Hopping Behavior Mediates the Anomalous Confined Diffusion of Nanoparticles in Porous Hydrogels

Diffusion is an essential means of mass transport in porous materials such as hydrogels, which are appealing in various biomedical applications. Herein, we investigate the diffusive motion of nanoparticles (NPs) in porous hydrogels to provide a microscopic view of confined diffusion. Based on the mean square displacement from particle tracking experiments, we elucidate the anomalous diffusion dynamics of the embedded NPs and reveal the heterogeneous pore structures in hydrogels. The results demonstrate that diffusive NPs can intermittently escape from single pores through void connective pathways and exhibit non-Gaussian displacement probability distribution. We simulate this scenario using the Monte Carlo method and clarify the existence of hopping events in porous diffusion. The resultant anomalous diffusion can be fully depicted by combining the hopping mechanism and the hydrodynamic effect. Our results highlight the hopping behavior through the connective pathways and establish a hybrid model to predict NP transport in porous environments

Computational Investigations of the Interaction between the Cell Membrane and Nanoparticles Coated with a Pulmonary Surfactant

When inhaled nanoparticles (NPs) come into the deep lung, they develop a biomolecular corona by interacting with the pulmonary surfactant. The adsorption of the phospholipids and proteins gives a new biological identity to the NPs, which may alter their subsequent interactions with cells and other biological entities. Investigations of the interaction between the cell membrane and NPs coated with such a biomolecular corona are important in understanding the role of the biofluids on cellular uptake and estimating the dosing capacity and the nanotoxicology of NPs. In this paper, using dissipative particle dynamics, we investigate how the physicochemical properties of the coating pulmonary surfactant lipids and proteins affect the membrane response for inhaled NPs. We pinpoint several key factors in the endocytosis of lipid NPs, including the deformation of the coating lipids, coating lipid density, and ligand–receptor binding strength. Further studies reveal that the deformation of the coating lipids consumes energy but on the other hand promotes the coating ligands to bind with receptors more tightly. The coating lipid density controls the amount of the ligands as well as the hydrophobicity of the lipid NPs, thus affecting the endocytosis kinetics through the specific and nonspecific interactions. It is also found that the hydrophobic surfactant proteins associated with lipids can accelerate the endocytosis process of the NPs, but the endocytosis efficiency mainly depends on the density of the coating surfactant lipids. These findings can help understand how the pulmonary surfactant alters the biocompatibility of the inhaled NPs and provide some guidelines in designing an NP complex for efficient pulmonary drug delivery

Generation of Multiple Concentration Gradients Using a Two-Dimensional Pyramid Array

Concentration heterogeneity of diffusible reactants is a prevalent phenomenon in biochemical processes, requiring the generation of concentration gradients for the relevant experiments. In this study, we present a high-density pyramid array microfluidic network for the effective and precise generation of multiple concentration gradients. The complex gradient distribution in the 2D array can be adaptively adjusted by modulating the reactant velocities and concentrations at the inlets. In addition, the unique design of each reaction chamber and mixing block in the array ensures uniform concentrations within each chamber during dynamic changes, enabling large-scale reactions with low reactant volumes. Through detailed numerical simulation of mass transport within the complex microchannel networks, the proposed method allows researchers to determine the desired number of reaction chambers within a given concentration range based on experimental requirements and to quickly obtain the operating conditions with the help of machine learning-based prediction. The effectiveness in generating a multiple concentration gradient environment was further demonstrated by concentration-dependent calcium carbonate crystallization experiments. This device provides a highly efficient mixing and adaptable concentration platform that is well suited for high-throughput and multiplexed reactions

Generation of Multiple Concentration Gradients Using a Two-Dimensional Pyramid Array

Concentration heterogeneity of diffusible reactants is a prevalent phenomenon in biochemical processes, requiring the generation of concentration gradients for the relevant experiments. In this study, we present a high-density pyramid array microfluidic network for the effective and precise generation of multiple concentration gradients. The complex gradient distribution in the 2D array can be adaptively adjusted by modulating the reactant velocities and concentrations at the inlets. In addition, the unique design of each reaction chamber and mixing block in the array ensures uniform concentrations within each chamber during dynamic changes, enabling large-scale reactions with low reactant volumes. Through detailed numerical simulation of mass transport within the complex microchannel networks, the proposed method allows researchers to determine the desired number of reaction chambers within a given concentration range based on experimental requirements and to quickly obtain the operating conditions with the help of machine learning-based prediction. The effectiveness in generating a multiple concentration gradient environment was further demonstrated by concentration-dependent calcium carbonate crystallization experiments. This device provides a highly efficient mixing and adaptable concentration platform that is well suited for high-throughput and multiplexed reactions

Model fit of modified Smeed equation using the data of China and 13 selected countries.

<p>Model fit of modified Smeed equation using the data of China and 13 selected countries.</p

Diffusion of Nanoparticles with Activated Hopping in Crowded Polymer Solutions

A long-distance hop of diffusive nanoparticles (NPs) in crowded environments was commonly considered unlikely, and its characteristics remain unclear. In this work, we experimentally identify the occurrence of the intermittent hops of large NPs in crowded entangled poly­(ethylene oxide) (PEO) solutions, which are attributed to thermally induced activated hopping. We show that the diffusion of NPs in crowded solutions is considered as a superposition of the activated hopping and the reptation of the polymer solution. Such activated hopping becomes significant when either the PEO molecular weight is large enough or the NP size is relatively small. We reveal that the time-dependent non-Gaussianity of the NP diffusion is determined by the competition of the short-time relaxation of a polymer entanglement strand, the activated hopping, and the long-time reptation. We propose an exponential scaling law τhop/τe ∼ exp­(d/dt) to characterize the hopping time scale, suggesting a linear dependence of the activated hopping energy barrier on the dimensionless NP size. The activated hopping motion can only be observed between the onset time scale of the short-time relaxation of local entanglement strands and the termination time scale of the long-time relaxation. Our findings on activated hopping provide new insights into long-distance transportation of NPs in crowded biological environments, which is essential to the delivery and targeting of nanomedicines

Heterogeneous Nanostructures Cause Anomalous Diffusion in Lipid Monolayers

The diffusion and mobility in biomembranes are crucial for various cell functions; however, the mechanisms involved in such processes remain ambiguous due to the complex membrane structures. Herein, we investigate how the heterogeneous nanostructures cause anomalous diffusion in dipalmitoylphosphatidylcholine (DPPC) monolayers. By identifying the existence of condensed nanodomains and clarifying their impact, our findings renew the understanding of the hydrodynamic description and the statistical feature of the diffusion in the monolayers. We find a universal characteristic of the multistage mean square displacement (MSD) with an intermediate crossover, signifying two membrane viscosities at different scales: the short-time scale describes the local fluidity and is independent of the nominal DPPC density, and the long-time scale represents the global continuous phase taking into account nanodomains and increases with DPPC density. The constant short-time viscosity reflects a dynamic equilibrium between the continuous fluid phase and the condensed nanodomains in the molecular scale. Notably, we observe an “anomalous yet Brownian” phenomenon exhibiting an unusual double-peaked displacement probability distribution (DPD), which is attributed to the net dipolar repulsive force from the heterogeneous nanodomains around the microdomains. The findings provide physical insights into the transport of membrane inclusions that underpin various biological functions and drug deliveries

Road traffic mortality from police data and health data and per capita motor vehicles, China, 1970–2013.

<p>Road traffic mortality from police data and health data and per capita motor vehicles, China, 1970–2013.</p

Fitted curves between road traffic mortality and per capita motor vehicles based on modified Smeed equation.

Fitted curves between road traffic mortality and per capita motor vehicles based on modified Smeed equation.</p

Nonspecific Organelle-Targeting Strategy with Core–Shell Nanoparticles of Varied Lipid Components/Ratios

We report a nonspecific organelle-targeting strategy through one-step microfluidic fabrication and screening of a library of surface charge- and lipid components/ratios-varied lipid shell–polymer core nanoparticles. Different from the common strategy relying on the use of organelle-targeted moieties conjugated onto the surface of nanoparticles, here, we program the distribution of hybrid nanoparticles in lysosomes or mitochondria by tuning the lipid components/ratios in shell. Hybrid nanoparticles with 60% 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and 20% 1,2-dioleoyl-<i>sn</i>-glycero-3-phosphoethanolamine (DOPE) can intracellularly target mitochondria in both in vitro and in vivo models. While replacing DOPE with the same amount of 1,2-dipalmitoyl-<i>sn</i>-glycero-3-phosphocholine (DPPC), the nanoparticles do not show mitochondrial targeting, indicating an incremental effect of cationic and fusogenic lipids on lysosomal escape which is further studied by molecular dynamics simulations. This work unveils the lipid-regulated subcellular distribution of hybrid nanoparticles in which target moieties and complex synthetic steps are avoided