Abstract:At present, with the development of new diagnostic technologies, the detection rate of aortic dissection has been increasing year by year, but its mortality rate still remains high. Cardiovascular disease is a chronic inflammatory disease, and vascular inflammation plays a major role in the progression of aortic dissection. Therefore, this article systematically describes the specific roles and mechanisms of inflammatory cells, inflammatory factors, and inflammasomes in the development of aortic dissection.

Abstract:Aim To investigate the risk factors of death after acute Stanford type A aortic dissection (ATAAD) complicated with malperfusion syndrome (MPS). Methods 244 patients with ATAAD complicated with MPS who admitted to Nanchong Central Hospital from June 2020 to June 2023 were selected as the study objects. The postoperative survival of the patients was followed up and they were classified into survival group (156 cases) and death group (88 cases). After propensity score matching (PSM) was applied in 1∶1 matching, there were 54 cases in both groups. Univariate and Logistic regression analysis was performed to analyze the risk factors of postoperative death in patients with ATAAD complicated with MPS. Area under curve (AUC) of receiver operating characteristics (ROC) was used to analyze the prognosis of ATAAD complicated with MPS. The prediction model was established by using the regression equation y=1－1/(1+e－z) and the stability of the model was verified by cross-checking method. Results After matching, compared with the survival group (n＝54), in the death group (n＝54), the proportion of sex (male), the proportion of alcohol consumption, acute physiology and chronic health status Ⅱ (APACHE Ⅱ) score, sequential organ failure (SOFA) score, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total serum bilirubin (TSB), cholinesterase, serum creatinine (SCr), blood urea nitrogen (BUN), N-terminal pro-brain natriuretic peptide (NT-proBNP), D-dimer (D-D), white blood cell (WBC), neutrophile granulocyte (NEU), fibrinogen degradation product (FDP), platelet (PLT), fibrinogen (FIB), C-reactive protein (CRP), hypersensitive troponin, operation time, ICU stay time, ventilator stay time, hospital stay, distal extremity hypoperfusion, renal hypoperfusion were significantly increased (P＜0.05). Logistic analysis displayed that gender (male), history of drinking, NT-proBNP≥271.86 ng/L, D-D≥0.74 mg/L and NEU≥13.06×109 L－1 were independent risk factors in ATAAD patients complicated with MPS for postoperative death (P＜0.05). The combination of NT-proBNP, D-D, gender (male), alcohol drinking history and NEU (referred to as “five factors”) had the highest value in predicting ATAAD patients with MPS. The AUC of its ROC curve was 0.979 (95%CI:0.937～0.984), the sensitivity was 94.3%, and the specificity was 91.8%, which was higher than the independent predictor. The best critical value predicted by the five factors was 5.02. The survival rate of the group ＞5.02 was significantly higher than that of the group ≤5.02. Log Rank test P＜0.01. A prediction model was established based on the important factors of postoperative death in ATAAD patients with MPS. The results showed that the model had good prediction accuracy. Conclusion NT-proBNP≥271.86 ng/L, D-D≥0.74 mg/L, gender (male), history of alcohol consumption, and NEU≥×109 L－1 were independent risk factors for long-term prognosis in patients with ATAAD combined with MPS, and their combined application could effectively increase the accuracy of prognosis assessment.

Abstract:Aortic aneurysm/dissection is the primary cause of mortality in patients with Marfan syndrome (MFS).Though aberrant activation of the transforming growth factor-β(TGF-β) pathway has been considered the central pathogenic mechanism for MFS aortic aneurysms, recent research has gradually revealed the involvement of other signaling pathways in MFS. This review summarizes the latest researches on the molecular mechanisms of MFS, including classical TGF-β and related signaling pathways such as Notch and nitric oxide(NO), as well as epigenetics and gene therapy, which provide new insights for the prevention and treatment of MFS.

