2.5 concentration are close to the areas with serious pollution in Hebei Province by analyzing the PM 2.5 map of Beijing, and area transport and human activities are important sources of air pollution. [ABSTRACT FROM AUTHOR]

In July 2012, symptoms of irregular mosaic stripe and mottle were observed on maize leaves in field in Beijing, China. The causal pathogen was identified to be Cucumber mosaic virus ( CMV) based upon reverse transcription- PCR, enzyme-linked immunosorbent assay, Western blotting and fulfilment of Koch's postulates. The isolate was named ZMBJ- CMV. Full sequence of ZMBJ- CMV RNA3 was determined, and it had the highest identity to that of strain K- CMV (95.03%) and SD- CMV (94.96%). Phylogenetic analysis revealed ZMBJ- CMV clustered with K- CMV and SD- CMV in subgroup IB. To our knowledge, this is the first report on the natural infection and phylogenetic analysis of CMV on maize in China. [ABSTRACT FROM AUTHOR]

Correct understanding of groundwater/surface-water (GW-SW) interaction in karst systems is of greatest importance for managing the water resources. A typical karst region, Fangshan in northern China, was selected as a case study. Groundwater levels and hydrochemistry analyses, together with isotope data based on hydrogeological field investigations, were used to assess the GW-SW interaction. Chemistry data reveal that water type and the concentration of cations in the groundwater are consistent with those of the surface water. Stable isotope ratios of all samples are close to the local meteoric water line, and the H concentrations of surface water and groundwater samples are close to that of rainfall, so isotopes also confirm that karst groundwater is recharged by rainfall. Cross-correlation analysis reveals that rainfall leads to a rise in groundwater level with a lag time of 2 months and groundwater exploitation leads to a fall within 1 month. Spectral analysis also reveals that groundwater level, groundwater exploitation and rainfall have significantly similar response periods, indicating their possible inter-relationship. Furthermore, a multiple nonlinear regression model indicates that groundwater level can be negatively correlated with groundwater exploitation, and positively correlated with rainfall. The overall results revealed that groundwater level has a close correlation with groundwater exploitation and rainfall, and they are indicative of a close hydraulic connection and interaction between surface water and groundwater in this karst system. [ABSTRACT FROM AUTHOR]

Beijing is an international metropolis, where over-exploration of water resource makes land subsidence becoming more and more serious. The related problems cannot be avoided in the coming years because of the giant increase of population. The aims of this study are to quantify land subsidence over the period 2003 to 2010, grasp the evolution of the process, and investigate the relation with the triggering factors in the northern area of the Beijing plain. Various data, including deep compaction from vertical multiple borehole extensometers, land subsidence from Persistent Scatterer Interferometry and leveling surveys, groundwater levels, hydrogeological setting from wellbores, and Landsat TM image were collected and effectively used to detect the spatial and temporal features of land subsidence and its possible relation with groundwater level changes, compressible layer thickness, and urban development. Results show that land subsidence is unevenly distributed and continuously increased from 2003 to 2010. The average loss of elevation over the monitoring period amounted to 92.5 mm, with rates up to 52 mm/y. The distribution of the subsidence bowl is only partially consistent with that of the groundwater depression cone because of the variable thickness of the most compressible fine deposits. In fact, extensometers reveal that silty-clay layers account for the larger contribution to land subsidence, with the 15 m thick silty-clay layer between 102 and 117 m depth accounting for about 25% of the total subsidence. Finally, no clear correlation has been observed between the subsidence rates and the increase of the load on the land surface connected to the impressive urban development. This study represents a first step toward the development of a physically-based model of the subsidence occurrence to be used for planning remediation strategies in the northern Beijing plain. [ABSTRACT FROM AUTHOR]

Abstract: Forty passive air samplers were deployed to study the occurrence of gas and particulate phase PAHs in remote, rural village and urban areas of Beijing–Tianjin region, North China for four seasons (spring, summer, fall and winter) from 2007 to 2008. The influence of emissions on the spatial distribution pattern of air PAH concentrations was addressed. In addition, the air–soil gas exchange of PAHs was studied using fugacity calculations. The median gaseous and particulate phase PAH concentrations were 222ng/m3 and 114ng/m3, respectively, with a median total PAH concentration of 349ng/m3. Higher PAH concentrations were measured in winter than in other seasons. Air PAH concentrations measured at the rural villages and urban sites in the northern mountain region were significantly lower than those measured at sites in the southern plain during all seasons. However, there was no significant difference in PAH concentrations between the rural villages and urban sites in the northern and southern areas. This urban–rural PAH distribution pattern was related to the location of PAH emission sources and the population distribution. The location of PAH emission sources explained 56%–77% of the spatial variation in ambient air PAH concentrations. The annual median air–soil gas exchange flux of PAHs was 42.2ng/m2/day from soil to air. Among the 15 PAHs measured, acenaphthylene (ACY) and acenaphthene (ACE) contributed to more than half of the total exchange flux. Furthermore, the air–soil gas exchange fluxes of PAHs at the urban sites were higher than those at the remote and rural sites. In summer, more gaseous PAHs volatilized from soil to air because of higher temperatures and increased rainfall. However, in winter, more gaseous PAHs deposited from air to soil due to higher PAH emissions and lower temperatures. The soil TOC concentration had no significant influence on the air–soil gas exchange of PAHs. [Copyright &y& Elsevier]

Background: Quantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions. As the largest urbanized megalopolis region in northern China, the Beijing-Tianjin-Hebei (Jing-Jin-Ji, JJJ) region (population: 112.7 million) is under considerable pressure to reduce carbon emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the CO2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies. Results: Here, we collected and analyzed 8 published emission inventories to assess the emissions and uncertainty at the JJJ city level. The results showed that a large discrepancy existed in the JJJ emissions among downscaled country-level emission inventories, with total emissions ranging from 657 to 1132 Mt CO2 (or 849 ± 214 for mean ± standard deviation (SD)) in 2012, while emission estimates based on provincial-level data estimated emissions to be 1038 and 1056 Mt. Compared to the mean emissions of city-data-based inventories (989 Mt), provincial-data-based inventories were 6% higher, and national-data-based inventories were 14% lower. Emissions from national-data-based inventories were 53–75% lower in the high-emitting industrial cities of Tangshan and Handan, while they were 47–160% higher in Beijing and Tianjin than those from city-data-based inventories. Spatially, the emissions pattern was consistent with the distribution of urban areas, and urban emissions in Beijing contributed 50–70% of the total emissions. Higher emissions from Beijing and Tianjin resulted in lower estimates of prefectural cities in Hebei for some national inventories. Conclusions: National-level data-based emission inventories produce large differences in JJJ prefectural city-level emission estimates. The city-level statistics data-based inventories produced more consistent estimates. The consistent spatial distribution patterns recognized by these inventories (such as high emissions in southern Beijing, central Tianjin and Tangshan) potentially indicate areas with robust emission estimates. This result could be useful in the efficient deployment of monitoring instruments, and if proven by such measurements, it will increase our confidence in inventories and provide support for policy makers trying to reduce emissions in key regions. [ABSTRACT FROM AUTHOR]