Ginsenosides Inhibit the Proliferation of Lung Cancer Cells and Suppress the Rate of Metastasis by Modulating EGFR/VEGF Signaling Pathways.

Ginsenosides Rg3 and Rg5 obtained from Panax (ginseng) have shown significant anticancer activity via the PI3K-Akt signaling pathway. This study evaluated the anticancer and antimetastatic effects of a combination of Rg3 and Rg5 on lung cancer cells. A combination of Rg3 and Rg5 was treated for lung cancer cell line A549 and human lung tumor xenograft mouse model, and anti-metastatic effects on Matrigel plug implantation in mice. The combination of Rg3 and Rg5 showed potent antiproliferative effects on A549 cells with IC50 values of 44.6 and 36.0 µM for Rg3 and Rg5 respectively. The combination of Rg3 and Rg5 (30 µM each) showed 48% cell viability as compared to Rg3 (72% viability) and Rg5 (64% viability) at 30 µM concentrations. The combination of Rg3 and Rg5 induced apoptosis in A549 cells characterized by activation of caspase-9 and caspase-3 and cleavage of PARP, as well as suppression of the autophagic marker LC3A/B. The antitumoral potentials of the combination of Rg3 and Rg5 were ascertained in a lung tumor xenograft mouse model with high efficacy as compared to individual ginsenosides. The metastasislimiting properties of the combination of Rg3 and Rg5 were assessed in Matrigel plug implantation in mice which showed the potent efficacy of the combination as compared to individual ginsenoside. Mechanistically, the combination of Rg3 and Rg5 inhibited the expression of PI3K/Akt/mTOR and EGFR/VEGF signaling pathways in lung cancer cells. Results suggest that the combination of Rg3 and Rg5 suppressed the tumor cell proliferation in lung cancer cells and limited the rate of metastasis which further suggest that the combination has a significant effect as compared to the administration of single ginsenoside.

Scientometric analysis on the review research evolution of tailings dam failure disasters.

As the most severe damage form of tailings ponds, dam failure causes a serious threat and damage to the surrounding lives and environment. Therefore, based on the systematic collection and consultation of relevant data at home and abroad, the literature source analysis on tailings dam failure disasters is conducted using the CiteSpace scientometric tool. The research on tailings dam failure disasters can be classified into two stages: the preliminary germination stage and rapid development stage. Based on the scientometric knowledge map, the research hotspots of tailings dam failure disasters are analyzed and summarized as three main research directions: environmental impact, risk assessment, and mechanical behavior. With the maturity of the research on ecological problems caused by tailings leakage, ecological restoration has also gradually become a hot research topic. Through the analysis of keyword bursts and co-cited bursts, the research frontier of tailings dam break disaster is explored. "Risk management," "real-time monitoring," and "tailings characteristic" represent the current research frontier. Among them, risk management is burst for the longest time and is expected to be a very important research direction in the future. Finally, a tailings pond risk management and control suggestion is proposed with risk management as the core, emphasizing risk monitor, and combined with dynamic risk control, which provides a foundation for the construction of tailings dam safety management and dynamic monitoring systems.

Multi-hazard risk characterization and collaborative control oriented to space in non-coal underground mines.

In order to realize accurate risk assessment and collaborative control of multi-hazard risk in non-coal underground mines, a space-oriented risk characterization and collaborative control model of multi-hazard risk in non-coal underground mines is proposed. Statistical analysis of non-coal underground mine accidents from 2000 to 2022, revealing the characteristics of non-coal underground mine accidents and 5 risk types were identified, including cage fall accident, powered haulage accident, fire accident, mine water inrush accident, and roof fall and rib spalling accident. A multi-hazard risk analysis and assessment framework for non-coal underground mines based on the inherent risk of the system, the vulnerability of the disaster-bearing body and the adaptability of the disaster-bearing area is proposed. The multi-hazard inherent risks in non-coal underground mines are comprehensively identified and evaluated in five aspects, including hazardous equipment and facilities, hazardous materials, hazardous processes, hazardous operations and hazardous places, and the characterization and unified measurement of multi-hazard risk is realized by combining the vulnerability index of disaster-bearing body and the adaptability index of disaster-bearing area. Regional multi-hazard risk aggregation is achieved through the Nemerow pollution index and space-oriented multi-hazard risk is obtained. Constructed a multi-hazard safety risk collaborative control system of source identification, classification and control, process control, continuous improvement, and full participation. Finally, the validity and rationality of the risk characterization model and the risk collaborative control system are verified. The research can both support the formulation of macro policies for non-coal underground mines and provide guidance for the specific spatial layout.

Uncertainty prediction of mining safety production situation.

