[Temporal and Spatial Variation Characteristics of Heavy Metal in Atmospheric Deposition in China from 2000 to 2018].

Owing to the significant impact of heavy metals in atmospheric deposition on soil, clear knowledge on the present situation and temporal and spatial variation in fluxes of heavy metals in atmospheric deposition all around China is urgently needed. In this study, we collected 99 published papers on deposition fluxes of heavy metals from 2001 to 2021 based on the CNKI and Web of Science database and extracted 718 to 1672 monitoring points from these papers. The Meta-analysis method was used to calculate the weighted average of deposition fluxes of heavy metals, and the spatial-temporal characteristics in different periods from 2000 to 2018 were studied by subgroup analysis, which compared the differences between different types of areas, such as agricultural and rural areas and urban and industrial areas. The results showed that the annual fluxes of heavy metals in atmospheric deposition[mg·(m2·a)-1] in China were as follows:Zn (96.75)>Pb (23.37)>Cu (12.77)>Cr (11.04)>Ni (6.61)>As (2.97)>Cd (0.48)>Hg (0.05). Overall, the estimated value of deposition fluxes in China from 2000 to 2018 was higher than that of rural areas in England from 1995 to 1998. The deposition fluxes in industrial areas and urban areas were much higher than those in the agricultural and rural areas, especially the industrial areas where the heavy metal pollution was more serious. The deposition fluxes of As and Cd in the Changsha-Zhuzhou-Xiangtan area were relatively high, whereas the atmospheric deposition of heavy metals in Northeast China, the Pearl River Delta, and North China Plain was more serious than that in the other areas. In the past 20 years, the annual deposition fluxes of Cd fluctuated around the overall average, without an obviously declining trend, whereas the deposition fluxes of Cd in the urban, agricultural, and rural areas showed a trend of growth. These results suggested that precise and risk control measures of atmospheric emissions should be established based on the characteristics of regional industrial structure, which should cover all levels, all types, and all regions. In addition, more restrictive measures should be taken to solve the current problem caused by the higher deposition flux of Cd in atmospheric deposition.

Exploring spatiotemporal variation characteristics of China's industrial carbon emissions on the basis of multi-source data.

Spatiotemporal variations of industrial carbon emissions (IE) must be scientifically understood, which will be helpful to formulate reasonable emission reduction strategies. Given that spatial distribution of IE is irrelevant to space agents commonly used (such as population and nighttime light), estimation and spatialization methods for total carbon dioxide (CO2) emissions are not entirely suitable for IE. Therefore, this paper used greenhouse gases observing satellite level 4A product to estimate IE at the city level and used industrial land density to obtain the distribution of IE within the administrative districts. Sectoral emission inventories of 182 cities and a mosaic Asian anthropogenic emission inventory named MIX were used to verify the results. Then, spatiotemporal variation characteristics of China's IE were analyzed from multiple levels. Results showed that (1) the mean relative error of estimation results was 56.11%, among which 62 cities had relative error of less than 30%. Gridded IE in this paper had high consistency with MIX. (2) Cities with high IE experienced rapid growth from 2009 to 2012, followed by slower growth from 2012 to 2017. (3) Centroid of significant cold and hot spots moved to the southeast and northwest, respectively. Most cities with high annual IE growth had relatively low emission efficiency, mainly located in Inner Mongolia and Xinjiang. Aggregation of medium and high IE grids may represent high emission efficiency. Significant differences still exist between cities in IE, and sustainable development strategies should be formulated according to local conditions. Regions with high annual growth or low emission efficiency are the key to achieving IE reduction targets in future.

PDK1 is important lipid kinase for RANKL-induced osteoclast formation and function via the regulation of the Akt-GSK3ß-NFATc1 signaling cascade.

Perturbations in the balanced process of osteoblast-mediated bone formation and osteoclast-mediated bone resorption leading to excessive osteoclast formation and/or activity is the cause of many pathological bone conditions such as osteoporosis. The osteoclast is the only cell in the body capable of resorbing and degrading the mineralized bone matrix. Osteoclast formation from monocytic precursors is governed by the actions of two key cytokines macrophage-colony-stimulating factor and receptor activator of nuclear factor-κB ligand (RANKL). Binding of RANKL binding to receptor RANK initiates a series of downstream signaling responses leading to monocytic cell differentiation and fusion, and subsequent mature osteoclast bone resorption and survival. The phosphoinositide-3-kinase (PI3K)-protein kinase B (Akt) signaling cascade is one such pathway activated in response to RANKL. The 3-phosphoinositide-dependent protein kinase 1 (PDK1), is considered the master upstream lipid kinase of the PI3K-Akt cascade. PDK1 functions to phosphorylate and partially activate Akt, triggering the activation of downstream effectors. However, the role of PDK1 in osteoclasts has yet to be clearly defined. In this study, we specifically deleted the PDK1 gene in osteoclasts using the cathepsin-K promoter driven Cre-LoxP system. We found that the specific genetic ablation of PDK1 in osteoclasts leads to an osteoclast-poor osteopetrotic phenotype in mice. In vitro cellular assays further confirmed the impairment of osteoclast formation in response to RANKL by PDK1-deficient bone marrow macrophage (BMM) precursor cells. PDK1-deficient BMMs exhibited reduced ability to reorganize actin cytoskeleton to form a podosomal actin belt as a result of diminished capacity to fuse into giant multinucleated osteoclasts. Notably, biochemical analyses showed that PDK1 deficiency attenuated the phosphorylation of Akt and downstream effector GSK3ß, and reduced induction of NFATc1. GSK3ß is a reported negative regulator of NFATc1. GSK3ß activity is inhibited by Akt-dependent phosphorylation. Thus, our data provide clear genetic and mechanistic insights into the important role for PDK1 in osteoclasts.

