ABSTRACT
An electrocatalyst with ultra-small PtCo single atom alloy species evenly dispersed on nitrogen-doped ultra-thin carbon nanosheets (PtCo SAA/NC) was designed. The introduction of single-atom Pt not only maximizes the atomic utilization efficiency of Pt species, but also synergistically enhances the charge transfer characteristics of Co cluster surfaces, thereby increasing the migration and evolution rate of hydrogen ions. The PtCo SAA/NC catalyst exhibits a Tafel slope of 42 mV dec-1 and a low overpotential of 45 mV at 10 mA cm-2 in 0.5 M H2SO4 solution.
ABSTRACT
BACKGROUND: Cardiomyopathy is a complex type of myocardial disease, and its incidence has increased significantly in recent years. Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common and indistinguishable types of cardiomyopathy. RESULTS: Here, a systematic multi-omics integration approach was proposed to identify cardiomyopathy-related core genes that could distinguish normal, DCM and ICM samples using cardiomyopathy expression profile data based on a human metabolic network. First, according to the differentially expressed genes between different states (DCM/ICM and normal, or DCM and ICM) of samples, three sets of initial modules were obtained from the human metabolic network. Two permutation tests were used to evaluate the significance of the Pearson correlation coefficient difference score of the initial modules, and three candidate modules were screened out. Then, a cardiomyopathy risk module that was significantly related to DCM and ICM was determined according to the significance of the module score based on Markov random field. Finally, based on the shortest path between cardiomyopathy known genes, 13 core genes related to cardiomyopathy were identified. These core genes were enriched in pathways and functions significantly related to cardiomyopathy and could distinguish between samples of different states. CONCLUSION: The identified core genes might serve as potential biomarkers of cardiomyopathy. This research will contribute to identifying potential biomarkers of cardiomyopathy and to distinguishing different types of cardiomyopathy.
Subject(s)
Cardiomyopathies , Cardiomyopathy, Dilated , Myocardial Ischemia , Biomarkers/metabolism , Cardiomyopathies/genetics , Cardiomyopathy, Dilated/genetics , Humans , Metabolic Networks and Pathways/geneticsABSTRACT
Glioma is one particular type of brain malignancy which is highly complex and usually has a poor prognosis. Despite the limited diagnostic level of glioma, the survival time of affected patients broadly varies. Here, we conducted a detailed analysis, regarding the differences in patient survival time, to discover potential survival-related genes in glioma as well as their putative regulatory mechanisms. To contextualize the acquisition of these potential prognosis markers in large populations, particularly in China, we combined CGGA and The Cancer Genome Atlas (TCGA) databases to properly identify genes that are significantly related to survival. Our workflow combined a series of analytical approaches, including differential analysis, survival time, co-expression, clinical correlation analysis, ROC curve evaluation and prediction ability. Our results indicate that the four particular genes - PLAT, IGFBP2, BCAT1, SERPINH1 could be used as independent prognostic marker genes. These genes have also shown good prognostic ability in distinct populations, reiterating the robustness and value of these prognostic markers.
