[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Mesenchymal stem cells (MSCs) are an effective therapeutic strategy to delay aging in dogs, they are prone to aging and have poor genetic stability when cultured for a long time in vitro. Therefore, it is of great significance to explore a method to improve the anti-aging ability of MSCs. Previous studies have shown that sirtuin 6 (SIRT6) plays an important role in anti-aging. This study constructed MSCs with overexpressed SIRT6 gene. Through Giemsa staining and senescence-associated β-galactosidase staining, it was found that SIRT6 significantly enhances the anti-aging capacity of MSCs. Transmission electron microscopy imaging and the detection of oxidative stress-related indicators revealed that SIRT6 improves the anti-aging capacity of MSCs by maintaining mitochondrial homeostasis and reducing oxidative stress levels. Transcriptome sequencing analysis revealed that SIRT6 mainly acted on phosphatidylinositol-3-kinase, mitogen-activated protein kinase and other aging and inflammation related pathways. In the establishment and verification of aging models in mice and dogs, it was found that the spatial memory ability of the model mice was significantly increased after intravenous transplantation of SIRT6 overexpression cells, the organ index was also significantly changed, and the anti-oxidative capacity of the dogs and mice blood was improved. The morphology of the spleens and livers in the SIRT6 overexpression cell treatment group could be effectively restored, and the expression levels of aging and inflammation-related proteins were significantly decreased. This study provides a new idea for the study of SIRT6-mediated anti-aging of MSCs.
Animals ; Dogs ; Mesenchymal Stem Cells/metabolism* ; Sirtuins/genetics* ; Aging/physiology* ; Mice ; Oxidative Stress ; Mesenchymal Stem Cell Transplantation

Imaging examination is a crucial part in diagnosis and treatment of central nervous system infection(CNSI),involving complex imaging sequences and parameters.This consensus was jointly written by multiple CNSI imaging experts in China,aimed to standardize imaging examination of CNSI.

Objective To evaluate the application of high-resolution magnetic resonance vessel wall imaging(HRMR-VWI)in identifying high-risk features of intracranial atherosclerotic plaques,and to analyze the correlation between plaque characteristics and stroke recurrence under varying degrees of stenosis.Methods The data from 368 patients with intracranial atherosclerotic stenosis(ICAS)across two centers were retrospectively analyzed.Based on the degree of stenosis,all patients were categorized into mild-to-moderate stenosis group(luminal stenosis<70%,n=155)and severe stenosis group(luminal stenosis≥70%,n=213).HRMR-VWI images and clinical information of the patients were collected and analyzed,and the culprit plaques were quantitatively analyzed.Univariate and multivariate logistic regression analyses were employed to identify the risk factors for stroke recurrence,and the predictive performance was evaluated using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve.Results Higher normalized wall index(NWI)[odds ratio(OR)=1.082,95%confidence interval(CI)1.050-1.118,P<0.05]and the presence of intraplaque hemorrhage(IPH)(OR=1.843,95%CI 1.120-3.036,P<0.05)were risk factors for stroke recurrence in all patients.And these two factors were also significant in the mild-to-moderate stenosis group(NWI:OR=1.088,95%CI 1.009-1.186,P<0.05;IPH:OR=4.049,95%CI 1.227-16.065,P<0.05).A predictive model for stroke recurrence was constructed using the combination of IPH and NWI,with the best performance in the mild-to-moderate stenosis group(AUC=0.813,95%CI 0.723-0.906).Conclusion In patients with luminal stenosis<70%,the increase of NWI and the presence of IPH have been validated as significant and effective indicators for predicting stroke recurrence,demonstrating notable predictive performance.In contrast,among patients with luminal stenosis≥70%,the utility of plaque characteristics in predicting stroke recurrence is relatively lower,indicating that the correlation between plaque characteristics and stroke recurrence varies across different degrees of stenosis.

Objective To observe the value of the integrated model of MR high-resolution vascular wall imaging(HR-VWI)and attention mechanism for predicting stroke recurrence in symptomatic intracranial atherosclerotic stenosis(sICAS)patients.Methods A total of 363 patients with sICAS who underwent HR-VWI were enrolled and stratified into training set(n=254)and validation set(n=109)according to their origins.Employing a radiomics model that utilized HR-VWI T1 and contrast-enhanced sequences for feature extraction,image data were captured from relevant plaques.Subsequently,a Trans model was developed by integrating the Transformer attention mechanism.The predictive performance and clinical utility of conventional radiomics models and Trans models for forecasting stroke recurrence among patients with sICAS were evaluated.Results In training set and validation set,the area under the curve of Trans model for predicting stroke recurrence in sICAS patients was 0.992 and 0.988,respectively,both superior to that of T1 model,T1 enhanced model and dual sequence model(all P＜0.05).The calibration curve and decision curve analysis showed that Trans model had good predictive probability and clinical practicality.Conclusion The obtained integrated model of HR-VWI radiomics combined with attention mechanism had certain value for predicting stroke recurrence in patients with sICAS.

