Ferroptosis: a new target for iron overload-induced hemophilic arthropathy synovitis.

Iron deposition is closely related to developing haemophilic arthropathy (HA). Studying the relationship between ferroptosis signal expression and iron overload in HA synovium facilitates understanding the pathogenesis of joint synovial hyperplasia in bloodborne arthritis and the development of new protective methods. The knee synovium was collected from HA and osteoarthritis (OA) patients, and pathological changes were analysed by HE and Prussian blue staining. Ferroptosis phenotypes were examined by immunohistochemistry and western blotting. Moreover, ferric ammonium citrate (FAC)-induced was used to construct an in vitro iron overload model to investigate the relationship between iron overload and ferroptosis in synovial fibroblasts (FLS). Furthermore, the factors influencing ferroptosis in FLS were explored. Iron deposition, cell proliferation, and vascular proliferation in the synovium of HA were more obvious. Ferroptosis in HA synovium appears to inhibit. FLS ferroptosis increased with iron accumulation, malondialdehyde (MDA) in cells, and glutathione (GSH) depletion. TNF-α plays a protective role in this process. Blocking the action of TNF-α and inducing ferroptosis significantly reduced synovial proliferation. TNF-α inhibitors combined with a ferroptosis inducer may be a new therapeutic method for HA synovitis.

Surface-enhanced Raman imaging through sprayed probes for the application in chemical visualization of methamphetamine within fingerprints.

For fingerprint-involved forensic investigations, cyanoacrylates and inorganic nanophosphors are mostly used for fingerprint visualization. However, methods to simultaneously report fingerprint images and the corresponding specific chemical information have yet to be realized. In this work, chemical visualization of the analytes in fingerprints is achieved through surface-enhanced Raman spectroscopy (SERS) measurements with the aid of spray-dispersed gold nanorods (AuNRs). The optimal coverage of AuNRs was studied by theoretical simulations and experimental operations. A rapid sampling of fingerprints with the chemical of interest was developed by tuning the spray parameters. In particular, the SERS imaging of methamphetamine in fingerprint latent was attempted by addressing the SERS spectral features of methamphetamine. This chemical visualization method reflects both the graphical and chemical characteristics of fingerprints in a single batch measurement, in which methamphetamine can be detected and mapped at the concentration of 10-5 M. The data processing approach was also modified by employing relevant logical judgments. The improved SERS images with sharpened patterns of fingerprints were obtained by involving the scored multi-peak judgments.

Ultrafast synthesis of laccase-copper phosphate hybrid nanoflowers for efficient degradation of tetracycline antibiotics.

The presence of antibiotics in the environment causes increasing attention due to their potential risks to ecosystems and public health. Laccases are versatile oxidases capable of degrading various organic contaminants including pharmaceuticals. However, the performance of bacterial laccases on tetracycline antibiotics (TCs) degradation is seldom investigated. In this work, a bacterial laccase from Bacillus amyloliquefaciens was immobilized as laccase-inorganic hybrid nanoflowers (Lac-hNFs) by a facile and rapid method. The immobilized laccase was employed to remove different TCs including tigecycline, which is a third-generation TC that its degradation by laccase has not been reported. Lac-hNFs were synthesized by sonication-mediated self-assembly of laccase and copper ions in 5 min at room temperature. About 95% of laccase could be encapsulated in the nanoflowers, and the obtained Lac-hNFs exhibited great enhancement in stability under harsh conditions. The immobilized laccase showed a half-life of 11.7 h at 60 °C, which was about 1.4-fold higher than that of the free enzyme. Meanwhile, Lac-hNFs retained 81% of the initial activity after incubation at 25 °C for 10 days. The laccase in combination with acetosyringone could efficiently decompose tetracycline, doxycycline, and tigecycline. More than 79% of the three TCs were transformed in 1 h. Compared with the free enzyme, Lac-hNFs demonstrated higher capacity in the removal of TCs. Furthermore, Lac-hNFs remained their high degradation capacity after five cycles of reuse. Bacterial growth inhibition test revealed that most of the toxicity of TCs was eliminated after Lac-hNFs treatment. The main transformation products were identified by LC-MS, and the possible degradation pathways were proposed. The interaction mechanism between laccase and TCs was also analyzed using molecular docking. This work provides an efficient way to remove toxic organic pollutants.

