The role and regulatory mechanisms of macrophage polarization in cardiac transplantation have gained significant attention.Macrophages can polarize into either the M1(pro-inflammatory)or M2(anti-inflammatory)phenotype...The role and regulatory mechanisms of macrophage polarization in cardiac transplantation have gained significant attention.Macrophages can polarize into either the M1(pro-inflammatory)or M2(anti-inflammatory)phenotype in response to environmental cues.M1 macrophages facilitate transplant rejection by releasing inflammatory mediators and activating T cells,whereas M2 macrophages support graft survival by secreting antiinflammatory factors and promoting tissue repair.Mitochondrial quality control regulation plays a crucial role in macrophage polarization,which may influence graft survival and immune responses.This review provides an overview of the current understanding of mitochondrial quality control-regulated macrophage polarization in cardiac transplantation,its effects on graft outcomes,and potential therapeutic strategies to modulate this process to enhance transplant success rates.The review was conducted by systematically analyzing recent studies and integrating findings from key research articles to synthesize a comprehensive understanding of this emerging field.展开更多
To explore the effect of temperature on the phase transformation of HCP→FCC during compression, the uniaxial compression process of AZ31 magnesium alloy was simulated by the molecular dynamics method, and the changes...To explore the effect of temperature on the phase transformation of HCP→FCC during compression, the uniaxial compression process of AZ31 magnesium alloy was simulated by the molecular dynamics method, and the changes of crystal structure and dislocation evolution were observed. The effects of temperature on mechanical properties, crystal structure, and dislocation evolution of magnesium alloy during compression were analyzed. It is concluded that some of the Shockley partial dislocation is related to FCC stacking faults. With the help of TEM characterization, the correctness of the correlation between some of the dislocations and FCC stacking faults is verified. Through the combination of simulation and experiment, this paper provides an idea for the in-depth study of the solid-phase transformation of magnesium alloys and provides reference and guidance for the design of magnesium alloys with good plasticity and formability at room temperature.展开更多
This study developed a new technology for preparing high-chromium cast iron(HCCI)/low-carbon steel(LCS)wear-resistant composite plates by hot rolling at a 1050°C and a rolling speed of 0.2 m/s.The effects of diff...This study developed a new technology for preparing high-chromium cast iron(HCCI)/low-carbon steel(LCS)wear-resistant composite plates by hot rolling at a 1050°C and a rolling speed of 0.2 m/s.The effects of different rolling reductions(30%,45%,and 60%)on the microstructure(interface and HCCI layer)and mechanical properties(bonding strength,hardness,and wear resistance)of the composite plate were studied.SEM images showed that when the reduction was increased,no impurities and interlayers were found between the microscopic interfaces after hot rolling,and the bonding interface exhibited a wave-like shape.EDS analysis showed that the Cr element diffusion between two metals after hot rolling was promoted when the reduction was increased,thereby improving the bonding quality under the same rolling temperature and rolling speed.Experiments showed that due to the stress release effect of the LCS of the cladded layer,the macro-slab shape after hot rolling performed well,and the brittle HCCI layer underwent thermoplastic deformation without cracking.Moreover,the increase of rolling reduction improved the bonding quality.As the rolling reduction was increased,the volume fraction of Cr-carbides in the HCCI layer also increased,resulting in an increase of hardness and wear-resistance.展开更多
Background:Cardiac surgery-associated acute kidney injury(CSA-AKI)is a major complication that increases morbidity and mortality after cardiac surgery.Most established predictive models are limited to the analysis of ...Background:Cardiac surgery-associated acute kidney injury(CSA-AKI)is a major complication that increases morbidity and mortality after cardiac surgery.Most established predictive models are limited to the analysis of nonlinear relationships and do not adequately consider intraoperative variables and early postoperative variables.Nonextracorporeal circulation coronary artery bypass grafting(off-pump CABG)remains the procedure of choice for most coronary surgeries,and refined CSA-AKI predictive models for off-pump CABG are notably lacking.Therefore,this study used an artificial intelligence-based machine learning approach to predict CSA-AKI from comprehensive perioperative data.Methods:In total,293 variables were analysed in the clinical data of patients undergoing off-pump CABG in the Department of Cardiac Surgery at the First Affiliated Hospital of Guangxi Medical University between 2012 and 2021.According to the KDIGO criteria,postoperative AKI was defined by an elevation of at least 50%within 7 days,or 0.3 mg/dL within 48 hours,with respect to the reference serum creatinine level.Five machine learning algorithms—a simple decision tree,random forest,support vector machine,extreme gradient boosting and gradient boosting decision tree(GBDT)—were used to construct the CSA-AKI predictive model.The performance of these models was evaluated with the area under the receiver operating characteristic curve(AUC).Shapley additive explanation(SHAP)values were used to explain the predictive model.Results:The three most influential features in the importance matrix plot were 1-day postoperative serum potassium concentration,1-day postoperative serum magnesium ion concentration,and 1-day postoperative serum creatine phos-phokinase concentration.Conclusion:GBDT exhibited the largest AUC(0.87)and can be used to predict the risk of AKI development after surgery,thus enabling clinicians to optimise treatment strategies and minimise postoperative complications.展开更多
基金supported by Guangxi Natural Science Foundation(2023GXNSFAA026128).
