Browse Articles

This study characterizes recombinant human Protein arginine methyltransferase 1 (PRMT1) expressed in Escherichia. coli and reveals that the enzyme exhibits leaky expression even without isopropyl β-D-1-thiogalactopyranoside (IPTG) induction. Through in vitro histone methyltransferase assays, we demonstrate that PRMT1 activity toward histone H4R3 is enhanced by dithiothreitol (DTT) in a dose-dependent manner but remains unresponsive to β-mercaptoethanol. These findings highlight the critical role of redox conditions in regulating PRMT1 catalytic function and provide a practical framework for future biochemical and kinetic studies.

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

This study investigates the effects of the PROTAC compound A1874 on CT26 colon carcinoma cells, focusing on its ability to degrade the protein BRD4 and reduce cell viability. While A1874 had previously shown effectiveness in other colon cancer cell lines, its impact on CT26 cells was unknown.

Predicting antibody structures and antibody-antigen complexes using AlphaFold

The authors looked at the ability of eggshells to slow ice melting. They found that eggshells were able to increase ice melting time when crushed showing that they were an effective thermal barrier.

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

Here, the authors chose to investigate the efficacy of zinc oxide nanoparticles (ZnO NPs) and cisplatin or zinc ions in inducing cancer apoptosis. While both treatments were found to reduce the proliferation of lung cancer cells, the authors suggest that further studies to identify the mechanism are necessary.

The authors test electrocardiography biofeedback as a treatment for individuals with Postural Orthostatic Tachycardia Syndrome.

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.