Recent Progress in Atmospheric Chemistry Research in China: Establishing a Theoretical Framework for the "Air Pollution Complex".

Atmospheric chemistry research has been growing rapidly in China in the last 25 years since the concept of the "air pollution complex" was first proposed by Professor Xiaoyan TANG in 1997. For papers published in 2021 on air pollution (only papers included in the Web of Science Core Collection database were considered), more than 24 000 papers were authored or co-authored by scientists working in China. In this paper, we review a limited number of representative and significant studies on atmospheric chemistry in China in the last few years, including studies on (1) sources and emission inventories, (2) atmospheric chemical processes, (3) interactions of air pollution with meteorology, weather and climate, (4) interactions between the biosphere and atmosphere, and (5) data assimilation. The intention was not to provide a complete review of all progress made in the last few years, but rather to serve as a starting point for learning more about atmospheric chemistry research in China. The advances reviewed in this paper have enabled a theoretical framework for the air pollution complex to be established, provided robust scientific support to highly successful air pollution control policies in China, and created great opportunities in education, training, and career development for many graduate students and young scientists. This paper further highlights that developing and low-income countries that are heavily affected by air pollution can benefit from these research advances, whilst at the same time acknowledging that many challenges and opportunities still remain in atmospheric chemistry research in China, to hopefully be addressed over the next few decades.

FGF23 and SOX9 expression in haemophilic cartilage: In vitro studies of the effects of iron.

INTRODUCTION: Clarifying the links between iron and FGF23, SOX9 expression in chondrocytes would be helpful for comprehending articular cartilage degradation pathogenesis in blood-induced arthritis and exploring new protective methods. AIM: The purpose of this study was to determine iron regulation of fibroblast growth factor 23 (FGF23) and SRY-box 9 (SOX9) in human chondrocytes, an area which is unexplored in blood-induced arthritis cartilage degradation pathogenesis. METHODS: Expression of FGF23, SOX9, MMP13 and collagen Ⅱ in articular cartilage of patients with osteoarthritis (OA) or haemophilic arthritis (HA) was determined by western blot (WB). Iron-induced FGF23 and SOX9 mRNA and protein expression in primary human normal chondrocyte cells (HUM-iCell-s018) was quantified by qRT-PCR and WB, respectively. RESULTS: We found that compared with OA patients, the expression of FGF23, MMP13 in articular cartilage of patients with HA was up-regulated, while the expression of SOX9, collagen Ⅱ was down-regulated. Iron-induced FGF23 and suppressed SOX9 expression in chondrocytes in a dose-dependent manner. CONCLUSIONS: These findings demonstrated that iron was involved in hemophilic cartilage lesion directly via changing cartilage phenotype through regulation of FGF23 and SOX9 expression in chondrocytes.

Pathological changes and expression of lysine oxidases and matrix metalloproteinases -1, -2, and -3 in ligaments of patients with haemophilic arthritis.

