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BackgroundHeart failure (HF) is a serious end-stage condition of various heart diseases with increasing frequency. Few studies have combined clinical features with high-throughput echocardiographic data to assess the risk of major cardiovascular events (MACE) in patients with heart failure. In this study, we assessed the relationship between these factors and heart failure to develop a practical and accurate prognostic dynamic nomogram model to identify high-risk groups of heart failure and ultimately provide tailored treatment options.Materials and methodsWe conducted a prospective study of 468 patients with heart failure and established a clinical predictive model. Modeling to predict risk of MACE in heart failure patients within 6 months after discharge obtained 320 features including general clinical data, laboratory examination, 2-dimensional and Doppler measurements, left ventricular (LV) and left atrial (LA) speckle tracking echocardiography (STE), and left ventricular vector flow mapping (VFM) data, were obtained by building a model to predict the risk of MACE within 6 months of discharge for patients with heart failure. In addition, the addition of machine learning models also confirmed the necessity of increasing the STE and VFM parameters.ResultsThrough regular follow-up 6 months after discharge, MACE occurred in 156 patients (33.3%). The prediction model showed good discrimination C-statistic value, 0.876 (p < 0.05), which indicated good identical calibration and clinical efficacy. In multiple datasets, through machine learning multi-model comparison, we found that the area under curve (AUC) of the model with VFM and STE parameters was higher, which was more significant with the XGboost model.ConclusionIn this study, we developed a prediction model and nomogram to estimate the risk of MACE within 6 months of discharge among patients with heart failure. The results of this study can provide a reference for clinical physicians for detection of the risk of MACE in terms of clinical characteristics, cardiac structure and function, hemodynamics, and enable its prompt management, which is a convenient, practical and effective clinical decision-making tool for providing accurate prognosis.

In this paper, we determined the whole mitochondrial DNA (mtDNA) sequence of Phoxinus lagowskii, a small freshwater fish that is distributed in rivers of north China, Russia and North Korea. The entire sequence of P. lagowskii mitochondrial genome is 16,699 bp in size, consisting of 13 protein-coding genes, 2 ribosomal RNA genes (12S rRNA and 16S rRNA), 22 transfer RNA genes (tRNA) and 1 putative control region. Most of the genes are encoded on the heavy strand except ND6 and eight tRNA genes (Gln, Ala, Asn, Cys, Try, Ser, Glu and Pro) encoded on the light strand.

MARVEL domain-containing 1 (MARVELD1) is one of the MARVEL domain-containing proteins. Expression of MARVELD1 in tumor and non-tumor tissues, the relationship between its expression and cancer prognosis, and upstream regulation of MARVELD1 were examined using pan-cancer data from The Cancer Genome Atlas. MARVELD1 expression was significantly downregulated in tissues used for pan-cancer analysis compared to that in normal tissues. Low expression of MARVELD1 was associated with poor disease outcomes in pan-cancer. Colon cancer patients with low expression of MARVELD1 had worse progression free survival and overall survival than those with high expression levels in our cohort. Hypermethylation and histone modification in the MARVELD1 promoter locus synergistically affected its expression in pan-cancer. The function of MARVELD1 in colon cancer remains to be studied. Gene Ontology enrichment analysis revealed that MARVELD1 may modulate processes associated with inhibition of tumorigenesis in colon cancer. Both upstream transcription factors and downstream functional enrichment of MARVELD1 were related to the Wnt/β-catenin signaling pathway. Overexpression of MARVELD1 inhibited the expression of β-catenin and its entry into the nucleus. MARVELD1 also inhibited the proliferation, migration, and invasion of colon cancer cells. With Wnt/β-catenin activator LiCl treatment, rescue experiments demonstrated that the role of MARVELD1 in colon cancer progression was dependent on the Wnt/β-catenin pathway. These results indicate that MARVELD1 acts as a tumor suppressor and inhibits tumorigenesis via the Wnt/β-catenin pathway.