[Impacts of Changes in Meteorological Conditions During COVID-19 Lockdown on PM2.5 Concentrations over the Jing-Jin-Ji Region].

The Chinese government triggered the immediate implementation of a lockdown policy in China following the outbreak of the COVID-19 pandemic, leading to drastic decreases in air pollutant emissions. However, concentrations of PM2.5 and other pollutants increased during the COVID-19 lockdown over the Jing-Jin-Ji region compared with those averaged over 2015-2019, and two PM2.5 pollution events occurred during the lockdown. Using the ERA5 reanalysis data, we found that the Jing-Jin-Ji region during the COVID-19 lockdown was characterized by higher relative humidity, lower planetary boundary layer height, and anomalous updraft. These conditions were favorable for condensation and the secondary formation of aerosols and prevented turbulent diffusion of pollutants. Furthermore, we conducted sensitivity tests using the WRF-Chem model and found that ρ(PM2.5) increased by 20-55 µg·m-3(60%-170%) over the middle region of Jing-Jin-Ji during the COVID-19 lockdown due to changes in meteorological conditions. Furthermore, the enhanced aerosol chemistry and unfavorable diffusion conditions were identified as the key factors driving increases in PM2.5 concentrations during the lockdown. Planetary boundary layer height and relative humidity may become the important factors in forecasting PM2.5 pollution events over the Jing-Jin-Ji region under the background of emission reduction.

[Similarities and Differences of Valley Winds in the Beijing Plain and Yanqing Areas and Its Impact on Pollution].

Under certain terrain and weather conditions, mountain-valley circulation is one of the main meteorological factors affecting aerosol pollution in plain-mountain area. Based on environmental monitoring data and multi-source meteorological data for the Beijing-Tianjin-Hebei region between 2015 and 2019, the characteristics, similarities, and differences of mountain-valley winds in the Beijing Plain and Yanhuai Basin regions were compared. The results show that the mountain-valley winds recorded at the Beijing Observatory are from southwest to northeast compared to from the southeast to northeast at Yanqing station. With the aggravation of pollution levels, the mountain-valley wind intensity decreased by 17.7%-32.4%. When the wind speed at Beijing Observatory was 2-6 m·s-1, the maximum PM2.5 concentration in southeast was 83 µg·m-3, which was higher than in the southwest. When the wind speed at the Yanqing station was 2-6 m·s-1, the PM2.5 concentrations in SE-SSE area was 20-40 µg·m-3 higher than in other directions, and the concentrations in the valley winds were 10-12 µg·m-3 higher than the average value for the last five years. Taking the typical heavy pollution event on March 5-8, 2015, as an example, the influence of mountain-valley winds is mainly reflected in the high humidity and regional transmission of southeast winds during the valley wind stage. The PM2.5 concentrations at the Yanqing station increased by 100-130 µg·m-3 during the valley wind stage on March 6 and 7, 2015. The inversion temperature developed to 1000 m during the mountain wind stage, the local dew point at the Beijing Observatory and the Yanqing station rose by approximately 18℃. The peak dew point at the Yanqing station occurring 2 hours after the Beijing Observatory, and the concentrations of PM2.5 rose slightly under high humidity conditions. Meanwhile, the thermal gradient between the 400-m-high Yanqing Station and Yudu Mountain gradually decreased, and the mountain-valley wind decreased by 8% and 6%, respectively. The weakening of local circulation may be related to the bidirectional feedback mechanism of the boundary layer and high concentrations of aerosols.

[Characteristics of VOCs and Their Roles in Ozone Formation at a Regional Background Site in Beijing, China].

