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Magnetic Resonance in Medicine Jun 2024Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a...
PURPOSE
Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type.
METHODS
A simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting.
RESULTS
Analysis of synthetic functional H-MRS data shows a marked decrease in parameter uncertainty as predicted by prior work. Analysis with our tool replicates the results of two previously published studies using the original in vivo functional and diffusion-weighted data. Finally, joint spectral fitting with diffusion orientation models is demonstrated in synthetic data.
CONCLUSION
A toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.
Topics: Magnetic Resonance Spectroscopy; Software; Contrast Media; Diffusion; Uncertainty
PubMed: 38265152
DOI: 10.1002/mrm.30001 -
Advances in Health Care Management Feb 2024Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and...
Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation - artificial intelligence (AI) - for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.
Topics: Humans; Artificial Intelligence; Diffusion; Diffusion of Innovation; Health Facilities; Knowledge
PubMed: 38262012
DOI: 10.1108/S1474-823120240000022005 -
The Journal of Physical Chemistry. B May 2024G protein-coupled receptors (GPCRs) are a major gateway to cellular signaling, which respond to ligands binding at extracellular sites through allosteric conformational...
G protein-coupled receptors (GPCRs) are a major gateway to cellular signaling, which respond to ligands binding at extracellular sites through allosteric conformational changes that modulate their interactions with G proteins and arrestins at intracellular sites. High-resolution structures in different ligand states, together with spectroscopic studies and molecular dynamics simulations, have revealed a rich conformational landscape of GPCRs. However, their supramolecular structure and spatiotemporal distribution is also thought to play a significant role in receptor activation and signaling bias within the native cell membrane environment. Here, we applied single-molecule fluorescence techniques, including single-particle tracking, single-molecule photobleaching, and fluorescence correlation spectroscopy, to characterize the diffusion and oligomerization behavior of the muscarinic M receptor (MR) in live cells. Control samples included the monomeric protein CD86 and fixed cells, and experiments performed in the presence of different orthosteric MR ligands and of several compounds known to change the fluidity and organization of the lipid bilayer. M receptors exhibit Brownian diffusion characterized by three diffusion constants: (∼0.01 μm/s), (∼0.04 μm/s), and (∼0.14 μm/s), whose populations were found to be modulated by both orthosteric ligands and membrane disruptors. The lipid raft disruptor C6 ceramide led to significant changes for CD86, while the diffusion of MR remained unchanged, indicating that M receptors do not partition in lipid rafts. The extent of receptor oligomerization was found to be promoted by increasing the level of expression and the binding of orthosteric ligands; in particular, the agonist carbachol elicited a large increase in the fraction of MR oligomers. This study provides new insights into the balance between conformational and environmental factors that define the movement and oligomerization states of GPCRs in live cells under close-to-native conditions.
Topics: Ligands; Receptor, Muscarinic M1; Diffusion; Humans; Cell Membrane; Protein Multimerization; Animals; Spectrometry, Fluorescence; Molecular Dynamics Simulation; Lipid Bilayers
PubMed: 38683784
DOI: 10.1021/acs.jpcb.4c01035 -
Journal of Visualized Experiments : JoVE Aug 2023Nanoimpact electrochemistry enables the time-resolved in situ characterization (e.g., size, catalytic activity) of single nanomaterial units, providing a means of...
Nanoimpact electrochemistry enables the time-resolved in situ characterization (e.g., size, catalytic activity) of single nanomaterial units, providing a means of elucidating heterogeneities that would be masked in ensemble studies. To implement this technique with redox inactive particles, a solution-phase redox reaction is used to produce a steady-state background current on a disk ultramicroelectrode. When a particle adsorbs onto the electrode, it produces a stepwise reduction in the exposed electrode area, which produces, in turn, a stepwise decrease in the current commensurate with the size of the adsorbing species. Historically, however, nanoimpact electrochemistry has suffered from "edge effects," in which the radial diffusion layer formed at the circumference of the ultramicroelectrodes renders the step size dependent not only on the size of the particle but also on where it lands on the electrode. The introduction of electrocatalytic current generation, however, mitigates the heterogeneity caused by edge effects, thus improving the measurement precision. In this approach, termed "electrocatalytic interruption," a substrate that regenerates the redox probe at the diffusion layer is introduced. This shifts the rate-limiting step of the current generation from diffusion to the homogeneous reaction rate constant, thus reducing flux heterogeneity and increasing the precision of particle sizing by an order of magnitude. The protocol described here explains the set-up and data collection employed in nanoimpact experiments implementing this effect for improved precision in the sizing of redox in-active materials.
Topics: Data Collection; Diffusion; Electrochemistry; Electrodes; Nanostructures
PubMed: 37590554
DOI: 10.3791/65116 -
The Journal of Physical Chemistry. B Aug 2023Immunoglobulin G (IgG) is the most common type of antibody found in blood and extracellular fluids and plays an essential role in our immune response. However, studies...