INTRODUCTION: Studying the pathological changes of ligaments in patients with haemophilic arthritis (HA) has important significance for guiding the release of ligaments during total knee arthroplasty (TKA) and exploring interventions to prevent ligament lesions. AIM: This study was conducted to show the pathological changes and investigate the lysine oxidase (LOX) and matrix metalloproteinase (MMP)-1, -2, and -3 levels in the ligaments of patients with HA compared with those of patients with osteoarthritis (OA). METHODS: Ligaments obtained during the TKA were stained with Masson trichrome, Verhoeff-Van Gieson and haematoxylin and eosin to show the basic pathological changes. Collagen I, elastin, LOXs and MMP-1, -2, and -3 expression levels were detected via western blot. LOX and MMP-1, -2, and -3 mRNA expression levels were analysed via quantitative real-time PCR. RESULTS: Compared with OA ligaments, HA ligaments were constructed more loosely with wider gaps, more breaks, haemocytodeposition and local hypertrophy among the fibres. LOXs and MMP mRNA expression levels were upregulated in the HA tissues, which was consistent with the western blot results. Collagen I and elastin levels were also higher in patients with HA. CONCLUSIONS: The metabolism of the ligaments in patients with HA is more complex than in those with OA, and the ligaments of patients with HA have stronger healing and destruction processes. This pathology is related to iron overload and imbalanced inflammatory factors due to repeated intra-articular bleeding.

Pre-colectomy location and TNM staging of colon cancer by the computed tomography colonography: a diagnostic performance study.

BACKGROUND: The Chinese Society of Clinical Oncology guidelines 2018 and the recent update of that (version 2020) recommends accurate examination before major treatment for decision(s) in cases of colon cancer. Also, the difficulty in the identification of the lesion during colectomy may lead to resection of a wrong segment of the colon or a more extensive resection than planned. Accurate pre-colectomy local staging of colon cancer is required to make decisions for treatment of colon cancer. The objective of the study was to evaluate the diagnostic performance of the computed tomography colonography (CTC) for pre-colectomy tumor location and tumor, node, and metastasis (TNM) staging of colon cancer. METHODS: Data of preoperative colonoscopies, CTC, surgeries, and surgical pathology of a total of 269 patients diagnosed with colon cancer by colonoscopy and biopsy and underwent pre-colectomy location and TNM staging by CTC were collected and analyzed. The consistency between the radiological and the surgery/surgical-pathological for location and TN stages of colon tumor were estimated with the weighted kappa or kappa coefficient (κ) at 95% confidence interval (CI). RESULTS: CTC detected 261 (93%) and colonoscopy detected 201 (72%) correct locations of tumors. Sensitivity and accuracy of CTC for detection of location of colon tumors were 100% and 92.58% (κ = 0.89; 95% Cl: 0.83-0.95). 72.48% sensitivity, 90.64% specificity, and 83.57% accuracy were reported for CTC in differentiation of tumors confined to the colon wall (T1/T2) from advanced tumors (T3/T4) (κ = 0.69, 95% Cl: 0.51-0.75). 81.01% sensitivity, 89.11% specificity, and 83.93% accuracy of CTC was reported for differentiation of tumors between low-intermediate risk and high risk (κ = 0.68, 95% Cl: 0.53-0.75). 69.31% sensitivity, 66.15% specificity, and 67.14% accuracy of CTC were reported for N staging of tumors (κ = 0.41, 95% Cl: 0.59-0.69). CONCLUSIONS: CTC has high diagnostic parameters for pre-colectomy location and T staging of colon tumors except patients of colon cancer who received neoadjuvant chemotherapy. LEVEL OF EVIDENCE: III. TECHNICAL EFFICACY STAGE: 2.

Variation in PM2.5 sources in central North China Plain during 2017-2019: Response to mitigation strategies.

