Hemoadsorption and Coagulation Systemic Rebalance in Patients Undergoing Nonelective Cardiac Surgery and Treated with Antithrombotics.

INTRODUCTION: Insufficient withdrawal duration of antithrombotics leads to excessive bleeding after major surgery. We hypothesize that intraoperative hemoadsorption (HA) can reduce postoperative allogeneic transfusion requirements and excessive bleeding events (EBE), without an increase in ischemic/thromboembolic events (ITE) in patients who have taken antithrombotics and undergone nonelective cardiac surgery. METHODS: A total of 460 patients admitted to our hospital from 2018 to 2022 were included in this study and divided into two groups: HA and non-HA. Because of the risk of bias due to differences in antithrombotic type, withdrawal duration, or basic coagulation function, propensity score matching was used for analyses. RESULTS: Out of 154 cases in the HA group, 144 pairs were successfully matched. No HA safety events such as hemolysis, hypotension, or device failure occurred. After matching, the two groups were found to be comparable in preoperative antithrombotic type, withdrawal duration, platelets and coagulation function, and demographic and perioperative characteristics. Although the HA group did not have a reduced incidence of EBE, this group exhibited significant decreases in the transfusion rate and volume, the incidence of ITE, acute kidney injury, and central nervous system injury. CONCLUSIONS: For patients who have undergone nonelective cardiac surgery and taken antithrombotics, HA can simply and safely rebalance the postoperative coagulation system and have associations with reduced transfusion and postoperative ITE.

Non-fragile guaranteed cost control of microbial fuel cells.

A microbial fuel cell (MFC), which is a new type of energy source, utilises electrogenic bacteria in sewage or soil to convert chemical energy into electrical energy. MFCs typically require an external controller to provide a stable output voltage to the external load. This study develops a non-fragile guaranteed cost (NFGC) controller to suppress the interference of the controller of an MFC and ensure that the quadratic cost function of the system satisfies certain performance indexes. First, for the convenience of controller design, a Takagi-Sugeno fuzzy model is established to approximate a single-chamber single-population MFC model. Subsequently, the linear matrix inequality method is used to design the NFGC controller. This control scheme can reduce the influence of controller disturbances on the system and ensure asymptotic stability of the closed-loop system under the specified upper bound of the provided cost function. The simulation results demonstrate that the developed control method has a shorter adjustment time and smaller steady-state error than traditional control methods such as sliding mode control (SMC), backstepping control, and fuzzy SMC.

The prognosis of patients with postoperative hyperglycemia after Stanford type A aortic dissection surgery and construction of prediction model for postoperative hyperglycemia.

Objective: The mortality of type A aortic dissection (TAAD) is extremely high. The effect of postoperative hyperglycemia (PHG) on the prognosis of TAAD surgery is unclear. This study aims to investigate the prognosis of patients with PHG after TAAD surgery and construct prediction model for PHG. Methods: Patients underwent TAAD surgery from January 2016 to December 2020 in Xiangya Hospital were collected. A total of 203 patients were included and patients were divided into non PHG group and PHG group. The occurrence of postoperative delirium, cardiac complications, spinal cord complication, cerebral complications, acute kidney injury (AKI), hepatic dysfunction, hypoxemia, and in-hospital mortality were compared between two groups. Data from MIMIC-IV database were further applied to validate the relationship between PHG and clinical outcomes. The prediction model for PHG was then constructed using Extreme Gradient Boosting (XGBoost) analysis. The predictive value of selected features was further validated using patient data from MIMIC-IV database. Finally, the 28-days survival rate of patient with PHG was analyzed using data from MIMIC-IV database. Results: There were 86 patients developed PHG. The incidences of postoperative AKI, hepatic dysfunction, and in-hospital mortality were significant higher in PHG group. The ventilation time after surgery was significant longer in PHG group. Data from MIMIC-IV database validated these results. Neutrophil, platelet, lactic acid, weight, and lymphocyte were selected as features for prediction model. The values of AUC in training and testing set were 0.8697 and 0.8286 respectively. Then, five features were applied to construct another prediction model using data from MIMIC-IV database and the value of AUC in the new model was 0.8185. Finally, 28-days survival rate of patients with PHG was significantly lower and PHG was an independent risk factor for 28-days mortality after TAAD surgery. Conclusion: PHG was significantly associated with the occurrence of AKI, hepatic dysfunction, increased ventilation time, and in-hospital mortality after TAAD surgery. The feature combination of neutrophil, platelet, lactic acid, weight, and lymphocyte could effectively predict PHG. The 28-days survival rate of patients with PHG was significantly lower. Moreover, PHG was an independent risk factor for 28-days mortality after TAAD surgery.

MFAFNet: A Lightweight and Efficient Network with Multi-Level Feature Adaptive Fusion for Real-Time Semantic Segmentation.

