Diabetes-associated cardiac autonomic neuropathy

Effects of Home-Based Exercise Training on Cardiac Autonomic Neuropathy and Metabolic Profile in Diabetic Hemodialysis Patients

Background: This study aimed to investigate the effects of a home-based exercise training program on Cardiac Autonomic Neuropathy (CAN) and metabolic profile in Diabetic Kidney Disease (DKD) patients undergoing maintenance hemodialysis (HD). Method: Twenty-eight DKD patients undergoing hemodialysis were randomly assigned into two groups. The exercise (EX) group followed a 6-month combined exercise training program at home, while the control (CO) group remained untrained. All participants at baseline and the end of the study underwent cardiopulmonary exercise testing (CPET), biochemical tests for glucose and lipid profile, and 24-h electrocardiographic monitoring for heart rate variability (HRV) analysis and heart rate turbulence (HRT). Results: At the end of the study, compared to the CO, the EX group showed a significant increase in serum high-density lipoprotein (HDL) by 27.7% (p = 0.01), peak oxygen uptake (VO2peak) by 9.3% (p < 0.05), the standard deviation of R-R intervals (SDNN) by 34.3% (p = 0.03), percentage of successive RR intervals higher than 50ms (pNN50) by 51.1% (p = 0.02), turbulence slope (TS) index by 18.4% (p = 0.01), and decrease in (glycated hemoglobin) HbA1c by 12.5% (p = 0.04) and low-frequency power LF (ms2) by 29.7% (p = 0.01). Linear regression analysis after training showed that VO2peak was correlated with SDNN (r = 0.55, p = 0.03) and HF (r = 0.72, p = 0.02). Multiple regression analysis indicated that the improvement of sympathovagal balance and aerobic capacity depended on patients’ participation in exercise training. Conclusion: In conclusion, a 6-month home-based mixed-type exercise program can improve cardiac autonomic function and metabolic profile in DKD patients on HD.

Low-fouling CNT-PEG-hydrogel coated quartz crystal microbalance sensor for saliva glucose detection

Saliva glucose detection based on a quartz crystal microbalance (QCM) sensor has emerged as a promising tool and a non-invasive diagnostic technique for diabetes. However, the low glucose concentration and strong protein interference in the saliva hinder the QCM sensors from practical applications. In this study, we present a robust and simple anti-fouling CNT-PEG-hydrogel film-coated QCM sensor for the detection of saliva glucose with high sensitivity. The CNT-PEG-hydrogel film consists of two layers; the bottom base PBA-hydrogel film is designed to recognize the glucose while the top CNT-PEG layer is used to restrict protein adsorption and improve the biocompatibility. Our results show that this CNT-PEG-hydrogel film exhibited a 10-fold enhancement on the detection limit compared to the PBA-hydrogel. Meanwhile, the adsorption of proteins on the surface of the CNT-PEG-hydrogel film, including bovine serum albumin (BSA), mucin (MUC), and fibrinogen (FIB), were reduced by 99.1%, 77.8%, and 83.7%, respectively. The CNT-PEG-hydrogel film could detect the typical saliva glucose level (0-50 mg L-1) in 10% saliva with a good responsivity. To sum up, this new tool with low-fouling film featuring high stability, specificity, and selectivity holds great potential for non-invasive monitoring of saliva glucose in human physiological levels.