Discovery of small molecules from natural compound databases as potent retinoid X alpha receptor agonists to treat Alzheimer's disease.

Alzheimer's is characterized as a progressive neurodegenerative disease due to beta-amyloid accumulation in the brain. Some previous studies reported that RXR agonists could be effective in the treatment of Alzheimer's disease. There are currently numerous attempts being made to discover a natural RXR agonist that is more potent than 9-cis-retinoic acid (9CR).

Deep Bayesian-Assisted Keypoint Detection for Pose Estimation in Assembly Automation.

Pose estimation is crucial for automating assembly tasks, yet achieving sufficient accuracy for assembly automation remains challenging and part-specific. This paper presents a novel, streamlined approach to pose estimation that facilitates automation of assembly tasks. Our proposed method employs deep learning on a limited number of annotated images to identify a set of keypoints on the parts of interest.

A comprehensive bioinformatic analysis revealed novel MicroRNA biomarkers of Parkinson's disease.

Parkinson's disease (PD) is categorized as a neurodegenerative disorder. Different studies have focused on the role of microRNAs (miRNAs) on PD progression. Due to its complexity in initiation and progression, a considerable requirement has arisen to identify novel miRNA biomarkers in a noninvasive manner.

The association between interferon lambda 3 and 4 gene single-nucleotide polymorphisms and the recovery of COVID-19 patients.

Background: The recent pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has elevated several clinical and scientific questions. These include how host genetic factors influence the pathogenesis and disease susceptibility. Therefore, the aim of this study was to evaluate the impact of interferon lambda 3 and 4 (IFNL3/4) gene polymorphisms and clinical parameters on the resistance and susceptibility to coronavirus disease 2019 (COVID-19) infection.

Selection and Characterization of Specific Nanobody Against Human Immunoglobulin G.

Nanobodies (or VHHs) are the smallest antigen-binding domain of heavy chain antibodies, which naturally occur in camelidae. The small size, monomeric nature, low immunogenicity, high solubility and stability, as well as high affinity to target in nanomolar range, makes nanobodies a promising tool for diagnostic and therapeutic application. In the present study, we developed and identified the nanobody against human IgG from an immune library using phage display technique.