Central North China Plain (NCP) is one of the most important source region of air pollutants over the Beijing-Tianjin-Hebei (BTH) region. The national government has issued abatement measures to improve the air quality in this area from 2017. To examine the effects of control measures, observational analysis on PM2.5 characteristics was performed in a city of central NCP during 2017-2019 to investigate the variation in mass concentration, chemical composition, and emission source of PM2.5. Annual PM2.5 concentration significantly reduced by 16% from 2017 to 2019, implying substantial improvements in air quality. PM2.5 enriched in autumn-winter seasons was dominated by SNA (sum of sulfate, nitrate and ammonium; ~38%), followed by organic carbon matters (OM; ~24%) and fine soil (FS; ~12%). This chemical composition was different from that in a megacity in NCP (Beijing) where OM accounted for a comparable fraction to SNA. Approximately half of SNA was attributed to nitrate, indicating that SNA changed from sulfate-driven to nitrate-driven, and the considerable effects of coal combustion cutoff, in which sulfate was concentrated. Decreased mass fraction of SNA and increased OM fraction in PM2.5 were observed in 2018-2019 partly contributed to the decrease in PM2.5. A progressive increase in the contribution of heterogeneous formed SNA whilst a decrease in OM was observed as the pollution elevated from clean to heavily polluted. Six sources (soil dust, biomass burning, secondary emission, road traffic, coal combustion and industry) were identified by the Positive Matrix Factorization (PMF) model in both years and dominated by secondary aerosols, respectively contributing 39% and 41% to PM2.5. The decreasing concentrations (with reductions of 17%-61%) of the secondary source, coal combustion, soil dust and biomass burning largely accounted for the reduction in PM2.5, as a consequence of the recent abatement measures. By contrast, contributions of vehicle-related emissions, similar to the increasing contribution of vehicles at sites in NCP after 2013, should receive increased attention.

Spatial Distribution and Environmental Risk of Arsenic and Antimony in Soil Around an Antimony Smelter of Qinglong County.

The purpose of this study was to investigate the distribution of arsenic (As) and antimony (Sb) in soils around an antimony smelter at Qinglong together with the soil pollution levels and potential ecological risk. The results show that (1) total concentrations of As (23 ~ 539 mg/kg) and Sb (19.7 ~ 5681 mg kg-1) were higher than the Guizhou province-level background values (As, 20; Sb, 2.24), especially Sb. Their dominant geochemical speciation was the residual fraction which accounted for > 90% of the total concentrations. (2) The distribution of As and Sb in soils influenced mainly by land-use type, altitude, predominant wind direction, and distance from the pollution source. (3) The geo-accumulation index shows that the soil was highly contaminated with Sb and moderately with As. The potential ecological risk index shows that As posed a moderate risk and Sb a high risk. The general ecological risk was classified as high risk. However, the risk index coding method shows low environmental risk from As and Sb.

Development and validation of an RNA binding protein-associated prognostic model for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is among the deadliest forms of cancer. While RNA-binding proteins (RBPs) have been shown to be key regulators of oncogenesis and tumor progression, their dysregulation in the context of HCC remains to be fully characterized. METHODS: Data from the Cancer Genome Atlas - liver HCC (TCGA-LIHC) database were downloaded and analyzed in order to identify RBPs that were differentially expressed in HCC tumors relative to healthy normal tissues. Functional enrichment analyses of these RBPs were then conducted using the GO and KEGG databases to understand their mechanistic roles. Central hub RBPs associated with HCC patient prognosis were then detected through Cox regression analyses, and were incorporated into a prognostic model. The prognostic value of this model was then assessed through the use of Kaplan-Meier curves, time-related ROC analyses, univariate and multivariate Cox regression analyses, and nomograms. Lastly, the relationship between individual hub RBPs and HCC patient overall survival (OS) was evaluated using Kaplan-Meier curves. Finally, find protein-coding genes (PCGs) related to hub RBPs were used to construct a hub RBP-PCG co-expression network. RESULTS: In total, we identified 81 RBPs that were differentially expressed in HCC tumors relative to healthy tissues (54 upregulated, 27 downregulated). Seven prognostically-relevant hub RBPs (SMG5, BOP1, LIN28B, RNF17, ANG, LARP1B, and NR0B1) were then used to generate a prognostic model, after which HCC patients were separated into high- and low-risk groups based upon resultant risk score values. In both the training and test datasets, we found that high-risk HCC patients exhibited decreased OS relative to low-risk patients, with time-dependent area under the ROC curve values of 0.801 and 0.676, respectively. This model thus exhibited good prognostic performance. We additionally generated a prognostic nomogram based upon these seven hub RBPs and found that four other genes were significantly correlated with OS. CONCLUSION: We herein identified a seven RBP signature that can reliably be used to predict HCC patient OS, underscoring the prognostic relevance of these genes.

