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Buffer Specificity of Ionizable Lipid Nanoparticle Transfection Efficiency and Bulk Phase Transition.
ACS Nano
March 2025
Faculty of Physics, Ludwig-Maximilians University, Geschwister-Scholl-Platz 1, 80539 Munich, Germany.
Lipid nanoparticles (LNPs) are efficient and safe carriers for mRNA vaccines based on advanced ionizable lipids. It is understood that the pH-dependent structural transition of the mesoscopic LNP core phase plays a key role in mRNA transfer. However, buffer-specific variations in transfection efficiency remain obscure.
View Article and Find Full Text PDFThe Role of Mitochondrial DNA Copy Number in Venous Thromboembolism: Insights from a 2-Sample Mendelian Randomization Study.
Ann Vasc Surg
April 2025
Department of Cardiology, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, China. Electronic address:
Background: Venous thromboembolism (VTE), including pulmonary embolism (PE) and deep vein thrombosis (DVT), is the third most common cardiovascular disease. A low amount of mitochondrial DNA copy number (mtDNA-CN) reflects mitochondrial dysfunctions and has been associations with arterial cardiovascular diseases. However, the role of mtDNA-CN in venous cardiovascular disease was unclear.
View Article and Find Full Text PDFDFT-assisted machine learning for polyester membrane design in textile wastewater recovery applications.
Water Res
March 2025
State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin, 150090, China.
Resource recovery from textile wastewater has attracted increasing interest because it simultaneously addresses wastewater treatment and maximizes the utilization of the residual dyes. Although polyester membranes have demonstrated great potential for textile wastewater recovery, tailoring high-performance polyester membranes remains a multidimensional challenge because of the complex nonlinear relationships between the membrane materials and their performance. Here we developed density functional theory (DFT)-assisted machine learning models that integrates DFT descriptors with fabrication and operation parameters to facilitate the generative design of polyester membranes.
View Article and Find Full Text PDFAccelerating polymer self-consistent field simulation and inverse DSA-lithography with deep neural networks.
J Chem Phys
March 2025
Department of Advanced Optical and Microelectronic Equipment, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China.
Self-consistent field theory (SCFT) is a powerful polymer field-theoretic simulation tool that plays a crucial role in the study of block copolymer (BCP) self-assembly. However, the computational cost of implementing SCFT simulations is comparatively high, particularly in computationally demanding applications where repeated forward simulations are needed. Herein, we propose a deep learning-based method to accelerate the SCFT simulations.
View Article and Find Full Text PDFEffective Transport by 2D Turbulence: Vortex-Gas Theory vs Scale-Invariant Inverse Cascade.
Phys Rev Lett
February 2025
Service de Physique de l'Etat Condensé, Université Paris-Saclay, CNRS, CEA, 91191 Gif-sur-Yvette, France.
The scale-invariant inverse energy cascade is a hallmark of 2D turbulence, with its theoretical energy spectrum observed in both direct numerical simulations (DNS) and laboratory experiments. Under this scale-invariance assumption, the effective diffusivity of a 2D turbulent flow is dimensionally controlled by the energy flux and the friction coefficient only. Surprisingly, however, we show that such scaling predictions are invalidated by numerical solutions of the 2D Navier-Stokes equation forced at intermediate wave number and damped by weak linear or quadratic drag.
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