7 papers · ranked by Valyu relevance
Sawako Yamashiro, Misato Nomura, Nils Chapin, Sreeja Sasidharan + 5 more
Cells sense and respond to fluid shear stress. Cell surfaces are exposed to flow, yet the influence of shear stress on the behavior of plasma membrane proteins remains unclear. Here we show that extracellular flow induces the gradient distribution of cell membrane proteins with increasing concentration toward the…
Varun L. Kopparthy, Niel D. Crews
We report the development of a versatile system based on oscillating-flow methodology in a thermal gradient system for nucleic acid analysis. Analysis of DNA and RNA samples were performed in the device, without additional temperature control and complexity. The technique reported in this study eliminates the need for…
Cécile Daversin-Catty, Vegard Vinje, Kent-André Mardal, Marie E. Rognes
Flow of cerebrospinal fluid (CSF) in perivascular spaces (PVS) is one of the key concepts involved in theories concerning clearance from the brain. Experimental studies have demonstrated both net and oscillatory movement of microspheres in PVS (Mestre et al. (2018), Bedussi et al. (2018)). The oscillatory particle…
Nikhil Parthasarathy, Eleanor Batty, William Falcon, Thomas Rutten + 3 more
Decoding sensory stimuli from neural signals can be used to reveal how we sense our physical environment, and is valuable for the design of brain-machine interfaces. However, existing linear techniques for neural decoding may not fully reveal or exploit the fidelity of the neural signal. Here we develop a new…
Ganchao Wei, Daniela de Albuquerque, Miles Martinez, Shiyang Pan + 1 more
While neuroscience experiments have repeatedly demonstrated the involvement of large populations of neurons in even simple behaviors, these studies have just as often reported that the collective dynamics of neural activity are approximately low-dimensional. As a result, methods for identifying low-dimensional latent…
Nathan Mancheun Lui, Max D Li, Matthew Ford
Deep generative models for molecular graphs offer a new avenue for property optimization in drug discovery. Optimizing differentiable models that generate molecular graphs is certainly faster, cheaper, and much more accessible than traditional methods of chemical synthesis. Recent advances in generative modeling have…
Yikai Liu, Guang Lin, Ming Chen
Molecular dynamics (MD) simulations remain the standard tool for characterizing protein conformational landscapes, but their high computational cost limits large-scale and long-timescale applications. Recent generative models, especially diffusion-based approaches, provide promising alternatives by learning equilibrium…