Currently, real-time semantic segmentation networks are intensely demanded in resource-constrained practical applications, such as mobile devices, drones and autonomous driving systems. However, most of the current popular approaches have difficulty in obtaining sufficiently large receptive fields, and they sacrifice low-level details to improve inference speed, leading to decreased segmentation accuracy. In this paper, a lightweight and efficient multi-level feature adaptive fusion network (MFAFNet) is proposed to address this problem. Specifically, we design a separable asymmetric reinforcement non-bottleneck module, which designs a parallel structure to extract short- and long-range contextual information and use optimized convolution to increase the inference speed. In addition, we propose a feature adaptive fusion module that effectively balances feature maps with multiple resolutions to reduce the loss of spatial detail information. We evaluate our model with state-of-the-art real-time semantic segmentation methods on the Cityscapes and Camvid datasets. Without any pre-training and post-processing, our MFAFNet has only 1.27 M parameters, while achieving accuracies of 75.9% and 69.9% mean IoU with speeds of 60.1 and 82.6 FPS on the Cityscapes and Camvid test sets, respectively. The experimental results demonstrate that the proposed method achieves an excellent trade-off between inference speed, segmentation accuracy and model size.

Identification of immune-related hub genes and analysis of infiltrated immune cells of idiopathic pulmonary artery hypertension.

Objectives: Idiopathic pulmonary artery hypertension (IPAH) is a rare but life-threaten disease. However, the mechanism underlying IPAH is unclear. In this study, underlying mechanism, infiltration of immune cells, and immune-related hub genes of IPAH were analyzed via bioinformatics. Methods: GSE15197, GSE48149, GSE113439, and GSE117261 were merged as lung dataset. Weighted gene correlation network analysis (WGCNA) was used to construct the co-expression gene networks of IPAH. Gene Ontology and pathway enrichment analysis were performed using DAVID, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA). Infiltration of immune cells in lung samples was analyzed using CIBERSORT. GSE22356 and GSE33463 were merged as peripheral blood mononuclear cells (PBMCs) dataset. Immune-related differentially expressed genes (IRDEGs) of lung and PBMCs dataset were analyzed. Based on the intersection between two sets of IRDEGs, hub genes were screened using machine learning algorithms and validated by RT-qPCR. Finally, competing endogenous RNA (ceRNA) networks of hub genes were constructed. Results: The gray module was the most relevant module and genes in the module enriched in terms like inflammatory and immune responses. The results of GSEA and GSVA indicated that increasement in cytosolic calcium ion, and metabolism dysregulation play important roles in IPAH. The proportions of T cells CD4 memory resting and macrophage M1 were significantly greater in IPAH group, while the proportions of monocytes and neutrophils were significantly lower in IPAH group. IRDEGs of two datasets were analyzed and the intersection between two set of IRDEGs were identified as candidate hub genes. Predictive models for IPAH were constructed using data from PBMCs dataset with candidate hub genes as potential features via LASSO regression and XGBoost algorithm, respectively. CXCL10 and VIPR1 were identified as hub genes and ceRNA networks of CXCL10 was constructed. Conclusion: Inflammatory response, increasement in cytosolic calcium ion, and metabolism dysregulation play important roles in IPAH. T cells CD4 memory resting and macrophage M1 were significantly infiltrated in lung samples from patients with IPAH. IRDEGs of lung dataset and PBMCs dataset were analyzed, and CXCL10 and VIPR1 were identified as hub genes.

Analysis of infiltrated immune cells in left atriums from patients with atrial fibrillation and identification of circRNA biomarkers for postoperative atrial fibrillation.

Background: Atrial fibrillation (AF) increases the risk of stroke and heart failure. Postoperative AF (POAF) increases the risk of mortality after cardiac surgery. This study aims to explore mechanisms underlying AF, analyze infiltration of immune cells in left atrium (LA) from patients with AF, and identify potential circular RNA (circRNA) biomarkers for POAF. Methods: Raw data of GSE797689, GSE115574, and GSE97455 were downloaded and processed. AF-related gene co-expression network was constructed using weighted gene correlation network analysis and enrichment analysis of genes in relevant module was conducted. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied to investigate pathways significantly enriched in AF group. Infiltration of immune cells was analyzed using single-sample GSEA. Differentially expressed genes (DEGs) between patients with or without AF were identified and competing endogenous RNA (ceRNA) networks of DEGs were constructed. To screen biomarkers for POAF, differentially expressed circRNAs (DEcircRNAs) between patients with or without POAF were identified. Intersection between DEcircRNAs and circRNAs in ceRNA networks of DEGs were extracted and circRNAs in the intersection were further screened using support vector machine, random forest, and neural network to identify biomarkers for POAF. Results: Three modules were found to be relevant with AF and enrichment analysis indicated that genes in these modules were enriched in synthesis of extracellular matrix and inflammatory response. The results of GSEA and GSVA suggested that inflammatory response-related pathways were significantly enriched in AF group. Immune cells like macrophages, mast cells, and neutrophils were significantly infiltrated in LA tissues from patients with AF. The expression levels of immune genes such as CHGB, HLA-DRA, LYZ, IGKV1-17 and TYROBP were significantly upregulated in patients with AF, which were correlated with infiltration of immune cells. ceRNA networks of DEGs were constructed and has_circ_0006314 and hsa_circ_0055387 were found to have potential predictive values for POAF. Conclusion: Synthesis of extracellular matrix and inflammatory response were main processes involved in development and progression of AF. Infiltration of immune cells was significantly different between patients with or without AF. Has_circ_0006314 and hsa_circ_0055387 were found to have potential predictive values for POAF.

