How to analyse the injury based on 24Model: a case study of coal mine gas explosion injury

BackgroundCoal mine gas explosion injury has caused mass casualties, which have resulted in widespread concern.MethodsIn order to prevent gas explosion injury in coal mine, 24Model is proposed to analyse the risk in this paper. 24Model is a human-oriented and organisation-oriented risk analysis method. Based on the 24Model, we propose a general procedure for analysing the causes of injury within the organisation.ResultsA coal mine gas explosion case was analysed using the 24Model and the proposed analysis method, and the evolution of injury and the interaction of various causes was showed, and 6 unsafe conditions, 25 unsafe acts, 13 safety knowledge, 13 safety management systems and 13 safety cultures were obtained.ConclusionCase analysis results show that by using the 24Model and analysis method the proposed effect can help employees to clearly see the evolution and identify the causes of the injury, to better understand the logical relationship with the causes of the injury, improve the effectiveness of training and effectively prevent similar injury. The case study provides a practical procedure for injury investigation and analysis, and thus, preventive measures can be made according to the various causations at different levels.

Evaluation of Gas Explosion Injury Based on Analysis of Rat Serum Profile by Ultra-Performance Liquid Chromatography/Mass Spectrometry-Based Metabonomics Techniques

Gas explosion can lead to serious global public health issues. Early period gas explosion injury (GEI) can induce a series of histopathologic and specific metabolic changes. Unfortunately, it is difficult to treat GEI thoroughly. To date, the specific molecular mechanism of GEI is still unclear. To accurately diagnose and provide comprehensive clinical intervention, we performed a global analysis of metabolic alterations involved in GEI. The physiological and behavioral indicators’ changes of rats after gas explosion were observed. These metabolic alterations were first investigated in a rat model using serum metabonomics techniques and multivariate statistical analysis. Significant heart rate (HR), mean blood pressure (mBP), and neurobehavioral index changes were observed in the GEI group after gas explosion. UPLC-MS revealed evident separated clustering between the control and GEI groups using supervised partial least squares discriminant analysis (PLS-DA). We designed an integrated metabonomics study for identifying reliable biomarkers of GEI using a time-course analysis of discriminating metabolites in this experiment. The metabonomics analysis showed alterations in a number of biomarkers (21 from serum). The meaningful biomarkers of GEI provide new insights into the pathophysiological changes and molecular mechanisms of GEI, including the disturbances in oxidative stress and neuroinflammatory reaction, as well as in metabolism of lipids, glucose, and amino acids in rats, suggesting that the process of GEI in humans is likely to be comprehensive and dynamic. Correlations between the GEI group and the biomarkers identified from the rat model will be further explored to elucidate the metabolic pathways responsible for GEI in the human body.