Whole-Genome Sequencing Reveals Diverse Models of Structural Variations in Esophageal Squamous Cell Carcinoma.

Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs.

Rapid Adaptation for Active Pantograph Control in High-Speed Railway via Deep Meta Reinforcement Learning.

Active pantograph control is the most promising technique for reducing contact force (CF) fluctuation and improving the train's current collection quality. Existing solutions, however, suffer from two significant limitations: 1) they are incapable of dealing with the various pantograph types, catenary line operating conditions, changing operating speeds, and contingencies well and 2) it is challenging to implement in practical systems due to the lack of rapid adaptability to a new pantograph-catenary system (PCS) operating conditions and environmental disturbances. In this work, we alleviate these problems by developing a revolutionary context-based deep meta-reinforcement learning (CB-DMRL) algorithm. The proposed CB-DMRL algorithm combines Bayesian optimization (BO) with deep reinforcement learning (DRL), allowing the general agent to adapt to new tasks quickly and efficiently. We evaluated the CB-DMRL algorithm's performance on a proven PCS model. The experimental results demonstrate that meta-training DRL policies with latent space swiftly adapt to new operating conditions and unknown perturbations. The meta-agent adapts quickly after two iterations with a high reward, which require only ten spans, approximately equal to 0.5 km of PCS interaction data. Compared with state-of-the-art DRL algorithms and traditional solutions, the proposed method can promptly traverse scenario changes and reduce CF fluctuations, resulting in an excellent performance.

Disentangling sources and transformation mechanisms of nitrogen, sulfate, and carbon in water of a Karst Critical Zone.

In the Karst Critical Zone (KCZ), mining and urbanization activities produce multiple pollutants, posing a threat to the vital groundwater and surface water resources essential for drinking and irrigation. Despite their importance, the interactions between these pollutants in the intricate hydrology and land use of the KCZ remain poorly understood. In this study, we unraveled the transformation mechanisms and sources of nitrogen, sulfate, and carbon using multiple isotopes and the MixSIAR model, following hydrology and surface analyses conducted in spatial modelling with ArcGIS. Our results revealed frequent exchange between groundwater and surface water, as evidenced by the analysis of δD-H2O and δ18O-H2O. Nitrification predominantly occurred in surface water, although denitrification also made a minor contribution. Inorganic nitrogen in both groundwater and surface water primarily originated from soil nitrogen (48 % and 49 %, respectively). Sewage and manure were secondary sources of inorganic nitrogen in surface water, accounting for 41 % in urban and 38 % in mining areas. Notably, inorganic sulfur oxidation displayed significant spatial disparities between urban and mining areas, rendering groundwater more susceptible to sulfur pollution compared to surface water. The frequent interchange between groundwater and surface water posed a higher pollution risk to groundwater. Furthermore, the primary sources of CO2 and HCO3- in both groundwater and surface water were water­carbonate reactions and soil respiration. Sulfide oxidation was found to enhance carbonate dissolution, leading to increased CO2 release from carbonate dissolution in the KCZ. These findings enhance our understanding of the transformation mechanisms and interactions of nitrogen, sulfur, and carbon in groundwater and surface water. This knowledge is invaluable for accurately controlling and treating water pollution in the KCZ.

Temporal and spatial distribution characteristics and source analysis of dissolved organic nitrogen in the surface sediment of the Caohai Lake, southwest China.