Comparison of the efficacy between Del Nido cardioplegia and HTK cardioplegia in Stanford type A aortic dissection patients undergoing open-heart surgery. / Del Nido停搏液和HTK停搏液在Stanford A型主动脉夹层手术中的临床效果比较.

OBJECTIVES: Acute Stanford type A aortic dissection is an extremely dangerous and life-threatening cardiovascular disease, usually treated with extracorporeal circulation heart surgery. Histidine-tryptophan-ketoglutarate (HTK) cardioplegia is a protective intracellular myocardial fluid that has been used extensively in different types of extracorporeal circulation surgeries. Del Nido cardioplegia is an extracellular myocardial protection fluid, which was first used in pediatric heart surgery and has been gradually used in a variety of pediatric and adult heart procedures. This study aims to compare the myocardial protection effect between Del Nido and HTK in patients undergoing extracorporeal circulation heart surgery for acute Stanford type A dissection and its impact on patients' prognosis by analyzing selected parameters and clinical manifestations at different time points. METHODS: Clinical data were collected from 431 patients with acute Stanford type A dissection who were diagnosed and underwent surgery between January 1, 2018 and December 31, 2020 at Xiangya Hospital, Central South University. After excluding some of the data based on exclusion criteria, patients were divided into a HTK group and a Del Nido (DN) group based on type of intraoperative cardioplegia. Propensity score-matching was performed subsequently using the the R statistical software to determine the DN group ( n =40) and HTK group ( n =41). The matching factors were age, sex, hypertension, cardiopulmonary bypass time, and aortic occlusion time. Perioperative data, postoperative complications, blood gas data, and myocardial injury data were collected from the patients, and SPSS 26.0 was used to analyze the data of each group. RESULTS: The DN group had a higher rate of spontaneous cardioversion (41.5% vs 15.0%, P =0.005) and a lower postoperative hospital stay [10.0(8.0,14.0) d vs 13.0(11.0,19.0) d, P <0.05] compared to the HTK group. In terms of changes in blood gas analysis, immediate sodium and potassium concentrations were significantly higher in the DN group than that in the HTK group (both P <0.05). There was no significant difference in myocardial injury indexes between the two groups at different time points (all P >0.05). In terms of postoperative complications, the cardiac complications in DN group were much lower than those in the HTK Group (0 vs 12.5%, P =0.026). CONCLUSIONS: Del Nido cardioplegia has similar myocardial protective effects as HTK cardioplegia used in Stanford type A aortic dissection, with a higher rate of cardiac recurrence and fewer cardiac complications. Del Nido cardioplegia should play an important role in future application for acute Stanford type A aortic dissection, but our findings need to be further validated in a large sample of prospective clinical studies.

Identification of biomarkers and analysis of infiltrated immune cells in stable and ruptured abdominal aortic aneurysms.

Objectives: The mortality rate of abdominal aortic aneurysm (AAA) is extremely high in the older population. This study aimed to identify potential biomarkers of AAA and aortic rupture and analyze infiltration of immune cells in stable and ruptured AAA samples. Methods: Raw data of GSE47472, GSE57691, and GSE98278 were downloaded. After data processing, the co-expression gene networks were constructed. Gene Ontology and pathway enrichment analysis of AAA- and aortic rupture-related gene modules were conducted using the Database for Annotation, Visualization, and Integrated Discovery. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used for further enrichment analysis. The CIBERSORT tool was used to analyze the relative abundance of immune cells in samples. Differentially expressed immune-related genes were analyzed between different samples. Predictive models were constructed via extreme gradient boosting, and hub genes were identified according to feature importance. Results: Blue and yellow modules were significantly related to AAA, and genes in these modules were associated with the aortic wall and immune response, respectively. In terms of aortic rupture, the most relevant module was significantly enriched in the inflammatory response. The results of GSEA and GSVA suggested that immune cells and the inflammatory response were involved in the development of AAA and aortic rupture. There were significant differences in the infiltration of immune cells and expression levels of immune-related genes among different samples. NFKB1 might be an important transcription factor mediating the inflammatory response of AAA and aortic rupture. After the construction of a predictive model, CD19, SELL, and CCR7 were selected as hub genes for AAA whereas OAS3, IFIT1, and IFI44L were identified as hub genes for aortic rupture. Conclusion: Weakening of the aortic wall and the immune response both contributed to the development of AAA, and the inflammatory response was closely associated with aortic rupture. The infiltration of immune cells was significantly different between different samples. NFKB1 might be an important transcription factor in AAA and aortic rupture. CD19, SELL, and CCR7 had potential diagnostic value for AAA. OAS3, IFIT1, and IFI44L might be predictive factors for aortic rupture.