Abstract:Aortic dissection refers to the dissection hematoma formed when the intima of the aorta is torn by itself or external factors, and the blood in the lumen enters the middle layer of the artery wall through the intima breach. Aortic dissection is a dangerous acute disease and if the aortic dissection is completely torn, it will quickly lose blood and lead to circulatory failure and immediate death. Nonetheless, mechanistic studies of aortic dissection are currently poorly understood. Non-coding RNA is an independent RNA transcript, accounting for more than 90% of human genomic RNA. It usually does not encode protein, but acts as an important regulator to maintain normal physiological functions. So far, many studies have demonstrated that non-coding RNA are involved in the regulation of cardiovascular diseases. Therefore, much attention has been paid to the study of non-coding RNA in aortic dissection. This article reviews the mechanism of non-coding RNA in aortic dissection, and emphasizes that non-coding RNA is a biomarker of aortic dissection and a potential preventive and therapeutic means to target aortic dissection, providing a broad idea for the development of targeted drugs using non-coding RNA as a carrier in the future.

Abstract:Acute aortic dissection (AAD) is a very dangerous cardiovascular emergency. Although some progress has been made in diagnosis and treatment, the mortality rate of AAD is still high. AAD is a multi-factor involved disease, and its pathophysiological mechanism has not been fully explained, so its clinical treatment effect is limited and its mortality rate is extremely high. A large number of studies have shown that serum amyloid A (SAA), as a major inflammatory protein produced in the acute phase response, is closely related to the occurrence and development of cardiovascular diseases.Therefore, SAA may become a candidate target for the diagnosis and treatment of AAD. This review discusses the relationship between SAA and inflammatory response, vascular dysfunction, thrombosis and extracellular matrix remodeling, and the possibility of SAA as a potential biomarker of AAD.

Abstract:Aim To build a model based on general clinical variables and machine learning method to predict the risk of in-hospital major adverse events (MAE) in patients with Stanford a type aortic dissection (TAAD) after surgery. Methods A total of 1 641 patients with TAAD who underwent surgical treatment in Beijing Anzhen Hospital from January 2013 to December 2017 were included in this study. The individual characteristic variables, clinical signs and the first clinical serum markers on admission were collected. The outcome was defined as in-hospital MAE, including in-hospital death, new acute heart failure after mezzanine, respiratory failure, nervous system disorders, acute renal failure, infection, and unplanned secondary chest opening. The model was constructed after using machine learning to screen variables. Receiver operating characteristic curve (ROC) was used to analyze the ability of the model to predict in-hospital MAE. Net reclassification index (NRI) and integrated discrimination index (IDI) were used to compare the new model with the commonly used clinical models to evaluate the improvement effect of the new model in predicting the prognosis of postoperative TAAD. Finally, the nomogram was established to predict the risk of MAE in patients after TAAD operation. Results The risk prediction model of in-hospital MAE after TAAD operation was determined by using machine learning screening variables, which consisted of D-dimer, creatine kinase isoenzyme, urea, leukocyte count, age, abnormal electrocardiogram and operation time. The area under curve of ROC of in-hospital MAE predicted by the model was 0.776 (95%CI 0.718-0.734, P＜0.001). Compared with the commonly used clinical models, the NRI of our model was 0.654 (95%CI 0.540-0.750, P＜0.001), and the IDI was 0.136 (95%CI 0.117-0.155, P＜0.001), which improved the predictive ability for in-hospital MAE after TAAD operation. The model was presented in the form of nomogram, and the score of nomogram model could evaluate the risk of in-hospital MAE after TAAD operation. ConclusionsBased on machine learning, a model is constructed by using clinical variables of patients. The model can comprehensively evaluate individual characteristic variables, inflammation level, organ damage status and operation status of patients, which has predictive value for postoperative in-hospital MAE of patients with TAAD.

