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Objective: Acute myocardial infarction (AMI) is a severe condition with high morbidity and mortality rates. This study aimed to identify hub genes potentially associated with AMI and assess their clinical utility in predicting AMI occurrence. Methods: Gene microarray data were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted on samples from patients with AMI and control samples to identify modules significantly associated with AMI. GO and KEGG analyses were applied to investigate the potential functions of these hub genes. Lastly, the mendelian randomization (MR) method was applied to analyze the causal relationship between the hub gene TNF and AMI. Results: 285 differentially expressed genes (DEGs) were identified through WCGNA and were clustered into 6 modules. The yellow module appeared most relevant to AMI. Further exploration through GO and KEGG pathway enrichment showed that key hub genes in the yellow module were linked to positive regulation of cytokine production, cytokine receptor binding, NF—kappa B signaling pathway, IL−17 signaling pathway, and TNF signaling pathway. The top 10 genes identified through Cytoscape software analysis were IL1B, TNF, TLR4, TLR2, FCGR3B, MMP9, CXCL8, TLR8, ICAM1, and JUK. Utilizing inverse variance weighting (IVW) analysis, we discovered a significant association between TNF and AMI risk, with an OR of 0.946 (95% CI = 0.911–0.984, p = 0.005). Conclusions: The result of this study indicated that TNF, TLR2, TLR4, IL1B and FCGR3B may be potential biodiagnostic markers for AMI. TNF can inhibit inflammatory and oxidative stress responses in AMI, exerting a protective role in the heart. [ABSTRACT FROM AUTHOR]

One of the most current concerns in the field of information system is whether cloud computing technology can deliver the desired improvement of capability and value to enterprises. This paper studied the enterprise technology development capability of the enterprises in Beijing Zhongguancun Technology Park, the first national high-tech industrial development zone in China, from the perspective of the breadth and depth of the alignment of cloud computing and enterprise. It proposed a theoretical model to study how the breadth and depth of alignment affects the enterprise technology development capability in a turbulent environment and considers the intermediary role of the enterprise technology absorption capability and the moderation role of environmental turbulence in it. The model was tested empirically by questionnaires and structural equation model (SEM). Empirical results showed that both the deep and wide alignment of cloud computing can enhance the enterprise technology development capability by improving the enterprise technology absorption capability.

Herein, the evolution of transformation in the width direction of high‐strength low‐alloy hot‐rolled strip is studied by using thermomechanical simulation, and the temperature, microstructure, and internal stress are correlated based on electron backscatter diffraction data. The temperature and time range of the transverse transformation are determined based on the thermal expansion curve. The results show that the transformation at the edge of the steel plate ends earliest and that at the plate center begins at the latest; only 31.9% austenite undergoes transformation at the plate central by the end of laminar cooling. The fraction of transformed austenite at the plate center is the least throughout the laminar cooling process. The proportion of small grains (within the grain size range of 0–4 μm), mean, and variant coefficient of grain sizes at the plate edge are 75%, 4 μm, and 1.29, respectively. In contrast, those values of the central region are 66%, 4.4 μm, and 1.05, respectively. The correlation between temperature and internal stress evolutions is established. It is demonstrated that the internal stress increases monotonically with the average transformation rate. [ABSTRACT FROM AUTHOR]