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Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2>1 and P value <0.05) between first-day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up-regulated and 41 down-regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up-regulated and 1173 downregulated DEGs. The comparison of the DEGs in two datasets revealed four common up-regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (P < 0.05). The DEGs, especially the four up-regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650-658, 2018. © 2017 Wiley Periodicals, Inc. KEY WORDS: ACUTE MYOCARDIAL INFARCTION; DIFFERENTIALLY EXPRESSED GENES; FUNCTIONAL ANNOTATION; BIOMARKERSA cute myocardial infarction (AMI) can cause heart failure, an irregular heartbeat, cardiogenic shock, or cardiac arrest [Risk et al., 2017]. It is the major cause of morbidity and mortality in the general population. This well-known heart attack is generally classified into ST-elevation MI (STEMI) and non-ST elevation MI (NSTEMI) [Moe and Wong, 2010]. According to the World Health Organization (WHO), annually, more than 3 million people are estimated with acute STEMI and that and more than 4 million suffers from NSTEMI [Organization, 2005;Reed et al., 2017]. In the modern society, the aging of population and comorbidities (e.g., obesity and metabolic syndrome) become more prevalent. All theses public health burden are the high risks of AMI. Besides, other health problems caused by ischemic heart disease are likely to increase even further [Yasuda and Shimokawa, 2009].The main treatments for STEMI include thrombolysis and percutaneous coronary intervention [Bates and Menees, 2012]. Hereinto, the percutaneous coronary intervention (PCI) should be performed within 90-120 min, if not, thrombolysis, preferably within 30 min of arrival to the hospital, is recommended [Bassand et al., 2005]. All these treatments need is extremely a time ...
ObjectiveTo evaluate the prognostic value of the Prehospital Index (PHI) for hospitalized patients with acute trauma.Materials and methodsPHI score and the Injury Severity Score (ISS) were determined in 1,802 hospitalized patients with acute trauma. Receiver-operator characteristic (ROC) curves were used to compare the PHI and ISS in subgroups, and corresponding prediction indicators were calculated.ResultsThere were significant differences in PHI score and ISS between the survival group and the death group (Z=2.674, P=0.007). The area under the ROC curve was 0.871 (95% CI 0.855–0.886) for PHI score and 0.792 (95% CI 0.773–0.811) for ISS. Optimal cutoff points to determine the risk of critical illness were PHI ≥4 and ISS ≥22. The sensitivity of the PHI was superior to the ISS (χ2=6.975, P=0.008), but the specificity and the accuracy of the PHI and ISS showed no significant difference (P>0.05).ConclusionThe PHI is valuable in prognostic prediction of hospitalized patients with acute trauma, and it is superior to the ISS. The PHI has such advantages as being simple in operation, easy to learn, capable of reflecting conditions timely and reliably, and suitable for dynamic evaluation and screening for critical patients with trauma.
In this paper, we propose a weights-based image demosaicking algorithm which is based on the Bayer pattern color filter array (CFA). When reconstructing the missing G components, the proposed algorithm uses weights based on posteriori gradients to mitigate color artifacts and distortions. Furthermore, the proposed algorithm makes full use of the correlation of R–B channels in high frequency when interpolating R/B values at B/R positions. Experimental results show that the proposed algorithm is superior to previous similar algorithms in composite peak signal-to-noise ratio (CPSNR) and subjective visual effect. The biggest advantage of the proposed algorithm is the use of posteriori gradients and the correlation of R–B channels in high frequency.
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