Abstract:Aim To explore the differential risk assessment of acute aortic syndrome (AAS) and non-ST-segment elevation myocardial infarction (NSTEMI) in patients with chest pain less than 3 hours. Methods 69 patients with AAS and 136 patients with NSTEMI were retrospectively analyzed. The data of the two groups were statistically analyzed and the differences between the two groups were compared. Univariate and multivariate Logistic regression analysis were used to evaluate the differential risk factors of AAS and NSTEMI. The area under curve (AUC) of receiver operating characteristic (ROC) of differential risk factors was compared. The value of each factor in distinguishing AAS and NSTEMI was analyzed, and the best cut-off value of partial difference risk factors was determined. Results Multivariate Logistic regression analysis showed that D-dimer (OR 8.2,5% CI 4.064～19.366), platelet distribution width (PDW) (OR 1.5,5% CI 1.253～2.133), unconjugated bilirubin (UCB) (OR 1.9,5% CI 1.003～1.317), systolic blood pressure (SBP) (OR 1.5,5% CI 1.006～1.045) were higher risk factors of AAS compared with NSTEMI. ROC curve analysis showed that AUCD-dimer＝0.944 (95%CI 0.897～0.973) and AUCPDW＝0.794 (95%CI 0.724～0.853). The optimal cut-off value of D-dimer and PDW in identifying AAS from NSTEMI was determined by using the Youden index of ROC curve. The cut-off point of ROC curve of D-dimer was 247.5 μg/L, the sensitivity was 95.7%, and the specificity was 83.8%; The cut-off point of ROC curve of PDW was 16.05%, the sensitivity was 58.8%, and the specificity was 95.6%. Conclusions D-dimer, PDW, UCB and SBP are the differential risk factors of AAS and NSTEMI. When D-dimer is lower than 247.5 μg/L, AAS can be effectively excluded, and when PDW is higher than 16.05%, AAS will probably occur.

Abstract:Aim Detection of relative expression levels of plasma miR-21 by a case-control study of acute aortic dissection (AAD), combined with receiver operating curve (ROC) and related clinical data to evaluate the diagnostic value of miR-21 for AAD. Methods 30 samples of AAD patients, 30 samples of angina patients, 29 patients with acute myocardial infarction (AMI) and 29 patients in the control group, clinical data of each group were also collected. The plasma levels of miR-21 and housekeeping gene miR-16 in each group were identified by quantitative reverse transcriptase polymerase amplification reaction, and the relative expression of miR-21 was calculated. Results Compared with the control group, the relative expression level of miR-21 in plasma of AAD group were significantly increased (P<0.05). There was no significant difference in plasma miR-21 expression between angina pectoralis group vs AAD group and AMI group vs AAD group (P>0.05). ROC curve analysis showed that the area under the curve (AUC) was 0.664.The 95% confidence interval was 0.520~0.809, and the sensitivity of plasma miR-21 to AAD diagnosis was 40%, and the specificity was 96.6%. When the comparative expression of miR-21 was 0.034, the sensitivity of plasma miR-21 to AAD diagnosis was 80%, and the specificity was 20.7%. Conclusion The detection of plasma miR-21 has definite clinical value for the diagnosis of AAD, but it is not enough to support miR-21 as an ideal molecular diagnostic marker for AAD.

Abstract:The incidence of acquired aortic diseases, such as aortic dissection, aortic aneurysm and multiple aortitis, is increasing year by year, with a tendency to become common and frequently occurring diseases. These diseases are often in critical condition, difficult to treat and with high risk of operation. However, the molecular mechanism of their pathological process is still unclear. Circular RNA (circRNA) has the characteristics of stability, tissue/developmental stage specificity, conservativeness and variety richness. CircRNA can bind to miRNA or protein, selectively regulate gene splicing or transcription and protein translation, etc. Many studies have found the presence of specific circRNA in acquired aortic diseases, so it is speculated that circRNA may be a potential biomarker and therapeutic target for acquired aortic diseases. This article will review the origin, biological characteristics, functions of circRNA, and some circRNAs which may be involved in the regulation of the molecular mechanisms of acquired aortic diseases.

Abstract:Aortic dissection (AD) is a serious cardiovascular disease with high mortality rate. It has the characteristics of rapid onset, rapid progress, complex and diverse manifestations, dangerous course, high mortality and poor prognosis. Although the specific pathogenesis of AD has not been fully elucidated, in recent years, microRNA (miRNA) has been found to play an important role in the occurrence and development of many cardiovascular diseases. Through the application of gene chip technology analysis and other related studies, it is found that there are significant differences in the expression of some microRNAs between AD patients and normal aortic tissues, which obviously contribute to the diagnosis of AD. Many studies have shown that miRNAs may play an important role in the pathogenesis and diagnosis of AD. This article reviews the research progress on differential expression and pathogenesis of miRNAs in AD.