MSCs released extracellular vesicles (EVs) upon hypoxia stimulation. MSC-EVs were a mixture of microvesicles and exosomes. MSC-EVs could be promptly uptaken by human umbilical vein endothelial cells. MSC-EVs promoted neoangiogenesis in vitro and in vivo. MSC-EVs preserved cardiac performance in an AMI model.

These data show the correlation between some of the parameters of serum lipids and arterial stiffness. LDL-C was independently associated with aortic stiffness, and HDL-C was independently inversely associated with aortic stiffness and peripheral stiffness.

ObjectiveBoth decreased glomerular filtration rate (GFR) and arterial stiffness were considered as risk factors for atherosclerosis. Previous studies have suggested the association between central arterial stiffness and the degree of GFR loss. Whether decreased GFR contributes to peripheral artery stiffness remains controversial. Moreover, data analyzed from a cohort of Chinese women are rare. Our aim was to explore the relationship between GFR and regional arterial stiffness in Chinese women.MethodsIn this cross-sectional study, we randomly recruited 1131 adult women residents with GFR ≥ 60 mL/min per 1.73 m2 estimated by the Chinese Modification of Diet in Renal Disease equation from three large communities. Central and peripheral arterial stiffness were estimated simultaneously by measuring carotid-femoral pulse wave velocity (PWVcf) and carotid-radial PWV (PWVcr) using a validated automatic device. Augmentation Index at heart rate 75 beats/minutes (AIx-75) was measured by pulse wave analysis as a composite parameter reflecting both large and distal arterial properties.ResultsThe mean estimated GFR (eGFR) of the study group was 100.05 ± 23.26 mL/minute per 1.73 m2. Subjects were grouped by tertiles of eGFR level. PWVcf and AIx-75 increased ongoing from the top to the bottom eGFR tertile, while the values of PWVcr were comparable. Both univariate Pearson correlations and multiple stepwise regression analyses showed that eGFR significantly correlated to PWVcf, but not to PWVcr and AIx-75.ConclusionsIn Chinese women with normal to mildly impaired renal function, decreased eGFR affected carotid-to-femoral rather than carotid-to-radial stiffening. This provides rational to conduct future prospective studies to investigate predictors of atherosclerosis in this population.

Background The N‑terminal pro-brain natriuretic peptide (NT-proBNP) has an important prognostic value in chronic renal insufficiency; however, most studies have been conducted in patients with end-stage renal disease (ESRD). In this study we evaluated the prognostic significance of NT-proBNP in very old patients with stage 3 chronic kidney disease (CKD) and compared its prognostic value in CKD3a versus CKD3b patients. Methods Patients (age ≥80 years old) hospitalized with stage 3 CKD from 2007 to 2010 who were eligible for this prospective study underwent follow-up examinations in 2015. The examinations included measurements of anthropometric characteristics, blood pressure, plasma NT-proBNP, creatinine, and lipids. End-point events were all-cause death and major adverse cardiac events (MACEs). Results A total of 168 patients (mean age 87.4 ± 2.9 years, range 80–99 years) were included in the analysis (CKD3a, n = 117; CKD3b, n = 51). The results showed that CKD3b was associated with lower hemoglobin levels, higher NT-proBNP levels and a higher rate of hypertension compared with CKD3a. After a median follow-up of 3.8 years (interquartile range 1.5–6.1 years), a higher NT-proBNP level was associated with a higher risk of all-cause death (hazard ratio HR 1.986, 95% confidence interval CI 1.276–2.819, p = 0.028) and MACEs (HR 2.872, 95% CI 1.241–6.644, p = 0.014) after adjusting for age, sex, and traditional risk factors; however, a subgroup comparison showed that elevated NT-proBNP levels were associated with a higher risk of all-cause death (HR 2.350, 95% CI 1.906–6.091, p = 0.039) and MACEs (HR 3.025, 95% CI 1.024–8.940, p = 0.045) in CKD3a but not CKD3b. Conclusion Levels of NT-proBNP increased with decreased renal function in very old patients with stage 3 CKD; therefore, NT-proBNP is an independent predictor for all-cause death and MACEs in these patients but has a greater prognostic value in CKD3a than in CKD3b.

An improved bagging algorithm, combined with a resample strategy, a neural network, and a support vector machine (SVM), is proposed for in-hospital mortality prediction using imbalanced data with very uneven ratio of positive and negative samples. This approach was compared with other machine learning algorithms such as SVM, neural network and GBDT to evaluate its effectiveness. Permutation importance algorithm was employed to assess risk factors for heart failure patients and experimental validation was conducted using medical data from the Chinese PLA General Hospital which consisted of 207 positive and 5975 negative samples, achieving area under curve (AUC), sensitivity, and specificity values of 0.850, 0.800, and 0.752, respectively. The top 5 risk factors extracted are creatinine, serum albumin, lactate dehydrogenase, platelet count, and lymphocytes. These results suggest that the proposed method has the potential to be a valuable new tool for in-hospital mortality prediction using electronic health record data.