As important precursors of near-surface ozone, secondary organic aerosols (SOAs), and volatile organic compounds (VOCs) play an important role in photochemical reactions and fine particle formation. In this study, real-time VOCs were measured continuously by Syntech Spectras GC955 analyzers at the regional background site of the North China Plain from September 1 to 27, 2017. The VOC concentration levels, compositions, spatiotemporal variations, and the ozone formation potential during the observation period were investigated. The potential sources of initial VOCs indicated from the diagnostic ratios were further studied. The averaged total mixing ratio of VOCs was 12.53×10-9. Among all measured VOC species, alkanes were the most abundant species, which accounted for 65.3% of the total concentrations, followed by alkenes (26.7%) and aromatics (6.5%). In addition, the total OH radical loss rate of VOCs (L·OH) was 5.2 s-1. In particular, the contribution of C4-C5 alkenes to L·OH was as high as 61%, followed by C2-C3 alkenes, with a 12.8% contribution of L·OH. The average ozone formation potential of VOCs was 36.5×10-9. Among all the measured VOC species, alkenes were the most abundant species, which accounted for 71.2%. Among alkenes, the contribution of C4-C5 alkenes was the most prominent. Although the concentration of alkanes in Shangdianzi was much higher than other VOC species, the ozone formation potential was lower. Diagnostic ratios and source implications suggested that Shangdianzi was affected mainly by biomass/biofuel/coal burning, with substantially elevated benzene levels during the observation period, whereas a slight influence of traffic-related emissions was observed.

[Contribution Assessment of Meteorology Conditions and Emission Change for Air Quality Improvement in Beijing During 2014-2017].

During 2014-2017, the number of haze days and air pollution days declined year by year obviously in Beijing. The average mass concentrations of PM2.5, PM10, SO2, and NO2 also decreased with the alleviated pollution level. These decreases were more obvious during the heating period, especially in November and December. In order to analyze the reasons for the improvement of air quality, changes of the meteorological factors and emission-reduction have been discussed and quantified in this study. This work was based on the numerical simulation model WRF-CHEM and the large data mining technologies of k-nearest neighbor (KNN) and support vector machines (SVM). Meteorological observations indicated that the mean wind speed of 2017 increased by 7.9% compared with the last three years. The frequency of hourly wind speed higher than 3.4 m·s-1 was the highest (10.6%), and frequency of daily relative humidity higher than 70% was lowest (25.1%), in 2017. Meanwhile, the number of low wind days (daily wind speed lower than 2 m·s-1), environmental capacity, ventilation index, and height of the boundary layer showed that the diffusion conditions were better in the heating period of 2017 than those of 2014~2016, especially in November and December. The accumulated precipitation during the non-heating period was 558.3 mm in 2017, which is conducive to pollutant removal and wet deposition. Inter-annual changes of meteorological conditions are important to the air quality. A simulation for December 1~19 by WRF-CHEM during 2014-2017 was performed, and the results demonstrated that changes of meteorological conditions led to a reduction of the PM2.5 concentration of 2017 by 5%, 38%, and 25% compared with that of 2014-2016, respectively. However, it was not possible to quantify the specific contributions of meteorology conditions because of the lack of real emission reduction options. The KNN and SVM models are applied in this study based on the observed meteorology factors, haze days, and pollution days, and it was found that for the reduced haze days and heavy pollution days in 2017, 65.0% could be attributed to emission reduction and 35.0% was caused by improvement of the meteorological conditions.

Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma.

AIM: Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed. MATERIALS & METHODS: We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein-protein interaction networks, weighted gene co-expression network analysis and genes' cancer/testis expression pattern. We also further characterized these genes using data from the Cancer Genome Atlas (TCGA) project and gene ontology annotation. RESULTS: Cell cycle-related pathways were significantly enriched in upregulated genes in ATC. We identified TRIP13, DLGAP5, HJURP, CDKN3, NEK2, KIF15, TTK, KIF2C, AURKA and TPX2 as cell cycle-related key genes with cancer/testis expression pattern. We further uncovered that most of these putative key genes were critical components during chromosome segregation. CONCLUSION: We predicted several key genes harboring potential therapeutic value in ATC. Cell cycle-related processes, especially chromosome segregation, may be the key to tumorigenesis and treatment of ATC.

Research progress of lL - 6 and diabetic retinopathy / 国际眼科杂志(Guoji Yanke Zazhi)

?ln recent years, the number of patients with diabetes increase rapidly. Diabetic retinopathy ( DR ) , one of the complications of diabetes, is also the important aspect of current and future prevention of blindness in our country. Now, more and more scholar have noticed the important role of immune inflammation in the pathogenesis of diabetic retinopathy. ln this article, we reviewed the role of interleukin-6 ( lL-6 ) in diabetic retinopathy.