Background: The anticancer impact of Epigallocatechin gallate (EGCG) the highly active polyphenol of green tea was abundantly studied.  Though, the exact mechanism of its cytotoxicity is still under investigation. Objectives: Hence, the current study designed to investigate the molecular target of EGCG in HepG2 cells on thirteen autophagy- and/or apoptosis- related genes. Methods: The apoptosis detection analyses such as flow cytometry and dual apoptosis assay were used. The genes expression profile was explored by the real-time quantitative-PCR. Results: EGCG increases G0/G1 cell cycle arrest and the real-time apoptosis markers proteins leading to stimulate apoptos

Objectives This work presents laser coating of grade 1 pure titanium (Ti) dental implant surface with sintered biological apatite beta-tricalcium phosphate (β-TCP), which has a chemical composition close to bone. Materials and methods Pulsed Nd:YAG laser of single pulse capability up to 70 J/10 ms and pulse peak power of 8 kW was used to implement the task. Laser pulse peak power, pulse duration, repetition rate and scanning speed were modulated to achieve the most homogenous, cohesive and highly adherent coat layer. Scanning electron microscopy (SEM), energy dispersive X-ray microscopy (EDX), optical microscopy and nanoindentation analyses were conducted to characterise and evaluate the microstructure, phases, modulus of elasticity

This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

The present study employed the NAG-4SX3-3D analyzer to precisely measure the energy response of the sensor. The goal was to enhance the understanding of this technology by providing expert information about the device. This technology offers an economical, quick, accurate, and sensitive approach. By utilizing the turbidity method, Cyproheptadine hydrochloride (CPH) was quantified in pharmaceutical samples without the need for additional substances. CPH is expected to undergo a direct reaction with calcium hexacyanoferrate, resulting in the formation of white precipitates. The linear range for CPH measurement falls within the range of (0.008–30) mM. The relative standard deviation (RSD) for six repetitions at concentrations of (6 and