The approach of drug delivery systems emphasizes the use of nanoparticles as a vehicle, offering the optional property of delivering drugs as a single dose rather than in multiple doses. The current study aims to improve antioxidant and drug release properties of curcumin loaded gum Arabic-sodium alginate nanoparticles (Cur/ALG-GANPs). The Cur/ALG-GANPs were prepared using the ionotropic gelation technique and further subjected to physico-chemical characterization using attenuated total reflectance–Fourier transform infrared (ATR-FTIR), X-ray diffractometry (XRD), differential scanning calorimetry (DSC), size distribution, and transmission electron microscopy (TEM). The size of Cur/ALG-GANPs ranged between 10 ± 0.3 nm and 190 ± 0.1 nm and the zeta potential was –15 ± 0.2 mV. The antioxidant study of Cur/ALG-GANPs exhibited effective radical scavenging capacity for 1,1-diphenyl-2-picrylhydrazyl (DPPH) at concentrations that ranged between 30 and 500µg/mL. Cytotoxicity was performed using MTT assay to measure their potential in inhibiting the cell growth and the result demonstrated a significant anticancer activity of Cur/ALG-GANPs against human liver cancer cells (HepG2) than in colon cancer (HT29), lung cancer (A549) and breast cancer (MCF7) cells. Thus, this study indicates that Cur/ALG-GANPs have promising anticancer properties that might aid in future cancer therapy.

Background. Paravalvular leak (PVL) is common after transcatheter aortic valve implantation (TAVI) and has been linked with worse survival. This study aimed to investigate the determinants and outcome of PVL after TAVI and determine the role of aortic valve calcification (AVC) distribution in predicting PVL. Methods and Results. This was a retrospective cohort study of 270 consecutive patients who underwent TAVI. Determinants and outcomes of ≥mild PVL were assessed. Matching rates of PVL jet with AVC distribution were calculated. AVC volume, larger annulus dimensions, and transvalvular peak velocity were risk factors for ≥mild PVL after TAVI. AVC volume was an independent predictor of ≥mild PVL. On the other hand, annulus ellipticity, left ventricular outflow tract nontubularity, and diameter-derived prosthesis mismatch were not found to predict PVL after TAVI. PVL jet matched, in varying proportions, with calcification at all aortic root regions, and the highest matching rate was with calcifications at body of leaflets. Moreover, matching rates were less with commissure compared to cusp calcifications. Mild or greater PVL was not associated with all-cause and cardiovascular mortality up to 1-year follow-up. Conclusion. ≥mild PVL after TAVI is common and can be predicted by aortic root calcification volume, larger annulus dimensions, and pre-TAVI transvalvular peak velocity, with calcification volume being an independent predictor for PVL. However, annulus ellipticity, left ventricular outflow tract nontubularity, and diameter-derived prosthesis mismatch had no role in predicting PVL. Importantly, body of leaflet calcifications (versus annulus and tip of leaflet) and cusp calcifications (versus commissure calcification) are more important in predicting PVL. No association between ≥mild PVL and increased risk of all-cause and cardiovascular mortality at 1-year follow-up.

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Background: The present study aims to evaluate how nutritional status may affect transcatheter aortic valve implantation (TAVI) outcomes. Materials and Methods: This is a retrospective study of 383 TAVI patients. In-hospital, 1-month, and 12-month survival was evaluated. Since most patients undergoing TAVI are over 75 years old, the NRI definition for a geriatric population (GNRI) was used. Preoperative baseline clinical and laboratory data were collected and then the corresponding nutritional status was calculated, including Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNRI), and Controlling Nutritional Status Score (CONUT). Survival analysis and receiver operating characteristic curve (ROC) analysis were used to evaluate the correlation between these parameters and TAVI outcome. Results: By CONUT and GNRI scores, 168 (58.9%) and 40 (14.0%) patients were considered to have mild malnutrition, respectively. By using PNI, CONUT, and GNRI scores, 16 (5.7%), 29 (10.3%), and 39 (13.7%) patients were moderately or severely malnourished. Survival analysis showed that patients with worse nutritional status had a worse prognosis regardless of the nutritional score used. Subgroup analysis showed that these differences remained significant in subgroups of patients over age 75. COX multivariate analysis showed that GNRI, PNI, and CONUT were independently associated with all-cause mortality during the follow-up. Conclusion: Patients with worse nutritional status had a worse prognosis regardless of the nutritional score used. Subgroup analysis showed that these differences remained significant in subgroups of patients over age 75. GNRI, PNI, and CONUT were independent predictors of all-cause mortality after TAVI.