Serum Osteopontin Level Is Positively Associated with Aortic Stiffness in Patients with Peritoneal Dialysis

Automatic and Early Detection of Parkinson's Disease by Analyzing Acoustic Signals Using Classification Algorithms Based on Recursive Feature Elimination Method

Parkinson's disease (PD) is a neurodegenerative condition generated by the dysfunction of brain cells and their 60-80% inability to produce dopamine, an organic chemical responsible for controlling a person's movement. This condition causes PD symptoms to appear. Diagnosis involves many physical and psychological tests and specialist examinations of the patient's nervous system, which causes several issues. The methodology method of early diagnosis of PD is based on analysing voice disorders. This method extracts a set of features from a recording of the person's voice. Then machine-learning (ML) methods are used to analyse and diagnose the recorded voice to distinguish Parkinson's cases from healthy ones. This paper proposes novel techniques to optimize the techniques for early diagnosis of PD by evaluating selected features and hyperparameter tuning of ML algorithms for diagnosing PD based on voice disorders. The dataset was balanced by the synthetic minority oversampling technique (SMOTE) and features were arranged according to their contribution to the target characteristic by the recursive feature elimination (RFE) algorithm. We applied two algorithms, t-distributed stochastic neighbour embedding (t-SNE) and principal component analysis (PCA), to reduce the dimensions of the dataset. Both t-SNE and PCA finally fed the resulting features into the classifiers support-vector machine (SVM), K-nearest neighbours (KNN), decision tree (DT), random forest (RF), and multilayer perception (MLP). Experimental results proved that the proposed techniques were superior to existing studies in which RF with the t-SNE algorithm yielded an accuracy of 97%, precision of 96.50%, recall of 94%, and F1-score of 95%. In addition, MLP with the PCA algorithm yielded an accuracy of 98%, precision of 97.66%, recall of 96%, and F1-score of 96.66%.

Osteopontin as a Biomarker in Chronic Kidney Disease

Osteopontin (OPN) is a ubiquitously expressed protein with a wide range of physiological functions, including roles in bone mineralization, immune regulation, and wound healing. OPN has been implicated in the pathogenesis of several forms of chronic kidney disease (CKD) where it promotes inflammation and fibrosis and regulates calcium and phosphate metabolism. OPN expression is increased in the kidneys, blood, and urine of patients with CKD, particularly in those with diabetic kidney disease and glomerulonephritis. The full-length OPN protein is cleaved by various proteases, including thrombin, matrix metalloproteinase (MMP)-3, MMP-7, cathepsin-D, and plasmin, producing N-terminal OPN (ntOPN), which may have more detrimental effects in CKD. Studies suggest that OPN may serve as a biomarker in CKD, and while more research is needed to fully evaluate and validate OPN and ntOPN as CKD biomarkers, the available evidence suggests that they are promising candidates for further investigation. Targeting OPN may be a potential treatment strategy. Several studies show that inhibition of OPN expression or activity can attenuate kidney injury and improve kidney function. In addition to its effects on kidney function, OPN has been linked to cardiovascular disease, which is a major cause of morbidity and mortality in patients with CKD.

Vitamin D3 Repletion Improves Vascular Function, as Measured by Cardiorenal Biomarkers in a High-Risk African American Cohort

Background: 25-hydroxy vitamin D (Vit D)-deficiency is common among patients with chronic kidney disease (CKD) and contributes to cardiovascular disease (CVD). African Americans (AAs) suffer disproportionately from CKD and CVD, and 80% of AAs are Vit D-deficient. The impact of Vit D repletion on cardio-renal biomarkers in AAs is unknown. We examined Vit D repletion on full-length osteopontin (flOPN), c-terminal fibroblast growth factor-23 (FGF-23), and plasminogen activator inhibitor-1 (PAI-1), which are implicated in vascular and kidney pathology. Methods: We performed a randomized, placebo-controlled study of high-risk AAs with Vit D deficiency, treated with 100,000 IU Vit D3 (cholecalciferol; n = 65) or placebo (n = 65) every 4 weeks for 12 weeks. We measured kidney function (CKD-EPI eGFR), protein-to-creatinine ratio, vascular function (pulse wave velocity; PWV), augmentation index, waist circumference, sitting, and 24-h-ambulatory blood pressure (BP), intact parathyroid hormone (iPTH) and serum calcium at baseline and study end, and compared Vit D levels with laboratory variables. We quantified plasma FGF-23, PAI-1, and flOPN by enzyme-linked immunosorbent assay. Multiple regression analyzed the relationship between log flOPN, FGF-23, and PAI-1 with vascular and renal risk factors. Results: Compared to placebo, Vit D3 repletion increased Vit D3 2-fold (p < 0.0001), decreased iPTH by 12% (p < 0.01) and was significantly correlated with PWV (p < 0.009). Log flOPN decreased (p = 0.03), log FGF-23 increased (p = 0.04), but log PAI-1 did not change. Multiple regression indicated association between log flOPN and PWV (p = 0.04) and diastolic BP (p = 0.02), while log FGF-23 was associated with diastolic BP (p = 0.05), and a trend with eGFR (p = 0.06). Conclusion: Vit D3 repletion may reduce flOPN and improve vascular function in high risk AAs with Vit D deficiency.