文摘The role and regulatory mechanisms of macrophage polarization in cardiac transplantation have gained significant attention.Macrophages can polarize into either the M1(pro-inflammatory)or M2(anti-inflammatory)phenotype in response to environmental cues.M1 macrophages facilitate transplant rejection by releasing inflammatory mediators and activating T cells,whereas M2 macrophages support graft survival by secreting antiinflammatory factors and promoting tissue repair.Mitochondrial quality control regulation plays a crucial role in macrophage polarization,which may influence graft survival and immune responses.This review provides an overview of the current understanding of mitochondrial quality control-regulated macrophage polarization in cardiac transplantation,its effects on graft outcomes,and potential therapeutic strategies to modulate this process to enhance transplant success rates.The review was conducted by systematically analyzing recent studies and integrating findings from key research articles to synthesize a comprehensive understanding of this emerging field.
基金supported by the National Key Research and Development Project (2018YFB1307902)Shanxi Province Joint Student Training Base Talent Training Project(No.2018JD33)+5 种基金Shanxi young top talent projectShanxi Province Science Foundation for Youths (201901D211312)Excellent young academic leaders in Shanxi colleges and universities(No.2019045)Excellent Achievements Cultivation Project of Shanxi Higher Education Institutions(No.2019KJ028)Shanxi Province emerging industry leader talent projectShanxi Graduate Education Innovation Project(No.2019SY482)。
文摘To explore the effect of temperature on the phase transformation of HCP→FCC during compression, the uniaxial compression process of AZ31 magnesium alloy was simulated by the molecular dynamics method, and the changes of crystal structure and dislocation evolution were observed. The effects of temperature on mechanical properties, crystal structure, and dislocation evolution of magnesium alloy during compression were analyzed. It is concluded that some of the Shockley partial dislocation is related to FCC stacking faults. With the help of TEM characterization, the correctness of the correlation between some of the dislocations and FCC stacking faults is verified. Through the combination of simulation and experiment, this paper provides an idea for the in-depth study of the solid-phase transformation of magnesium alloys and provides reference and guidance for the design of magnesium alloys with good plasticity and formability at room temperature.
文摘This study developed a new technology for preparing high-chromium cast iron(HCCI)/low-carbon steel(LCS)wear-resistant composite plates by hot rolling at a 1050°C and a rolling speed of 0.2 m/s.The effects of different rolling reductions(30%,45%,and 60%)on the microstructure(interface and HCCI layer)and mechanical properties(bonding strength,hardness,and wear resistance)of the composite plate were studied.SEM images showed that when the reduction was increased,no impurities and interlayers were found between the microscopic interfaces after hot rolling,and the bonding interface exhibited a wave-like shape.EDS analysis showed that the Cr element diffusion between two metals after hot rolling was promoted when the reduction was increased,thereby improving the bonding quality under the same rolling temperature and rolling speed.Experiments showed that due to the stress release effect of the LCS of the cladded layer,the macro-slab shape after hot rolling performed well,and the brittle HCCI layer underwent thermoplastic deformation without cracking.Moreover,the increase of rolling reduction improved the bonding quality.As the rolling reduction was increased,the volume fraction of Cr-carbides in the HCCI layer also increased,resulting in an increase of hardness and wear-resistance.
基金This study was partly supported by Natural Science Foundation of China(No.82060082).
文摘Background:Cardiac surgery-associated acute kidney injury(CSA-AKI)is a major complication that increases morbidity and mortality after cardiac surgery.Most established predictive models are limited to the analysis of nonlinear relationships and do not adequately consider intraoperative variables and early postoperative variables.Nonextracorporeal circulation coronary artery bypass grafting(off-pump CABG)remains the procedure of choice for most coronary surgeries,and refined CSA-AKI predictive models for off-pump CABG are notably lacking.Therefore,this study used an artificial intelligence-based machine learning approach to predict CSA-AKI from comprehensive perioperative data.Methods:In total,293 variables were analysed in the clinical data of patients undergoing off-pump CABG in the Department of Cardiac Surgery at the First Affiliated Hospital of Guangxi Medical University between 2012 and 2021.According to the KDIGO criteria,postoperative AKI was defined by an elevation of at least 50%within 7 days,or 0.3 mg/dL within 48 hours,with respect to the reference serum creatinine level.Five machine learning algorithms—a simple decision tree,random forest,support vector machine,extreme gradient boosting and gradient boosting decision tree(GBDT)—were used to construct the CSA-AKI predictive model.The performance of these models was evaluated with the area under the receiver operating characteristic curve(AUC).Shapley additive explanation(SHAP)values were used to explain the predictive model.Results:The three most influential features in the importance matrix plot were 1-day postoperative serum potassium concentration,1-day postoperative serum magnesium ion concentration,and 1-day postoperative serum creatine phos-phokinase concentration.Conclusion:GBDT exhibited the largest AUC(0.87)and can be used to predict the risk of AKI development after surgery,thus enabling clinicians to optimise treatment strategies and minimise postoperative complications.