Caohai Lake is a typical natural lake-type karst plateau wetland, which is sensitive to environmental changes, and the release of dissolved organic nitrogen (DON) in sediment is a potential factor of nitrogen pollution in this lake. Therefore, we aimed to reveal the temporal and spatial distribution characteristics and source analysis of DON in karst lake sediment. Surface sediment samples were collected from Caohai Lake in southwest China, and the sample locations were distributed across almost the entire wetland area, during both the wet and dry seasons. The DON content and fluorescence spectroscopy were determined and analysed using a three-dimensional fluorescence-parallel factor analysis (3DEEM-PARAFAC) model. The mean DON content in the sediment during the dry season (67.79 ± 42.96 mg/kg) was higher than that in the wet season (28.57 ± 20.97 mg/kg). There were four fluorescent components of DON in the sediment: C1 (tyrosine-like protein), C2 (terrestrial humus), C3 (tryptophan-like protein) and C4 (terrestrial humus). The DON in the surface sediment of Caohai Lake was influenced by terrestrial sources and biological activities. These findings help reveal the circulation mechanism of endogenous nitrogen in the lake and provide theoretical support for the prevention and control of nitrogen pollution in Caohai Lake.

Risk Assessment of Heavy Metal in Farmlands and Crops Near Pb-Zn Mine Tailing Ponds in Niujiaotang, China.

To accurately evaluate the pollution and risk of heavy metals in crops and farmlands near mines, we determined the contents of Cr, Ni, Cu, As, Cd, Pb, and Zn in 10 farmland soil sampling sites and six crops (pak choi, rice, spring onion, radish, Chinese cabbage, Chrysanthemum coronarium) in an area near the Niujiaotang Pb-Zn mine in Duyun City, China. Four evaluation methods were compared, including the potential ecological hazard index, Nemeiro comprehensive pollution assessment, risk assessment code, and the ratio of secondary phase to primary phase methods. The average concentration of As, Cd, Pb, and Zn exceeded the soil environmental background levels in Niujiaotang and Guizhou Province. Cd exceeded the standard substantially, and Zn pollution accumulation was the most evident. Heavy metal contamination of crops was in the order pak choi > Chinese cabbage > spring onion > paddy > radish > Chrysanthemum coronarium, whereas heavy metal concentration in crops were in the order Zn > As > Cr > Cd > Ni > Pb. The levels of all heavy metals except Cu exceeded Chinese food hygiene standards. Carcinogenic and non-carcinogenic chemicals in crops present significant risks to adults and children. Risk evaluation considering the morphological contents of heavy metals rather than their total concentration was more accurate for environmental quality assessment of agricultural soils. Samples should be collected at different times to study the spatial and temporal distribution, and further studies on the migration transformation of heavy metals between the tailings pond-soil-crop should be conducted.

Analyzing the impacts of cadmium alone and in co-existence with polypropylene microplastics on wheat growth.

Heavy metals typically coexist with microplastics (MPs) in terrestrial ecosystems. Yet, little is known about how the co-existence of heavy metals and MPs affect crops. Therefore, this study aimed to evaluate the impact of cadmium (Cd; 40 mg/L) alone and its co-existence with polypropylene (PP)-MPs (50 and 100 µm) on seed germination, root and shoot growth, seedling dry weight (DW), and antioxidant enzyme activities of wheat. The study demonstrated that the germination rate of wheat did not vary significantly across treatment groups. Yet, the inhibitory impact on wheat seed germination was strengthened under the co-existence of Cd and PP-MPs, as the effect of a single treatment on seed germination was non-significant. The germination index and mean germination time of wheat seeds were not affected by single or combined toxicity of Cd and PP-MPs. In contrast, Cd and PP-MPs showed synergistic effects on germination energy. Wheat root and shoot length were impeded by Cd alone and in combination with PP-MPs treatments. The DW of wheat seedlings showed significant change across treatment groups until the third day, but on the seventh day, marginal differences were observed. For example, on third day, the DW of the Cd treatment group increased by 6.9% compared to CK, whereas the DW of the 100 µm PP-MPs+Cd treatment group decreased by 8.4% compared to CK. The co-occurrence of Cd and PP-MPs indicated that 50 µm PP-MPs+Cd had an antagonistic impact on wheat seedling growth, whereas 100 µm PP-MPs+Cd had a synergistic impact due to the larger size of PP-MPs. The antioxidant enzyme system of wheat seeds and seedlings increased under single Cd pollution, while the activities of superoxide dismutase, catalase, and peroxidase were decreased under combined pollution. Our study found that Cd adversely affects wheat germination and growth, while the co-existence of Cd and PP-MPs have antagonistic and synergistic effects depending on the size of the PP-MPs.