The Role and Mechanism of miRNA-1224 in the Polygonatum sibiricum Polysaccharide Regulation of Bone Marrow-Derived Macrophages to Osteoclast Differentiation.

MicroRNAs (miRNAs) are endogenous noncoding small molecule RNAs that regulate cell proliferation, differentiation, fat metabolism, and hormone secretion. Studies have shown that miRNAs regulate the processes related to osteoporosis, including the differentiation of osteoblasts, osteoclasts, and chondrocytes, and are one of the important regulatory factors of some bone metabolic diseases. In our previous study, it has been revealed that natural compound Polygonatum sibiricum polysaccharide (PSP) can promote osteoblast formation and block osteoclastogenesis through Wnt/ß-catenin signaling pathway. This study was designed to investigate whether PSP can inhibit expression of osteoclast-related genes by Hippo signaling pathway, which was prevented by effectively blocking the expression of miR-1224. This study showed that there were 27 differentially expressed miRNAs when PSP inhibits osteoclastogenesis, the most notable of which was miR-1224. Furthermore, the study showed that PSP increased the level of Limd1, which was the target gene of miR-1224. In conclusion, these findings demonstrate that PSP suppressed osteoclastogenesis in vitro through the Hippo signaling pathway based on miR-1224. This study may aid in the development of a therapeutic approach utilizing PSP for the enhancement of bone health and prevention of osteoporosis.

miR-136-5p Regulates the Inflammatory Response by Targeting the IKKß/NF-κB/A20 Pathway After Spinal Cord Injury.

BACKGROUND/AIMS: miR-136-5p participates in recovery after spinal cord injury (SCI) via an unknown mechanism. We investigated the mechanism underlying the involvement of miR-136-5p in the inflammatory response in a rat model of SCI. METHODS: Sprague-Dawley rat astrocytes were cultured in vitro to construct a reporter plasmid. Luciferase assays were used to detect the ability of miR-136-5p to target the IKKß and A20 genes. Next, recombinant lentiviral vectors were constructed, which either overexpressed miR-136-5p or inhibited its expression. The influence of miR-136-5p overexpression and miR-136-5p silencing on inflammation was observed in vivo in an SCI rat model. The expression of IL-1ß, IL-6, TNF-α, IFN-α, and related proteins (A20, IKKß, and NF-κB) was detected. RESULTS: In vitro studies showed that luciferase activity was significantly activated in the presence of the 3' untranslated region (UTR) region of the IKKß gene after stimulation of cells with miR-136-5p. However, luciferase activity was significantly inhibited in the presence of the 3'UTR region of the A20 gene. Thus, miR-136-5p may act directly on the 3'UTR regions of the IKKß and A20 genes to regulate their expression. miR-136-5p overexpression promoted the production of related cytokines and NF-κB in SCI rats and inhibited the expression of A20 protein. CONCLUSION: Overexpression of miR-136-5p promotes the generation of IL-1ß, IL-6, TNF-α, IFN-α, IKKß, and NF-κB in SCI rats but inhibits the expression of A20. Under these conditions, inflammatory cell infiltration into the rat spinal cord increases and injury is significantly aggravated. Silencing of miR-136-5p significantly reduces the protein expression results described after miR-136-5p overexpression and ameliorates the inflammatory cell infiltration and damage to the spinal cord. Therefore, miR-136-5p might be a new target for the treatment of SCI.

Global mean estimation using a self-organizing dual-zoning method for preferential sampling.

Giving an appropriate weight to each sampling point is essential to global mean estimation. The objective of this paper was to develop a global mean estimation method with preferential samples. The procedure for this estimation method was to first zone the study area based on self-organizing dual-zoning method and then to estimate the mean according to stratified sampling method. In this method, spreading of points in both feature and geographical space is considered. The method is tested in a case study on the metal Mn concentrations in Jilin provinces of China. Six sample patterns are selected to estimate the global mean and compared with the global mean calculated by direct arithmetic mean method, polygon method, and cell method. The results show that the proposed method produces more accurate and stable mean estimates under different feature deviation index (FDI) values and sample sizes. The relative errors of the global mean calculated by the proposed method are from 0.14 to 1.47 % and they are the largest (4.83-8.84 %) by direct arithmetic mean method. At the same time, the mean results calculated by the other three methods are sensitive to the FDI values and sample sizes.