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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 -
ELife Oct 2021Key processes of biological condensates are diffusion and material exchange with their environment. Experimentally, diffusive dynamics are typically probed via...
Key processes of biological condensates are diffusion and material exchange with their environment. Experimentally, diffusive dynamics are typically probed via fluorescent labels. However, to date, a physics-based, quantitative framework for the dynamics of labeled condensate components is lacking. Here, we derive the corresponding dynamic equations, building on the physics of phase separation, and quantitatively validate the related framework via experiments. We show that by using our framework, we can precisely determine diffusion coefficients inside liquid condensates via a spatio-temporal analysis of fluorescence recovery after photobleaching (FRAP) experiments. We showcase the accuracy and precision of our approach by considering space- and time-resolved data of protein condensates and two different polyelectrolyte-coacervate systems. Interestingly, our theory can also be used to determine a relationship between the diffusion coefficient in the dilute phase and the partition coefficient, without relying on fluorescence measurements in the dilute phase. This enables us to investigate the effect of salt addition on partitioning and bypasses recently described quenching artifacts in the dense phase. Our approach opens new avenues for theoretically describing molecule dynamics in condensates, measuring concentrations based on the dynamics of fluorescence intensities, and quantifying rates of biochemical reactions in liquid condensates.
Topics: Biomolecular Condensates; Diffusion; Fluorescence Recovery After Photobleaching; Polyelectrolytes; Proteins; Spatio-Temporal Analysis
PubMed: 34636323
DOI: 10.7554/eLife.68620 -
Journal of the Royal Society, Interface Feb 2024We link continuum models of reaction-diffusion systems that exhibit diffusion-driven instability to constraints on the particle-scale interactions underpinning this...
We link continuum models of reaction-diffusion systems that exhibit diffusion-driven instability to constraints on the particle-scale interactions underpinning this instability. While innumerable biological, chemical and physical patterns have been studied through the lens of Alan Turing's reaction-diffusion pattern-forming mechanism, the connections between models of pattern formation and the nature of the particle interactions generating them have been relatively understudied in comparison with the substantial efforts that have been focused on understanding proposed continuum systems. To derive the necessary reactant combinations for the most parsimonious reaction schemes, we analyse the emergent continuum models in terms of possible generating elementary reaction schemes. This analysis results in the complete list of such schemes containing the fewest reactions; these are the simplest possible hypothetical mass-action models for a pattern-forming system of two interacting species.
Topics: Models, Biological; Diffusion
PubMed: 38412962
DOI: 10.1098/rsif.2023.0490 -
Biophysical Journal May 2018The study of the dynamics of biological systems requires one to follow relaxation processes in time with micron-size spatial resolution. This need has led to the... (Review)
Review
The study of the dynamics of biological systems requires one to follow relaxation processes in time with micron-size spatial resolution. This need has led to the development of different fluorescence correlation techniques with high spatial resolution and a tremendous (from nanoseconds to seconds) temporal dynamic range. Spatiotemporal information can be obtained even on complex dynamic processes whose time evolution is not forecast by simple Brownian diffusion. Our discussion of the most recent applications of image correlation spectroscopy to the study of anomalous sub- or superdiffusion suggests that this field still requires the development of multidimensional image analyses based on analytical models or numerical simulations. We focus in particular on the framework of spatiotemporal image correlation spectroscopy and examine the critical steps in getting information on anomalous diffusive processes from the correlation maps. We point out how a dual space-time correlative analysis, in both the direct and the Fourier space, can provide quantitative information on superdiffusional processes when these are analyzed through an empirical model based on intermittent active dynamics. We believe that this dual space-time analysis, potentially amenable to mathematical treatment and to the exact fit of experimental data, could be extended to include the rich phenomenology of subdiffusive processes, thereby quantifying relevant parameters for the various motivating biological problems of interest.
Topics: Diffusion; Models, Biological; Molecular Imaging; Spectrometry, Fluorescence; Stochastic Processes
PubMed: 29477335
DOI: 10.1016/j.bpj.2018.01.034 -
Magnetic Resonance in Medicine Jun 2022To address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin-echo (OGSE) experiments, an OGSE implementation...
PURPOSE
To address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin-echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap-filled oscillating gradient shapes providing stronger diffusion encoding, and a high-performance gradient system is developed here and utilized to investigate the tradeoff between b-value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow-compensated variants are devised for experimental comparison.
METHODS
Using DTI sequences, OGSE acquisitions were performed on three volunteers at b-values of 300, 500, and 1000 s/mm and frequencies up to 125, 100, and 75 Hz, respectively; scans were performed for gap-filled oscillating gradient shapes with and without flow sensitivity. Pulsed gradient spin-echo DTI acquisitions were also performed at each b-value. Upon reconstruction, mean diffusivity (MD) maps and maps of the diffusion dispersion rate were computed.
RESULTS
The power law diffusion dispersion model was found to fit best to MD measurements acquired at b = 1000 s/mm despite the associated reduction of the spectral range; this observation was consistent with Monte Carlo simulations. Furthermore, diffusion dispersion rates without flow sensitivity were slightly higher than flow-sensitive measurements.