In order to explore the occurrence and development law of mining safety production accidents, analyze its future change trends, and aim at the ambiguity, non-stationarity, and randomness of mining safety production accidents, an uncertainty prediction model for mining safety production situation is proposed. Firstly, the time series effect evaluation function is introduced to determine the optimal time granularity, which is used as the window width of fuzzy information granulation (FIG), and the time series of mining safety production situation is mapped to Low, R, and Up three granular parameter sequences, according to the triangular fuzzy number; then, the mean value of the intrinsic mode function (IMF) is maintained in the normal dynamic filtering range. After the ensemble empirical mode decomposition (EEMD), the three non-stationary granulation parameter sequences of Low, R, and Up are decomposed into the intrinsic mode function components representing the detail information and the trend components representing the overall change, and then the sub-sequences are reconstructed according to the sample entropy to highlight the correlation among the sub-sequences; finally, the cloud model language rules of mining safety production situation prediction are created. Through time series discretization, cloud transformation, concept jump, time series set division, association rule mining, and uncertain reasoning, the reconstructed component sequence is modeled and predicted by uncertainty information extraction. The accuracy of the uncertainty prediction model was verified by 21 sets of test samples. The average relative errors of Low, R, and Up sequences were 9.472 %, 16.671 %, and 3.625 %, respectively. The research shows that the uncertainty prediction model of mining safety production situation overcomes the fuzziness, non-stationarity, and uncertainty of safety production accidents, and provides theoretical reference and practical guidance for mining safety management and decision-making.

LncRNA MIR155HG contributes to smoke-related chronic obstructive pulmonary disease by targeting miR-128-5p/BRD4 axis.

Chronic obstructive pulmonary disease (COPD) is a common airway disease characterized by an exaggerated pulmonary inflammatory response. Long noncoding MIR155 host gene (lncRNA MIR155HG) has been identified to be related to the macrophage polarization in COPD. However, the detailed function of MIR155HG in cigarette smoke (CS)-mediated COPD remains largely unknown. The expression level of MIR155HG was elevated while miR-218-5p was decreased in lung tissues of smokers without or with COPD, especially in smokers with COPD, and cigarette smoke extract (CSE)-treated human pulmonary microvascular endothelial cell (HPMECs) in a dose- and time-dependent manner. Then, functional experiments showed that MIR155HG deletion could reverse CSE exposure-induced apoptosis and inflammation in HPMECs. MiR-218-5p was confirmed to be a target of MIR155HG and rescue assay showed miR-218-5p inhibitor attenuated the inhibitory action of MIR155HG knockdown on CSE-induced HPMECs. Subsequently, miR-218-5p was found to target bromodomain containing 4 (BRD4) directly, and miR-218-5p overexpression overturned CSE-induced injury of HPMECs via regulating BRD4. Additionally, co-expression analysis indicated MIR155HG indirectly regulated BRD4 expression in HPMECs via miR-218-5p. Thus, we concluded that MIR155HG contributed to the apoptosis and inflammation of HPMECs in smoke-related COPD by regulating miR-128-5p/BRD4 axis, providing a novel insight on the pathogenesis of COPD and a therapeutic strategy on COPD treatments.

Experimental Research on Shear Failure Monitoring of Composite Rocks Using Piezoelectric Active Sensing Approach.

Underground space engineering structures are generally subject to extensive damages and significant deformation. Given that composite rocks are prone to shear failure, which cannot be accurately monitored, the piezoelectric active sensing method and wavelet packet analysis method were employed to conduct a shear failure monitoring test on composite rocks in this study. For the experiment, specimens were prepared for the simulation of the composite rocks using cement. Two pairs of piezoelectric smart aggregates (SAs) were embedded in the composite specimens. When the specimens were tested using the direct shear apparatus, an active sensing-based monitoring test was conducted using the embedded SAs. Moreover, a wavelet packet analysis was conducted to compute the energy of the monitoring signal; thus allowing for the determination of the shear damage index of the composite specimens and the quantitative characterization of the shear failure process. The results indicated that upon the shear failure of the composite specimens, the amplitudes and peak values of the monitoring signals decreased significantly, and the shear failure and damage indices of the composite specimens increased abruptly and approached a value of 1. The feasibility and reliability of the piezoelectric active sensing method, with respect to the monitoring of the shear failure of composite rocks, was therefore experimentally demonstrated in this study.

Fuzzy risk prediction of roof fall and rib spalling: based on FFTA-DFCE and risk matrix methods.

The working conditions of underground mining are complex and variable, and roof fall and rib spalling are one of the main types of accidents that can occur. Building an integrated model to evaluate the risk of roof fall and rib spalling is the foundation of mine safety. On the basis of the inherent attributes of event risk, the fuzzy evaluation set and probability of basic events are obtained by using the fuzzy fault tree analysis method based on the sample's fuzzy information. Subsequently, the likelihood of roof fall and rib spalling is determined. Consequence severity data are obtained by using the dynamic fuzzy logic method, and the consequence severity grade of roof fall and rib spalling is evaluated via the dynamic fuzzy comprehensive evaluation method. The event risk level is determined by the risk matrix method. Roof fall and rib spalling in a non-coal mine is analyzed and evaluated by using fuzzy fault tree analysis and dynamic fuzzy comprehensive evaluation. The weak links in the operation of an underground mine are identified by fuzzy fault tree analysis as "mining process, roof management, support and reinforcement." Then, the risk development trend is determined by the dynamic fuzzy comprehensive evaluation method. The risk matrix method is integrated to determine whether the risk level of the mine is "high risk, unacceptable" and expected to deteriorate in the future. The results show the validity and feasibility of the risk analysis and prediction model for roof fall and rib spalling.