Radiative effects and feedbacks of anthropogenic aerosols on boundary layer meteorology and fine particulate matter during the COVID-19 lockdown over China.

The COVID-19 epidemic has exerted significant impacts on human health, social and economic activities, air quality and atmospheric chemistry, and potentially on climate change. In this study, an online coupled regional climate-chemistry-aerosol model (RIEMS-Chem) was applied to explore the direct, indirect, and feedback effects of anthropogenic aerosols on radiation, boundary layer meteorology, and fine particulate matter during the COVID-19 lockdown period from 23 January to 8 April 2020 over China. Model performance was validated against a variety of observations for meteorological variables, PM2.5 and its chemical components, aerosol optical properties, as well as shortwave radiation flux, which demonstrated that RIEMS-Chem was able to reproduce the spatial distribution and temporal variation of the above variables reasonably well. During the study period, direct radiative effect (DRE) of anthropogenic aerosols was stronger than indirect radiative effect (IRE) in most regions north of the Yangtze River, whereas IRE dominated over DRE in the Yangtze River regions and South China. In North China, DRE induced larger changes in meteorology and PM2.5 than those induced by IRE, whereas in South China, the changes by IRE were remarkably larger than those by DRE. Emission reduction alone during the COVID-19 lockdown reduced PM2.5 concentration by approximately 32 % on average over East China. As a result, DRE at the surface was weakened by 15 %, whereas IRE changed little over East China, leading to a decrease in total radiative effect (TRE) by approximately 7 % in terms of domain average. The DRE-induced changes in meteorology and PM2.5 were weakened due to emission reduction, whereas the IRE-induced changes were almost the same between the cases with and without emission reductions. By aerosol radiative and feedback effects, the COVID-19 emission reductions resulted in 0.06 °C and 0.04 °C surface warming, 1.6 and 4.0 µg m-3 PM2.5 decrease, 0.4 and 1.3 mm precipitation increase during the lockdown period in 2020 in terms of domain average over North China and South China, respectively, whereas the lockdown caused negligible changes on average over East Asia.

The Universally Conserved Unconventional G Protein YchF Is Critical for Growth and Stress Response.

The ancient guanine nucleotide-binding (G) proteins are a group of critical regulatory and signal transduction proteins, widely involved in diverse cellular processes of all kingdoms of life. YchF is a kind of universally conserved novel unconventional G protein that appears to be crucial for growth and stress response in eukaryotes and bacteria. YchF is able to bind and hydrolyze both adenine nucleoside triphosphate (ATP) and guanosine nucleoside triphosphate (GTP), unlike other members of the P-loop GTPases. Hence, it can transduce signals and mediate multiple biological functions by using either ATP or GTP. YchF is not only a nucleotide-dependent translational factor associated with the ribosomal particles and proteasomal subunits, potentially bridging protein biosynthesis and degradation, but also sensitive to reactive oxygen species (ROS), probably recruiting many partner proteins in response to environmental stress. In this review, we summarize the latest insights into how YchF is associated with protein translation and ubiquitin-dependent protein degradation to regulate growth and maintain proteostasis under stress conditions.

Modeling of secondary organic aerosols (SOA) based on two commonly used air quality models in China: Consistent S/IVOCs contribution but large differences in SOA aging.