CONCLUSION
The presented OGSE implementation provided an improved depiction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b-values rather than higher frequencies within the regimes employed in this study.
Topics: Brain; Diffusion; Diffusion Magnetic Resonance Imaging; Humans; Monte Carlo Method
PubMed: 35049104
DOI: 10.1002/mrm.29161 -
Magnetic Resonance in Medicine Sep 2020To investigate diffusion-time dependency of diffusional kurtosis in the mouse brain using pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE)...
PURPOSE
To investigate diffusion-time dependency of diffusional kurtosis in the mouse brain using pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE) sequences.
METHODS
3D PGSE and OGSE kurtosis tensor data were acquired from ex vivo brains of adult, cuprizone-treated, and age-matched control mice with diffusion-time (t ) ~ 20 ms and frequency (f) = 70 Hz, respectively. Further, 2D acquisitions were performed at multiple times/frequencies ranging from f = 140 Hz to t = 30 ms with b-values up to 4000 s/mm . Monte Carlo simulations were used to investigate the coupled effects of varying restriction size and permeability on time/frequency-dependence of kurtosis with both diffusion-encoding schemes. Simulations and experiments were further performed to investigate the effect of varying number of cycles in OGSE waveforms.
RESULTS
Kurtosis and diffusivity maps exhibited significant region-specific changes with diffusion time/frequency across both gray and white matter areas. PGSE- and OGSE-based kurtosis maps showed reversed contrast between gray matter regions in the cerebellar and cerebral cortex. Localized time/frequency-dependent changes in kurtosis tensor metrics were found in the splenium of the corpus callosum in cuprizone-treated mouse brains, corresponding to regional demyelination seen with histological assessment. Monte Carlo simulations showed that kurtosis estimates with pulsed- and oscillating-gradient waveforms differ in their sensitivity to exchange. Both simulations and experiments showed dependence of kurtosis on number of cycles in OGSE waveforms for non-zero permeability.
CONCLUSION
The results show significant time/frequency-dependency of diffusional kurtosis in the mouse brain, which can provide sensitivity to probe intrinsic cellular heterogeneity and pathological alterations in gray and white matter.
Topics: Animals; Brain; Corpus Callosum; Diffusion; Diffusion Magnetic Resonance Imaging; Mice; White Matter
PubMed: 32022313
DOI: 10.1002/mrm.28189 -
Accounts of Chemical Research Mar 2022Organic semiconductors (OSs) are an exciting class of materials that have enabled disruptive technologies in this century including large-area electronics, flexible... (Review)
Review
Organic semiconductors (OSs) are an exciting class of materials that have enabled disruptive technologies in this century including large-area electronics, flexible displays, and inexpensive solar cells. All of these technologies rely on the motion of electrical charges within the material and the diffusivity of these charges critically determines their performance. In this respect, it is remarkable that the nature of the charge transport in these materials has puzzled the community for so many years, even for apparently simple systems such as molecular single crystals: some experiments would better fit an interpretation in terms of a localized particle picture, akin to molecular or biological electron transfer, while others are in better agreement with a wave-like interpretation, more akin to band transport in metals.Exciting recent progress in the theory and simulation of charge carrier transport in OSs has now led to a unified understanding of these disparate findings, and this Account will review one of these tools developed in our laboratory in some detail: direct charge carrier propagation by quantum-classical nonadiabatic molecular dynamics. One finds that even in defect-free crystals the charge carrier can either localize on a single molecule or substantially delocalize over a large number of molecules depending on the relative strength of electronic couplings between the molecules, reorganization, or charge trapping energy of the molecule and thermal fluctuations of electronic couplings and site energies, also known as electron-phonon couplings.Our simulations predict that in molecular OSs exhibiting some of the highest measured charge mobilities to date, the charge carrier forms "flickering" polarons, objects that are delocalized over 10-20 molecules on average and that constantly change their shape and extension under the influence of thermal disorder. The flickering polarons propagate through the OS by short (≈10 fs long) bursts of the wave function that lead to an expansion of the polaron to about twice its size, resulting in spatial displacement, carrier diffusion, charge mobility, and electrical conductivity. Arguably best termed "transient delocalization", this mechanistic scenario is very similar to the one assumed in transient localization theory and supports its assertions. We also review recent applications of our methodology to charge transport in disordered and nanocrystalline samples, which allows us to understand the influence of defects and grain boundaries on the charge propagation.Unfortunately, the energetically favorable packing structures of typical OSs, whether molecular or polymeric, places fundamental constraints on charge mobilities/electronic conductivity compared to inorganic semiconductors, which limits their range of applications. In this Account, we review the design rules that could pave the way for new very high-mobility OS materials and we argue that 2D covalent organic frameworks are one of the most promising candidates to satisfy them.We conclude that our nonadiabatic dynamics method is a powerful approach for predicting charge carrier transport in crystalline and disordered materials. We close with a brief outlook on extensions of the method to exciton transport, dissociation, and recombination. This will bring us a step closer to an understanding of the birth, survival, and annihiliation of charges at interfaces of optoelectronic devices.
