Deep eutectic solvent-based green extraction of Strychnos potatorum seed phenolics: Process optimization via response surface methodology and artificial neural network.

The current research focused on extraction optimization of bioactive compounds from Strychnos potatorum seeds (SPs) using an eco-friendly glycerol-sodium acetate based deep eutectic solvent (DES). The optimization was accomplished using response surface methodology (RSM) and artificial neural networking (ANN). The independent variables included shaking time (A), temperature (B), and solvent-to-feed ratio (C), and the responses were the extraction yield, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (DPPH), and antidiabetic activity (α-amylase inhibitory activity).

Automated CAD system for early detection and classification of pancreatic cancer using deep learning model.

Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due to the complex nature of CT scan images and variations in tumor shape, size, and location of the pancreatic tumor also make it challenging to detect and classify different types of tumors. Thus, to address this challenge we proposed a four-stage framework of computer-aided diagnosis systems.

Biopesticidal Efficacy of Green Synthesized Selenium-Doped Zinc Oxide Nanoparticles against Macrophomina phaseolina The causal agent of Maize Charcoal Rot.

This study explores the potential antagonistic effects of selenium-doped zinc oxide nanoparticles (Se-ZnO NPs), synthesized through a sustainable approach, on maize charcoal rot induced by the fungus Macrophomina phaseolina. Se-ZnO-NPs were prepared using the rhizobium extract of Curcuma longa and characterized for their physicochemical properties. Characterization included various in vitro parameters such as FTIR, ICP-MS, particle size, PDI, and zeta potential.

Ellagic Acid Induces DNA Damage and Apoptosis in Cancer Stem-like Cells and Overcomes Cisplatin Resistance.

Cancer stem cells (CSCs) are responsible for chemoresistance and tumor relapse in many solid malignancies, including lung and ovarian cancer. Ellagic acid (EA), a natural polyphenol, exhibits anticancer effects on various human malignancies. However, its impact and mechanism of action on cancer stem-like cells (CSLCs) are only partially understood.

Outcome reporting in studies on critically ill obstetric patients: A systematic review.

Introduction: This systematic review is the first step in the process of standardizing outcome reporting through the development of a core outcome set for research on critically ill obstetric patients (COSCO).

Methods: A five-database search was performed to identify randomized and non-randomized studies published before November 2017, on patients admitted to intensive care or high-dependency units during or immediately after pregnancy. Reported outcomes were categorized into domains and definitions were documented.