Identification and Verification of a Glycolysis-Related lncRNA Prognostic Signature for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a primary liver cancer with a high mortality rate. The search for a new biomarker could help the prognosis of HCC patients. We identified the glycolytic gene set associated with HCC and the glycolytic lncRNA based on TCGA and MsigDB databases. According to these lncRNAs, K-means clustering, and regression analysis were performed on the patients. Two groups of HCC patients with different lncRNA expression levels were obtained based on K-means clustering results. The results of difference analysis and enrichment analysis showed that DEmRNA in the two HCC populations with significant survival differences was mainly enriched in transmembrane transporter complex, RNA polymerase II specificity, cAMP signaling pathway, and calcium signaling pathway. In addition, a prognostic model of HCC with 4 DElncRNAs was constructed based on regression analysis. ROC curve analysis showed that the model had good predictive performance. Drug predictionresults showed that the efficacy of JQ1, niraparib, and teniposide was higher in the low-risk group than in the high-risk group. In conclusion, this study preliminarily identified glycolytic-related prognostic features of lncRNAs in HCC and constructed a risk assessment model. The results of this study are expected to guide the prognosis assessment of clinical HCC patients.

Risk Transmission of Trade Price Fluctuations from a Nickel Chain Perspective: Based on Systematic Risk Entropy and Granger Causality Networks.

Nickel is a strategic mineral resource, with 65% of nickel being used in stainless steel. The situation in Ukraine starting in February 2022 has led to significant fluctuations in nickel prices, with prices of nickel products along the same chain affecting and passing through each other. Using systematic risk entropy and granger causality networks, we measure the volatility risk of trade prices of nickel products using the nickel industry chain trade data from 2000-2019 and explore the transmission patterns of different volatility risk prices from the industry chain perspective. The findings show that: (1) Nickel ore has the highest risk of import trade price volatility and a strong influence, but low risk transmission. Stainless steel has the highest trade price impact but is also subject to the strongest passive influence. (2) The Americas have a higher risk of trade price volatility but a weaker influence. The influence and sensitivity of trade prices is stronger in Asia and Europe. (3) Indonesia's stainless steel export prices have a high rate of transmission and strong influence. Germany's ferronickel export prices are highly susceptible to external influences and can continue to spread loudly. Russian nickel ore export prices are able to quickly spread their impact to other regions.

China's carbon emissions from the electricity sector: Spatial characteristics and interregional transfer.

As a major carbon emitter, the electricity sector is crucial to the realization of China's emission reduction objectives. Existing studies focus mostly on the influencing factors, emission efficiency and low carbon development of carbon emissions in the electricity sector. Missing from the literature is an analysis of spatial characteristics of carbon emissions and the embodied carbon emission transfer caused by the separation of electricity production and consumption, which is the basis for assigning the responsibility for emission reduction. Thirty provinces in China were taken as research objects, and Moran's I index was adopted to analyze the spatial characteristics of the electricity sector's carbon emissions and carbon emission intensity. Based on multiregional input-output tables, we compared the transfer situation of China's provincial electricity carbon emissions in 2010 and 2015. The results demonstrate that, from 2010 to 2015, the electricity carbon emissions in 20 provinces increased, whereas the carbon emission intensity in 21 provinces decreased. Carbon emissions and carbon emission intensity of electricity in most provinces demonstrate positive spatial clustering characteristics. The total amount of carbon emission transfer in the electricity sector increased from 421.22 million tons in 2010 to 581.369 million tons in 2015, the number of net transfers out of areas increased from 13 to 15, and the number of net transfers into areas decreased from 16 to 15. The active degree of carbon emission transfer reveals the eastern region > the central region > the western region. Different emission reduction policies should be formulated based on the difference in resource endowment between the north and south. Provinces that transferred out large amounts of electricity carbon emissions should take greater responsibility for emission reduction. Integr Environ Assess Manag 2022;18:258-273. © 2021 SETAC.

Environmental Pollution Effect Analysis of Lead Compounds in China Based on Life Cycle.

Environmental pollution caused by lead toxicity causes harm to human health. Lead pollution in the environment mainly comes from the processes of mining, processing, production, use, and recovery of lead. China is the world's largest producer and consumer of refined lead. In this paper, the material flow analysis method is used to analyze the flow and direction of lead loss in four stages of lead production, manufacturing, use, and waste management in China from 1949 to 2017. The proportion coefficient of lead compounds in each stage of lead loss was determined. The categories and quantities of lead compounds discharged in each stage were calculated. The results show that in 2017, China emitted 2.1519 million tons of lead compounds. In the four stages of production, manufacturing, use, and waste management, 137.9 kilo tons, 209 kilo tons, 275 kilo tons, and 1.53 million tons were respectively discharged. The emissions in the production stage are PbS, PbO, PbSO4, PbO2, Pb2O3, and more. The emissions during the manufacturing phase are Pb, PbO, PbSO4, Pb2O3, Pb3O4, and more. The main emissions are Pb, PbO, Pb2O3, Pb3O4, and more. The main emissions in the waste management stage are PbS, Pb, PbO, PbSO4, PbO2, PbCO3, Pb2O3, Pb3O4, and more. Among them, the emissions of PbSO4, PbO, Pb, and PbO2 account for about 90%, which are the main environmental pollution emissions. The waste management stage is an important control source of lead compound emission and pollution. In view of these characteristics of the environmental pollution risk of lead compounds in China, the government should issue more targeted policies to control lead pollution.

Numerical built-in method for the nonlinear JRC/JCS model in rock joint.

The joint surface is widely distributed in the rock, thus leading to the nonlinear characteristics of rock mass strength and limiting the effectiveness of the linear model in reflecting characteristics. The JRC/JCS model is the nonlinear failure criterion and generally believed to describe the characteristics of joints better than other models. In order to develop the numerical program for JRC/JCS model, this paper established the relationship between the parameters of the JRC/JCS and Mohr-Coulomb models. Thereafter, the numerical implement method and implementation process of the JRC/JCS model were discussed and the reliability of the numerical method was verified by the shear tests of jointed rock mass. Finally, the effect of the JRC/JCS model parameters on the shear strength of the joint was analyzed.