Topics: Diffusion; Electronics; Electrons; Molecular Dynamics Simulation; Semiconductors
PubMed: 35196456
DOI: 10.1021/acs.accounts.1c00675 -
Bioinformatics (Oxford, England) Sep 2023As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest...
MOTIVATION
As an important player in transcriptome regulation, microRNAs may effectively diffuse somatic mutation impacts to broad cellular processes and ultimately manifest disease and dictate prognosis. Previous studies that tried to correlate mutation with gene expression dysregulation neglected to adjust for the disparate multitudes of false positives associated with unequal sample sizes and uneven class balancing scenarios.
RESULTS
To properly address this issue, we developed a statistical framework to rigorously assess the extent of mutation impact on microRNAs in relation to a permutation-based null distribution of a matching sample structure. Carrying out the framework in a pan-cancer study, we ascertained 9008 protein-coding genes with statistically significant mutation impacts on miRNAs. Of these, the collective miRNA expression for 83 genes showed significant prognostic power in nine cancer types. For example, in lower-grade glioma, 10 genes' mutations broadly impacted miRNAs, all of which showed prognostic value with the corresponding miRNA expression. Our framework was further validated with functional analysis and augmented with rich features including the ability to analyze miRNA isoforms; aggregative prognostic analysis; advanced annotations such as mutation type, regulator alteration, somatic motif, and disease association; and instructive visualization such as mutation OncoPrint, Ideogram, and interactive mRNA-miRNA network.
AVAILABILITY AND IMPLEMENTATION
The data underlying this article are available in MutMix, at http://innovebioinfo.com/Database/TmiEx/MutMix.php.
Topics: Humans; Diffusion; Glioma; MicroRNAs; Mutation; RNA, Messenger
PubMed: 37624931
DOI: 10.1093/bioinformatics/btad520 -
Robust and efficient identification of optimal mixing perturbations using proxy multiscale measures.Philosophical Transactions. Series A,... Jun 2022Understanding and optimizing passive scalar mixing in a diffusive fluid flow at finite Péclet number [Formula: see text] (where [Formula: see text] and [Formula: see...
Understanding and optimizing passive scalar mixing in a diffusive fluid flow at finite Péclet number [Formula: see text] (where [Formula: see text] and [Formula: see text] are characteristic velocity and length scales, and [Formula: see text] is the molecular diffusivisity of the scalar) is a fundamental problem of interest in many environmental and industrial flows. Particularly when [Formula: see text], identifying initial perturbations of given energy that optimally and thoroughly mix fluids of initially different properties can be computationally challenging. To address this challenge, we consider the identification of initial perturbations in an idealized two-dimensional flow on a torus that extremize various measures over finite time horizons. We identify such 'optimal' initial perturbations using the 'direct-adjoint looping' method, thus requiring the evolving flow to satisfy the governing equations and boundary conditions at all points in space and time. We demonstrate that minimizing multiscale measures commonly known as 'mix-norms' over short time horizons is a computationally efficient and robust way to identify initial perturbations that thoroughly mix layered scalar distributions over relatively long time horizons, provided the magnitude of the mix-norm's index is not too large. Minimization of such mix-norms triggers the development of coherent vortical flow structures which effectively mix, with the particular properties of these flow structures depending on [Formula: see text] and also the time horizon of interest. This article is part of the theme issue 'Mathematical problems in physical fluid dynamics (part 1)'.
Topics: Diffusion; Hydrodynamics
PubMed: 35465721
DOI: 10.1098/rsta.2021.0026 -
Single-molecule displacement mapping unveils nanoscale heterogeneities in intracellular diffusivity.Nature Methods May 2020Intracellular diffusion underlies vital cellular processes. However, it remains difficult to elucidate how an unbound protein diffuses inside the cell with good spatial...
Intracellular diffusion underlies vital cellular processes. However, it remains difficult to elucidate how an unbound protein diffuses inside the cell with good spatial resolution and sensitivity. Here we introduce single-molecule displacement/diffusivity mapping (SMdM), a super-resolution strategy that enables the nanoscale mapping of intracellular diffusivity through local statistics of the instantaneous displacements of freely diffusing single molecules. We thus show that the diffusion of an average-sized protein in the mammalian cytoplasm and nucleus is spatially heterogeneous at the nanoscale, and that variations in local diffusivity correlate with the ultrastructure of the actin cytoskeleton and the organization of the genome, respectively. SMdM of differently charged proteins further unveils that the possession of positive, but not negative, net charges drastically impedes diffusion, and that the rate is determined by the specific subcellular environments. We thus unveil rich heterogeneities and charge effects in intracellular diffusion at the nanoscale.
Topics: Cell Nucleus; Cells, Cultured; Cytoplasm; Diffusion; Humans; Image Interpretation, Computer-Assisted; Intracellular Space; Microscopy, Fluorescence; Models, Theoretical; Nanoparticles; Proteins; Single Molecule Imaging
PubMed: 32203387
DOI: 10.1038/s41592-020-0793-0