DataSheet1_Dapagliflozin promotes angiogenesis in hindlimb ischemia mice by inducing M2 macrophage polarization.docx

Critical limb ischemia (CLI) is associated with a higher risk of limb amputation and cardiovascular death. Dapagliflozin has shown great potential in the treatment of cardiovascular disease. However, the effects of dapagliflozin on CLI and the underlying mechanisms have not been fully elucidated. We evaluated the effect of dapagliflozin on recovery from limb ischemia using a mouse model of hindlimb ischemia. The flow of perfusion was evaluated using a laser Doppler system. Tissue response was assessed by analyzing capillary density, arterial density, and the degree of fibrosis in the gastrocnemius muscle. Immunofluorescence and Western blot were used to detect the expression of macrophage polarization markers and inflammatory factors. Our findings demonstrate the significant impact of dapagliflozin on the acceleration of blood flow recovery in a hindlimb ischemia mouse model, concomitant with a notable reduction in limb necrosis. Histological analysis revealed that dapagliflozin administration augmented the expression of key angiogenic markers, specifically CD31 and α-SMA, while concurrently mitigating muscle fibrosis. Furthermore, our investigation unveiled dapagliflozin’s ability to induce a phenotypic shift of macrophages from M1 to M2, thereby diminishing the expression of inflammatory factors, including IL-1β, IL-6, and TNF-α. These effects were partially mediated through modulation of the NF-κB signaling pathway. Lastly, we observed that endothelial cell proliferation, migration, and tube-forming function are enhanced in vitro by utilizing a macrophage-conditioned medium derived from dapagliflozin treatment. Taken together, our study provides evidence that dapagliflozin holds potential as an efficacious therapeutic intervention in managing CLI by stimulating angiogenesis, thereby offering a novel option for clinical CLI treatment.</p

Image_2_A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery.TIF

BackgroundPostoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model.MethodsThis retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram.ResultsA total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595–5.206; P ConclusionCardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions.</p

Image_1_A novel predictive model for new-onset atrial fibrillation in patients after isolated cardiac valve surgery.TIF

BackgroundPostoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model.MethodsThis retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram.ResultsA total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595–5.206; P ConclusionCardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions.</p