Focal adhesion kinase (FAK), ephrin receptor type A4 (EphA4), and adiponectin (ADPN) are important indicators in inflammation, tumor growth, migration, and angiogenesis in some cancers. The predictive impact of their concentrations in acute myeloid leukemia (AML) patients to be identified remains. The research sought to explore the effect of FAK, EphA4, and ADPN as prognostic biomarkers, and their influence on patient survival, and to look for any potential correlation between their levels with hematological parameters in AML patients.

In this work, mesoporous silica SBA-15 was prepared and functionalized with amine groups (i.e., NH2) to form NH2/SBA-15. The curcumin (CUR) was encapsulated into the surface and pore of NH2/SBA-15 to create CUR@NH2/SBA-15 as an efficient carrier in drug delivery systems (DDSs). The three samples (i.e., SBA-15, NH2/SBA-15, and CUR@NH2/SBA-15) were characterized. The study investigated the effect of the carrier dose, initial CUR concentration, pH, and contact time on the CUR loading efficiency (DLE%) via adsorption. The best DLE% for the SBA-15 and NH2/SBA-15 were found to be 45% and 89.7%, respectively. The Langmuir isotherm had a greater correlation coefficient (R2) of 0.998 for SBA-15. A pseudo-secondorder kinetic model seemed to fit well

Two new organotin(IV) complexes Me2Snesc (C1) and Bu2Snesc (C2) have been synthesised from the reaction of the corresponding organotin(IV) chloride with the Schiff base ligand 3,4-dihydroxybenzaldehyde-4-ethylsemicarbazone (H2esc). The ligand was prepared in two steps. The first step includes the formation of 4-ethylsemicarbazide, which then reacted with 3,4-dihydroxybenzaldehyde to give the title ligand. Complex formation between the organotin(IV) moiety and the anionic form of 3,4-dihydroxybenzaldehy-4-ethylsemicarbazone occurred through the o-dihydroxy positions. The ligand and its complexes were characterised by elemental analysis, FT-IR and NMR (1H, 13C and 119Sn) spectroscopy. Accordingly, the complexes were proposed to have tetrahedr

A theoretical and protection study was conducted of the corrosion behavior of carbon steel surface with different concentrations of the derivative (Quinolin-2-one), namly (1-Amino-4,7-dimethyl-6-nitro-1H-quinolin-2-one (ADNQ2O)). Theoretically, Density Functional Theory (DFT) of B3LYP/ 6-311++G (2d, 2p) level was used to calculate the optimized geometry, physical properties and chemical inhibition parameters, with the local reactivity to predict both the reactive centers and to locate the possible sites of nucleophilic and electrophilic attacks, in vacuum, and in two solvents (DMSO and H2O), all at the equilibrium geometry. Experimentally, the inhibition efficiencies (%IE) in the saline solution (of 3.5%) NaCl were studied using potentiomet

Platinum nanoparticles (PtNPs) exhibit promising biomedical properties, but concerns about biocompatibility and synthesis-related toxicity remain. This study aimed to develop eco-friendly PtNPs using aqueous broccoli extract as a natural reducing and stabilizing agent, and to assess their multifunctional biomedical potential. PtNPs were synthesized through sonochemical reduction of K₂PtCl₆ in broccoli extract, followed by purification and comprehensive physicochemical characterization. UV–Vis confirmed nanoparticle formation at 253 nm, while XRD and FTIR analyses verified the crystalline FCC structure and phytochemical capping. TEM revealed mainly spherical PtNPs with an average core size of 14.83 ± 7.67 nm. Conversely, DLS showe

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte