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Journal of Biomechanical Engineering Nov 2022Due to lack of full vascularization, the meniscus relies on diffusion through the extracellular matrix to deliver small (e.g., nutrients) and large (e.g., proteins) to...
Due to lack of full vascularization, the meniscus relies on diffusion through the extracellular matrix to deliver small (e.g., nutrients) and large (e.g., proteins) to resident cells. Under normal physiological conditions, the meniscus undergoes up to 20% compressive strains. While previous studies characterized solute diffusivity in the uncompressed meniscus, to date, little is known about the diffusive transport under physiological strain levels. This information is crucial to fully understand the pathophysiology of the meniscus. The objective of this study was to investigate strain-dependent diffusive properties of the meniscus fibrocartilage. Tissue samples were harvested from the central portion of porcine medial menisci and tested via fluorescence recovery after photobleaching to measure diffusivity of fluorescein (332 Da) and 40 K Da dextran (D40K) under 0%, 10%, and 20% compressive strain. Specifically, average diffusion coefficient and anisotropic ratio, defined as the ratio of the diffusion coefficient in the direction of the tissue collagen fibers to that orthogonal, were determined. For all the experimental conditions investigated, fluorescein diffusivity was statistically faster than that of D40K. Also, for both molecules, diffusion coefficients significantly decreased, up to ∼45%, as the strain increased. In contrast, the anisotropic ratios of both molecules were similar and not affected by the strain applied to the tissue. This suggests that compressive strains used in this study did not alter the diffusive pathways in the meniscus. Our findings provide new knowledge on the transport properties of the meniscus fibrocartilage that can be leveraged to further understand tissue pathophysiology and approaches to tissue restoration.
Topics: Animals; Anisotropy; Diffusion; Fibrocartilage; Fluoresceins; Meniscus; Swine
PubMed: 35789377
DOI: 10.1115/1.4054931 -
Journal of the Royal Society, Interface Nov 2022Budding allows virus replication and macromolecular secretion in cells through the formation of a membrane protrusion (bud) that evolves into an envelope. The largest...
Budding allows virus replication and macromolecular secretion in cells through the formation of a membrane protrusion (bud) that evolves into an envelope. The largest energetic barrier to bud formation is membrane deflection and is trespassed primarily thanks to nucleocapsid-membrane adhesion. Transmembrane proteins (TPs), which later form the virus ligands, are the main promotors of adhesion and can accommodate membrane bending thanks to an induced spontaneous curvature. Adhesive TPs must diffuse across the membrane from remote regions to gather on the bud surface, thus, diffusivity controls the kinetics. This paper proposes a simple model to describe diffusion-mediated budding unravelling important size limitations and size-dependent kinetics. The predicted optimal virion radius, giving the fastest budding, is validated against experiments for coronavirus, HIV, flu and hepatitis. Assuming exponential replication of virions and hereditary size, the model can predict the size distribution of a virus population. This is verified against experiments for SARS-CoV-2. All the above comparisons rely on the premise that budding poses the tightest size constraint. This is true in most cases, as demonstrated in this paper, where the proposed model is extended to describe virus infection via receptor- and clathrin-mediated endocytosis, and via membrane fusion.
Topics: Humans; SARS-CoV-2; COVID-19; Virus Replication; Virion; Diffusion
PubMed: 36321373
DOI: 10.1098/rsif.2022.0525 -
Physical Review Letters Jun 2023Noninterferometric experiments have been successfully employed to constrain models of spontaneous wave function collapse, which predict a violation of the quantum...
Noninterferometric experiments have been successfully employed to constrain models of spontaneous wave function collapse, which predict a violation of the quantum superposition principle for large systems. These experiments are grounded on the fact that, according to these models, the dynamics is driven by noise that, besides collapsing the wave function in space, generates a diffusive motion with characteristic signatures, which, though small, can be tested. The noninterferometric approach might seem applicable only to those models that implement the collapse through noisy dynamics, not to any model, that collapses the wave function in space. Here, we show that this is not the case: under reasonable assumptions, any collapse dynamics (in space) is diffusive. Specifically, we prove that any space-translation covariant dynamics that complies with the no-signaling constraint, if collapsing the wave function in space, must change the average momentum of the system and/or its spread.
Topics: Motion; Diffusion
PubMed: 37354406
DOI: 10.1103/PhysRevLett.130.230202 -
Biophysical Journal Jun 2020Protein diffusion in lower-dimensional spaces is used for various cellular functions. For example, sliding on DNA is essential for proteins searching for their target...
Protein diffusion in lower-dimensional spaces is used for various cellular functions. For example, sliding on DNA is essential for proteins searching for their target sites, and protein diffusion on microtubules is important for proper cell division and neuronal development. On the one hand, these linear diffusion processes are mediated by long-range electrostatic interactions between positively charged proteins and negatively charged biopolymers and have similar characteristic diffusion coefficients. On the other hand, DNA and microtubules have different structural properties. Here, using computational approaches, we studied the mechanism of protein diffusion along DNA and microtubules by exploring the diffusion of both protein types on both biopolymers. We found that DNA-binding and microtubule-binding proteins can diffuse on each other's substrates; however, the adopted diffusion mechanism depends on the molecular properties of the diffusing proteins and the biopolymers. On the protein side, only DNA-binding proteins can perform rotation-coupled diffusion along DNA, with this being due to their higher net charge and its spatial organization at the DNA recognition helix. By contrast, the lower net charge on microtubule-binding proteins enables them to diffuse more quickly than DNA-binding proteins on both biopolymers. On the biopolymer side, microtubules possess intrinsically disordered, negatively charged C-terminal tails that interact with microtubule-binding proteins, thus supporting their diffusion. Thus, although both DNA-binding and microtubule-binding proteins can diffuse on the negatively charged biopolymers, the unique molecular features of the biopolymers and of their natural substrates are essential for function.
Topics: Biopolymers; DNA; Diffusion; Microtubules; Protein Binding; Static Electricity
PubMed: 32492371
DOI: 10.1016/j.bpj.2020.05.004 -
Angewandte Chemie (International Ed. in... Mar 2022Numerous key biological processes rely on the concept of multivalency, where ligands achieve stable binding only upon engaging multiple receptors. These processes, like... (Review)
Review
Numerous key biological processes rely on the concept of multivalency, where ligands achieve stable binding only upon engaging multiple receptors. These processes, like viral entry or immune synapse formation, occur on the diffusive cellular membrane. One crucial, yet underexplored aspect of multivalent binding is the mobility of coupled receptors. Here, we discuss the consequences of mobility in multivalent processes from four perspectives: (I) The facilitation of receptor recruitment by the multivalent ligand due to their diffusivity prior to binding. (II) The effects of receptor preassembly, which allows their local accumulation. (III) The consequences of changes in mobility upon the formation of receptor/ligand complex. (IV) The changes in the diffusivity of lipid environment surrounding engaged receptors. We demonstrate how understanding mobility is essential for fully unravelling the principles of multivalent membrane processes, leading to further development in studies on receptor interactions, and guide the design of new generations of multivalent ligands.
Topics: Cell Membrane; Diffusion; Ligands; Lipids
PubMed: 34982497
DOI: 10.1002/anie.202114167 -
Journal of the American Chemical Society Aug 2022
Editorial Summary of the Comment and Responses on "Following Molecular Mobility during Chemical Reactions: No Evidence for Active Propulsion" and "Molecular Diffusivity of Click Reaction Components: The Diffusion Enhancement Question".
Topics: Diffusion
PubMed: 35919984
DOI: 10.1021/jacs.2c05873 -
Journal of Biomedical Optics Jul 2021Diffuse light is ubiquitous in biomedical optics and imaging. Understanding the process of migration of an initial photon population entering tissue to a completely...
SIGNIFICANCE
Diffuse light is ubiquitous in biomedical optics and imaging. Understanding the process of migration of an initial photon population entering tissue to a completely randomized, diffusely scattered population provides valuable insight to the interpretation and design of optical measurements.
AIM
The goal of this perspective is to present a brief, unifying analytical framework to describe how properties of light transition from an initial state to a distributed state as light diffusion occurs.
APPROACH
First, measurement parameters of light are introduced, and Monte Carlo simulations along with a simple analytical expression are used to explore how these individual parameters might exhibit diffusive behavior. Second, techniques to perform optical measurements are considered, highlighting how various measurement parameters can be leveraged to subsample photon populations.
RESULTS
Simulation results reinforce the fact that light undergoes a transition from a non-diffuse population to one that is first subdiffuse and then fully diffuse. Myriad experimental methods exist to isolate subpopulations of photons, which can be broadly categorized as source- and/or detector-encoded techniques, as well as methods of tagging the tissue of interest.
CONCLUSIONS
Characteristic properties of light progressing to diffusion can be described by some form of Gaussian distribution that grows in space, time, angle, wavelength, polarization, and coherence. In some cases, these features can be approximated by simpler exponential behavior. Experimental methods to subsample features of the photon distribution can be achieved or theoretical methods can be used to better interpret the data with this framework.
Topics: Computer Simulation; Diffusion; Monte Carlo Method; Optics and Photonics; Photons
PubMed: 34216136
DOI: 10.1117/1.JBO.26.7.070601 -
European Biophysics Journal : EBJ Dec 2015An equation of motion is derived from fractal analysis of the Brownian particle trajectory in which the asymptotic fractal dimension of the trajectory has a required...
An equation of motion is derived from fractal analysis of the Brownian particle trajectory in which the asymptotic fractal dimension of the trajectory has a required value. The formula makes it possible to calculate the time dependence of the mean square displacement for both short and long periods when the molecule diffuses anomalously. The anomalous diffusion which occurs after long periods is characterized by two variables, the transport coefficient and the anomalous diffusion exponent. An explicit formula is derived for the transport coefficient, which is related to the diffusion constant, as dependent on the Brownian step time, and the anomalous diffusion exponent. The model makes it possible to deduce anomalous diffusion properties from experimental data obtained even for short time periods and to estimate the transport coefficient in systems for which the diffusion behavior has been investigated. The results were confirmed for both sub and super-diffusion.
Topics: Diffusion; Fractals; Lipid Bilayers; Models, Theoretical
PubMed: 26129728
DOI: 10.1007/s00249-015-1054-5 -
Biophysical Journal Jun 2021From nutrient uptake to chemoreception to synaptic transmission, many systems in cell biology depend on molecules diffusing and binding to membrane receptors....
From nutrient uptake to chemoreception to synaptic transmission, many systems in cell biology depend on molecules diffusing and binding to membrane receptors. Mathematical analysis of such systems often neglects the fact that receptors process molecules at finite kinetic rates. A key example is the celebrated formula of Berg and Purcell for the rate that cell surface receptors capture extracellular molecules. Indeed, this influential result is only valid if receptors transport molecules through the cell wall at a rate much faster than molecules arrive at receptors. From a mathematical perspective, ignoring receptor kinetics is convenient because it makes the diffusing molecules independent. In contrast, including receptor kinetics introduces correlations between the diffusing molecules because, for example, bound receptors may be temporarily blocked from binding additional molecules. In this work, we present a modeling framework for coupling bulk diffusion to surface receptors with finite kinetic rates. The framework uses boundary homogenization to couple the diffusion equation to nonlinear ordinary differential equations on the boundary. We use this framework to derive an explicit formula for the cellular uptake rate and show that the analysis of Berg and Purcell significantly overestimates uptake in some typical biophysical scenarios. We confirm our analysis by numerical simulations of a many-particle stochastic system.
Topics: Diffusion; Kinetics; Ligands; Models, Biological; Receptors, Cell Surface
PubMed: 33794148
DOI: 10.1016/j.bpj.2021.03.021 -
The Journal of Chemical Physics Jan 2023We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent...
We develop a multiscale simulation model for diffusion of solutes through porous triblock copolymer membranes. The approach combines two techniques: self-consistent field theory (SCFT) to predict the structure of the self-assembled, solvated membrane and on-lattice kinetic Monte Carlo (kMC) simulations to model diffusion of solutes. Solvation is simulated in SCFT by constraining the glassy membrane matrix while relaxing the brush-like membrane pore coating against the solvent. The kMC simulations capture the resulting solute spatial distribution and concentration-dependent local diffusivity in the polymer-coated pores; we parameterize the latter using particle-based simulations. We apply our approach to simulate solute diffusion through nonequilibrium morphologies of a model triblock copolymer, and we correlate diffusivity with structural descriptors of the morphologies. We also compare the model's predictions to alternative approaches based on simple lattice random walks and find our multiscale model to be more robust and systematic to parameterize. Our multiscale modeling approach is general and can be readily extended in the future to other chemistries, morphologies, and models for the local solute diffusivity and interactions with the membrane.
Topics: Polymers; Solutions; Solvents; Diffusion; Computer Simulation
PubMed: 36641407
DOI: 10.1063/5.0127570