Aiming at the problem that the traditional coronary artery centerline extraction method is computationally intensive and requires a large number of manual interventions, a fully automatic coronary artery centerline tracking extraction method is proposed. First, adaptive adaptation of coronary vessels was performed based on different Fresenius norms designed for coronary scale. A multi-scale differential operator is constructed based on the vascular gray-scale distribution to establish a discriminant function, thereby obtaining the initial position and tracking direction of the seed point. Then, the new ridge point and tracking direction are optimally detected within the local arc length of the initial direction to ensure that the correct ridge position can still be obtained with large error interference. Finally, the pseudo vascular centerline is removed using the vascular topology feature detection method. The experimental results show that the method can accurately extract the blood vessel center line, direction vector and other information in the coronary angiography image without manual intervention, and can be used in the computer-assisted diagnosis and treatment process of clinical cardiovascular disease. INDEX TERMS Extraction method, coronary artery blood, vessel Centerline, CT coronary angiography.

Background. Heart failure (HF) is defined as the inability of the heart’s systolic and diastolic function to properly discharge blood flow from the veins to the heart. The goal of our research is to look into the possible mechanism that causes HF. Methods. The GSE5406 database was used for screening the differentially expressed genes (DEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network were applied to analyze DEGs. Besides, cell counting Kit-8 (CCK-8) was conducted to observe the knockdown effect of hub genes on cell proliferation. Results. Finally, 377 upregulated and 461 downregulated DEGs came out, enriched in the extracellular matrix organization and gap junction. According to GSEA results, Hoft cd4 positive alpha beta memory t cell bcg vaccine age 18–45 yo id 7 dy top 100 deg ex vivo up, Sobolev t cell pandemrix age 18–64 yo 7 dy dn, and so on were significantly related to gene set GSE5406. 7 hub genes, such as COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3 and MAPK1, were selected from PPI networks. CCK-8 indicated silencing of STAT3 promoted the proliferation of H9C2 cells and silencing of UBB inhibited the proliferation of H9C2 cells. Conclusion. Our analysis reveals that COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3, and MAPK1 might promote the progression of HF and become the biomarkers for diagnosis and treatment of HF.

In the current study, the gut microbiota of patients with and without coronary heart disease was compared and the relationship between gut microbiota distribution, intending to reveal the role of gut microbiota in the coronary atherosclerosis process, was investigated.This study included 50 patients diagnosed with coronary heart disease (CHD) who received conventional coronary angiography or computed tomography angiography and 50 patients with CHD at Changshu No. 2 People's Hospital, Suzhou, China, from May 2020 to January 2021. Trimethylamine N-oxide (TMAO) level was tested and feces were collected, the DNA of the gut microbiota was extracted, and the distribution by 16SrRNA gene sequencing was obtained from the two groups of patients.Plasma TMAO concentrations were significantly higher in patients with CHD (P < 0.001). In the CHD group, 22 patients with multivessel disease had a higher level of TMAO compared with the 28 patients who had the single-vessel disease (P < 0.001). No difference in the gut microbiota diversity was noted between the two groups (P < 0.001). Patients with CHD had a significantly lower proportion of Bacteroidetes phyla and more proportion of Epsilonbacteraeota phyla. At the genus level, patients with CHD had an increased abundance of Enterococcus, whereas healthy controls had significantly higher levels of Streptococcus. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2 analysis found that, in the KEGG ORTHOL-OGY, the level of choline trimethylamine-lyase gene expression correlated with TMAO production was higher in the fecal microbiome of the CHD group (P < 0.05).Gut microbiota and its product were expected to become a diagnostic marker and a new target for preventing CHD.

Background: To research the associations between gut microbiota composition, lipopolysaccharide (LPS), and atherosclerosis in process of coronary heart disease（CHD） Methods: We enrolled 50 patients who had been given a traditional coronary angiography diagnosis of coronary heart disease in the CHD group, and 50 matching patients who had CHD excluded in the control group. The CHD patients were further classified into three groups based on their Gensini scores, which were determined using the modified scoring schema: a mild CHD group (26 scores, N=16), a moderate CHD group (26-54 scores, N=23), and a severe CHD group (>54 scores, N=11). The DNA of the gut microbiota was then extracted from their excrement. 16S rRNA sequencing was used to compare the differences in the bacteria between the two groups. BugBase and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) were used to predict the functional composition of the bacteria. In addition, The level of plasma LPS and serum proinflammatory cytokines in the two groups was measured. Results: Plasma LPS and serum IL-1β, IL-6, and TNF-α concentrations were significantly higher in patients with CHD and significantly different among mild CHDgroup, moderate CHDgroup, and severe CHDgroup(all P＜0.05). There was no difference in the diversity of gut microbiota among the two groups (P＞0.05). At the phylum level, Bacteroidetes were more numerous in the control group. At the genus level, Enterococcus, Butyrivibrio, Dolosigranulum, Pseudomonas, and Anaerotignum were more numerous in the CHD group whereas Enterobacter, Parabacteriodes, Lachnoclostridium, Streptococcus were more numerous in the control group. PICRUSt analysis found that the level of LPS choline phosphotransferase (licD) gene expression and LPS biosynthesis correlated with LPS production was higher in the fecal microbiome of the CHD group(P＜0.05). Conclusion: The gut microbiota and LPS play a vital role in the development of atherosclerosis through its metabolites, which were anticipated to develop into a CHD diagnostic marker and unique treatment approach.