Objective To observe the value of the integrated model of MR high-resolution vascular wall imaging(HR-VWI)and attention mechanism for predicting stroke recurrence in symptomatic intracranial atherosclerotic stenosis(sICAS)patients.Methods A total of 363 patients with sICAS who underwent HR-VWI were enrolled and stratified into training set(n=254)and validation set(n=109)according to their origins.Employing a radiomics model that utilized HR-VWI T1 and contrast-enhanced sequences for feature extraction,image data were captured from relevant plaques.Subsequently,a Trans model was developed by integrating the Transformer attention mechanism.The predictive performance and clinical utility of conventional radiomics models and Trans models for forecasting stroke recurrence among patients with sICAS were evaluated.Results In training set and validation set,the area under the curve of Trans model for predicting stroke recurrence in sICAS patients was 0.992 and 0.988,respectively,both superior to that of T1 model,T1 enhanced model and dual sequence model(all P＜0.05).The calibration curve and decision curve analysis showed that Trans model had good predictive probability and clinical practicality.Conclusion The obtained integrated model of HR-VWI radiomics combined with attention mechanism had certain value for predicting stroke recurrence in patients with sICAS.

Objective To evaluate the application of high-resolution magnetic resonance vessel wall imaging(HRMR-VWI)in identifying high-risk features of intracranial atherosclerotic plaques,and to analyze the correlation between plaque characteristics and stroke recurrence under varying degrees of stenosis.Methods The data from 368 patients with intracranial atherosclerotic stenosis(ICAS)across two centers were retrospectively analyzed.Based on the degree of stenosis,all patients were categorized into mild-to-moderate stenosis group(luminal stenosis<70%,n=155)and severe stenosis group(luminal stenosis≥70%,n=213).HRMR-VWI images and clinical information of the patients were collected and analyzed,and the culprit plaques were quantitatively analyzed.Univariate and multivariate logistic regression analyses were employed to identify the risk factors for stroke recurrence,and the predictive performance was evaluated using the area under the curve(AUC)of the receiver operating characteristic(ROC)curve.Results Higher normalized wall index(NWI)[odds ratio(OR)=1.082,95%confidence interval(CI)1.050-1.118,P<0.05]and the presence of intraplaque hemorrhage(IPH)(OR=1.843,95%CI 1.120-3.036,P<0.05)were risk factors for stroke recurrence in all patients.And these two factors were also significant in the mild-to-moderate stenosis group(NWI:OR=1.088,95%CI 1.009-1.186,P<0.05;IPH:OR=4.049,95%CI 1.227-16.065,P<0.05).A predictive model for stroke recurrence was constructed using the combination of IPH and NWI,with the best performance in the mild-to-moderate stenosis group(AUC=0.813,95%CI 0.723-0.906).Conclusion In patients with luminal stenosis<70%,the increase of NWI and the presence of IPH have been validated as significant and effective indicators for predicting stroke recurrence,demonstrating notable predictive performance.In contrast,among patients with luminal stenosis≥70%,the utility of plaque characteristics in predicting stroke recurrence is relatively lower,indicating that the correlation between plaque characteristics and stroke recurrence varies across different degrees of stenosis.

Imaging examination is a crucial part in diagnosis and treatment of central nervous system infection(CNSI),involving complex imaging sequences and parameters.This consensus was jointly written by multiple CNSI imaging experts in China,aimed to standardize imaging examination of CNSI.

Objective To investigate the risk factors of in-hospital mortality and establish a risk prediction model for patients receiving venoarterial extracorporeal membrane oxygenation(VA-ECMO).Methods We retrospectively collected the data of 302 patients receiving VA-ECMO in ICU of 3 hospitals in Guangdong Province between January,2015 and January,2022 using a convenience sampling method.The patients were divided into a derivation cohort(201 cases)and a validation cohort(101 cases).Univariate and multivariate logistic regression analyses were used to analyze the risk factors for in-hospital death of these patients,based on which a risk prediction model was established in the form of a nomogram.The receiver operator characteristic(ROC)curve,calibration curve and clinical decision curve were used to evaluate the discrimination ability,calibration and clinical validity of this model.Results The in-hospital mortality risk prediction model was established based the risk factors including hypertension(OR=3.694,95%CI:1.582-8.621),continuous renal replacement therapy(OR=9.661,95%CI:4.103-22.745),elevated Na2+ level(OR=1.048,95%CI:1.003-1.095)and increased hemoglobin level(OR=0.987,95%CI:0.977-0.998).In the derivation cohort,the area under the ROC curve(AUC)of this model was 0.829(95%CI:0.770-0.889),greater than those of the 4 single factors(all AUC<0.800),APACHE Ⅱ Score(AUC=0.777,95%CI:0.714-0.840)and the SOFA Score(AUC=0.721,95%CI:0.647-0.796).The results of internal validation showed that the AUC of the model was 0.774(95%CI:0.679-0.869),and the goodness of fit test showed a good fitting of this model(χ2=4.629,P>0.05).Conclusion The risk prediction model for in-hospital mortality of patients on VA-ECMO has good differentiation,calibration and clinical effectiveness and outperforms the commonly used disease severity scoring system,and thus can be used for assessing disease severity and prognostic risk level in critically ill patients.