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Multiple roles of reactive oxygen species (ROS) and their consequences for health and disease are emerging throughout biological sciences. This development has led researchers unfamiliar with the complexities of ROS and their reactions to employ commercial kits and probes to measure ROS and oxidative damage inappropriately, treating ROS (a generic abbreviation) as if it were a discrete molecular entity. Unfortunately, the application and interpretation of these measurements are fraught with challenges and limitations. This can lead to misleading claims entering the literature and impeding progress, despite a well-established body of knowledge on how best to assess individual ROS, their reactions, role as signalling molecules and the oxidative damage that they can cause. In this consensus statement we illuminate problems that can arise with many commonly used approaches for measurement of ROS and oxidative damage, and propose guidelines for best practice. We hope that these strategies will be useful to those who find their research requiring assessment of ROS, oxidative damage and redox signalling in cells and in vivo.

In order to explore a scientific and effective fault complexity evaluation method, through analyzing the basic characteristic indicators of the fault, based on the fractal theory, selecting the fractal dimension value of the fault, the fault density value, the number of fault interchange points and the fault intensity index as the evaluation indicators, we use the idea of game theory to construct a combined weighting method of order relation analysis method and entropy weight method, and evaluate the complexity of faults in the north No.10 mining area of Jiangzhuang Coal Mine. The results are as follows: the simple and medium tectonic areas of the fault are mainly located in the west, south and north of the study area, and are distributed in a ring shape; the lower complex structural areas are mainly located in the south and north of the study area, distributed in strips and blocks; the complex structural areas are mainly located in the middle of the study area, and some are scattered in the south and north; the extremely complex structural areas are mainly distributed in the central part of the study area in large blocks.

Based on the data of drilling, geophysical exploration and roadway fault exposure of No.3 upper 107 working face in first mining area of Sanhekou Coal Mine, the water bearing capacity of Sanhekou fault and Qianzhai fault in natural state is analyzed, and the fault sealing methods such as lithology juxtaposition map, SGR method and fault plane normal pressure method are used to evaluate the fault water conductivity in natural conditions from lateral and vertical aspects. The numerical simulation of fault seepage characteristics and activation law under the condition of mining in working face is carried out. The results show that both Sanhekou fault and Qianzhai fault are water free faults under natural conditions. When the working face is excavated 30 m away from Sanhekou fault and 26 m away from Qianzhai fault, the pore water pressure in the two fault layers increases slowly, and only the upper end of the fault is damaged within a small range, and the overall water blocking performance of the fault does not change.

In order to accurately predict the development height of water-conducting fracture zone in the roof of fully mechanized caving coal of No.3 coal seam in Tengzhou Mining Area, based on the measured data of water-conducting fracture zone height and main control factors of 18 working faces in Tengzhou Mining Area, we use SPSS software to carry out correlation analysis on six factors such as mining thickness, mining depth, coal seam dip angle, strike length, dip length and roof thickness, and build the water-conducting fractured zone height of multivariate linear regression forecast model. Finally, four working faces in Tengxian Coalfield are taken as examples to calculate the height of water-conducting fracture zone and compare the error analysis by using the regulations for coal mining under buildings, water bodies and railways, standard formula and regression model. In addition, Tengdong Coal Mine also used UDEC numerical simulation analysis for auxiliary verification. The results show that the model’s predicted values in this paper are closer to the measured values(the error is controlled within 8%), and the accuracy is higher than that of the empirical formula.

The fault water damage accounts for most of the coal mine floor water inrush accidents in China, and the pillar design of fault waterproof coal(rock) is the main means to prevent fault water damage, which is related to the safety and efficient production of coal mine. The reasonable width of fault waterproof coal (rock) column can not only prevent the underground water from pouring into the mine through the fault, but also serve the reasonable and safe mining of coal resources. The design of fault waterproof coal (rock) column width involves many factors and is one of the focuses of many scholars and engineers. A variety of research methods have been applied at present, including theoretical calculation, multiple regression analysis, BP and RBF, similarity simulation, numerical simulation for the coal (rock) column design under different fault conditions have been specifically studied. On this basis, the research status of fault coal (rock) pillar is summarized, the existing problems are pointed out, and the future research technology and methods are prospected.

This article discusses a study that used nontargeted metabolomics and machine learning to identify potential biomarkers for cardiovascular diseases (CVD), specifically coronary heart disease (CHD) and myocardial infarction (MI). The study analyzed serum samples from a Chinese cohort of patients with CHD, MI, and controls, and identified differential metabolites that could distinguish between the groups. The researchers also conducted pathway enrichment analysis to explore the metabolic pathways involved in CHD and MI progression. They developed a model based on three metabolites (arginine, hypoxanthine, and acetylcarnitine) that could discriminate between CHD and MI with high accuracy. The study suggests that metabolomics and machine learning have the potential to improve the diagnosis of CHD and MI. [Extracted from the article]

During the Holocene, the upper and middle reaches of the Yellow River valley in China were pivotal areas for agricultural development. Quantitatively reconstructing the spatiotemporal changes in prehistoric human land use is essential for understanding, from a long-term perspective, the interactions among evolutions of climate, agriculture, and human activities. Based on 327 archaeological sites and the PLUM (prehistoric land use model), we quantitatively reconstructed human land use changes from 6 to 3 ka BP (thousands of years before the present) in the Tao River valley, the second-largest tributary in the upper reach of the Yellow River valley. The results indicated that regional land use areas increased from 571 km2 to 1468 km2, with spatial expansion from the lower reach to the upper–middle reach of the Tao River valley. A comparison of the five areas distributed across the upper and middle reaches of the Yellow River valley revealed two different trends of increasing land use from 8 to 3 ka BP within these areas. The first group (the Wei River and Yiluo River valleys) exhibited rapid and substantial growth before 5 ka BP, while the second group (the Huangshui River and Tao River valleys, and the Yunlin district) showed a much slower and less significant increase before 5 ka BP, but a more obvious increase thereafter. The asynchronous increases in these areas indicate an expansion of land use from the southeastern part of the upper and middle reaches of the Yellow River Valley to across the entire region between 8 and 3 ka BP, which was primarily driven by agricultural development and cultural communication. [ABSTRACT FROM AUTHOR]