Secondary organic aerosol (SOA) is an important component of atmospheric fine particulate matter (PM2.5), with contributions from anthropogenic and biogenic volatile organic compounds (AVOC and BVOC) and semi- (SVOC) and intermediate volatility organic compounds (IVOC). Policymakers need to know which SOA precursors are important but accurate simulation of SOA magnitude and contributions remain uncertain. Findings from existing SOA modeling studies have many inconsistencies due to differing emission inventory methodologies/assumptions, air quality model (AQM) algorithms, and other aspects of study methodologies. To address some of the inconsistencies, we investigated the role of different AQM SOA algorithms by applying two commonly used models, CAMx and CMAQ, with consistent emission inventories to simulate SOA concentrations and contributions for July and November 2018 in China. Both models have a volatility basis set (VBS) SOA algorithm but with different parameters and treatments of SOA photochemical aging. SOA generated from BVOC (i.e., BSOA) is found to be more important in southern China. In contrast, SOA generated from anthropogenic precursors is more prevalent in the North China Plain (NCP), Yangtze River Delta (YRD), Sichuan Basin and Central China. Both models indicate negligible SOA formation from SVOC emissions compared to other precursors. In July, when BVOC emissions are abundant, SOA is predominantly contributed by BSOA (except for NCP), followed by IVOC-SOA (i.e., SOA produced from IVOC) and ASOA (i.e., SOA produced from anthropogenic VOC). In contrast, in November, IVOC became the leading SOA contributor for all selected regions except PRD, illustrating the important contribution of IVOC emissions to SOA formation. While both models generally agree in terms of the spatial distributions and seasonal variations of different SOA components, CMAQ tends to predict higher BSOA, while CAMx generates higher ASOA concentrations. As a result, CMAQ results suggest that BSOA concentration is always higher than ASOA in November, while CAMx emphasizes the importance of ASOA. Utilizing a conceptual model, we found that different treatment of SOA aging between the two models is a major cause of differences in simulated ASOA concentrations. The step-wise SOA aging scheme implemented in the CAMx VBS (based on gas-phase reactions with OH radical and similar to other models) exhibits a strong enhancement effect on simulated ASOA concentrations, and this effect increases with the ambient organic aerosol (OA) concentrations. The CMAQ aerosol module implements a different SOA aging scheme that represents particle-phase oligomerization and has smaller impacts on total OA. Different structures and/or parameters of the SOA aging schemes are being used in current models, which could greatly affect model simulations of OA in ways that are difficult to anticipate. Our results indicate that future control policies should aim at reducing IVOC emissions as well as traditional VOC emissions. In addition, aging schemes are the major driver in CMAQ vs. CAMx treatments of ASOA and their resulting predicted mass. More sophisticated measurement data (e.g., with resolved OA components) and/or chamber experiments (e.g., investigating how aging influences SOA yields) are needed to better characterize SOA aging and constrain model parameterizations.

Sensitivity and uncertainties assessment in radiative forcing due to aerosol optical properties in diverse locations in China.

Aerosol optical properties play an important role in affecting direct aerosol radiative forcing (DARF). However, DARF estimation is still uncertain due to the complexity of aerosol optical properties. Therefore, in this study, the spatiotemporal distributions of aerosol properties and their effects on DARF in China from 2004 to 2020 are investigated using the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The results show that the aerosol optical parameters vary greatly and change with seasonal regularity, which is greatly affected by human activities. The control variable method was employed on aerosol optical properties for better estimation of DARF. Single scattering albedo (SSA) has the greatest effect on DARF, followed by aerosol optical depth (AOD) and the asymmetric factor (ASY) among the seven examined stations in China. The average DARF decreases by 4.2 % when the SSA increases by 0.3 % but increases by 34.7 % when the SSA decreases by 3 % in mainland China. When the AOD changes from -60 to +60 %, DARF changes from -54.7 % to +58.4 %. The variation in DARF is between -3 % and +3 % when the ASY varies from -30 % to +30 %. The instability in DARF resulted from the complicated and volatile nature of aerosol optical properties in the region; the aerosol optical properties are greatly affected by the aerosol types and relative humidity. The results of this study have important reference significance for understanding the variation of DARF and formulating pollution prevention and control policies in the region.