ProtInteract: A deep learning framework for predicting protein-protein interactions.

Proteins mainly perform their functions by interacting with other proteins. Protein-protein interactions underpin various biological activities such as metabolic cycles, signal transduction, and immune response. However, due to the sheer number of proteins, experimental methods for finding interacting and non-interacting protein pairs are time-consuming and costly.

Protein-protein interaction prediction with deep learning: A comprehensive review.

Most proteins perform their biological function by interacting with themselves or other molecules. Thus, one may obtain biological insights into protein functions, disease prevalence, and therapy development by identifying protein-protein interactions (PPI). However, finding the interacting and non-interacting protein pairs through experimental approaches is labour-intensive and time-consuming, owing to the variety of proteins.

Eighty-Five Percent of Improved Optical Power Delivery to Epiretinal Prostheses Using Rigid Body Compensation Algorithm.

Vision impairment caused by degenerative retinal pathologies such as age-related macular degeneration can be treated using retinal implants. Such devices receive power and data using cables passing through a permanent surgical incision in the eye wall (sclera), which increases the risk to patients and surgical costs. A recently developed retinal implant design eliminates the necessity of the implant cable using a photonic power converter (PPC), which receives optical power and data through the pupil and is directed by an ellipsoidal reflector and micro-electromechanical mirror.

The Implication of Spatial Statistics in Human Mesenchymal Stem Cell Response to Nanotubular Architectures.

Introduction: In recent years there has been ample interest in nanoscale modifications of synthetic biomaterials to understand fundamental aspects of cell-surface interactions towards improved biological outcomes. In this study, we aimed at closing in on the effects of nanotubular TiO surfaces with variable nanotopography on the response on human mesenchymal stem cells (hMSCs). Although the influence of TiO nanotubes on the cellular response, and in particular on hMSC activity, has already been addressed in the past, previous studies overlooked critical morphological, structural and physical aspects that go beyond the simple nanotube diameter, such as spatial statistics.

Effects of van der Waals Force and Thermal Stresses on Pull-in Instability of Clamped Rectangular Microplates.

We study the influence of von Karman nonlinearity, van der Waals force, and a athermal stresses on pull-in instability and small vibrations of electrostatically actuated mi-croplates. We use the Galerkin method to develop a tractable reduced-order model for elec-trostatically actuated clamped rectangular microplates in the presence of van der Waals forcesand thermal stresses. More specifically, we reduce the governing two-dimensional nonlineartransient boundary-value problem to a single nonlinear ordinary differential equation.