Immunoglobulin G (IgG) is the most common type of antibody found in blood and extracellular fluids and plays an essential role in our immune response. However, studies of the dynamics and reaction kinetics of IgG-antigen binding under physiological crowding conditions are scarce. Herein, we develop a coarse-grained model of IgG consisting of only six beads that we find minimal for a coarse representation of IgG's shape and a decent reproduction of its flexibility and diffusion properties measured experimentally. Using this model in Brownian dynamics simulations, we find that macromolecular crowding affects only slightly the IgG's flexibility, as described by the distribution of angles between the IgG's arms and stem. Our simulations indicate that, contrary to expectations, crowders slow down the translational diffusion of an IgG less strongly than they do for a smaller Ficoll 70, which we relate to the IgG's conformational size changes induced by crowding. We also find that crowders affect the binding kinetics by decreasing the rate of the first binding step and enhancing the second binding step.
Topics: Immunoglobulin G; Diffusion; Ficoll; Kinetics
PubMed: 37591305
DOI: 10.1021/acs.jpcb.3c02383 -
NeuroImage Dec 2023The dependence of the diffusion MRI signal on the diffusion time carries signatures of restricted diffusion and exchange. Here we seek to highlight these signatures in...
The dependence of the diffusion MRI signal on the diffusion time carries signatures of restricted diffusion and exchange. Here we seek to highlight these signatures in the human brain by performing experiments using free gradient waveforms designed to be selectively sensitive to the two effects. We examine six healthy volunteers using both strong and ultra-strong gradients (80, 200 and 300 mT/m). In an experiment featuring a large set of 150 gradient waveforms with different sensitivities to restricted diffusion and exchange, our results reveal unique and different time-dependence signatures in grey and white matter. Grey matter was characterised by both restricted diffusion and exchange and white matter predominantly by restricted diffusion. Exchange in grey matter was at least twice as fast as in white matter, across all subjects and all gradient strengths. The cerebellar cortex featured relatively short exchange times (115 ms). Furthermore, we show that gradient waveforms with tailored designs can be used to map exchange in the human brain. We also assessed the feasibility of clinical applications of the method used in this work and found that the exchange-related contrast obtained with a 25-minute protocol at 300 mT/m was preserved in a 4-minute protocol at 300 mT/m and a 10-minute protocol at 80 mT/m. Our work underlines the utility of free waveforms for detecting time dependence signatures due to restricted diffusion and exchange in vivo, which may potentially serve as a tool for studying diseased tissue.
Topics: Humans; Diffusion Magnetic Resonance Imaging; Brain; White Matter; Gray Matter; Diffusion
PubMed: 37839729
DOI: 10.1016/j.neuroimage.2023.120409 -
Chemosphere Aug 2023Soil characteristics play an important role in distribution of light non-aqueous phase liquid (LNAPL) spilled from buried pipeline, and enhanced understanding of...
Soil characteristics play an important role in distribution of light non-aqueous phase liquid (LNAPL) spilled from buried pipeline, and enhanced understanding of distribution is significant to the effective design of soil and groundwater remediation strategies. Therefore, distribution of diesel in soils with different porosity and temperature on the temporal evolution of the diesel migration following the saturation profiles of the two-phase flow in soils were investigated in this study. The diffusion ranges, areas and volumes in both the radial as well as in axial directions of leaked diesel in soils with different porosity and temperature increased with time. Soil porosities played an important role in the distributions when soil temperatures had no effect on distributions of diesel in soils. The distribution areas were 0.385 m, 0.294 m, 0.213 m, and 0.170 m at 60 min when the soils porosities were 0.1, 0.2, 0.3, and 0.4, respectively. The distribution volumes were 0.177 m, 0.125 m, 0.082 m, 0.060 m at 60 min when the soils porosities were 0.1, 0.2, 0.3, and 0.4, respectively. But the distribution areas were 0.213 m at 60 min when the soil temperatures were 286.15 K, 296.15 K, 306.15 K and 316.15 K, respectively. The distribution volumes were 0.082 m at 60 min when the soil temperatures were 286.15 K, 296.15 K, 306.15 K and 316.15 K, respectively. The calculation formulas of distribution areas and volumes of diesel in soils with different porosity and temperature for developing prevention and control strategies in the future were fitted. The seepage velocities of diesel changed sharply around the leakage port and decreased from about 4.9 m/s to 0 within a few millimeters in soils with different porosity. Additionally, the diffusion ranges of leaked diesel in soils with different porosity were different, indicating that soil porosity had a significant impact on seepage velocities and pressures. The seepage velocities fields and pressures fields of diesel in soils with different temperature were same at the leakage velocity of 4.9 m/s. And the study could provide some supports for determination of the safety zone and formulation of emergency response plans for LNAPL leakage accidents.
Topics: Porosity; Temperature; Soil; Soil Pollutants; Diffusion
PubMed: 37146773
DOI: 10.1016/j.chemosphere.2023.138744 -
Biophysical Journal Nov 2023To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do...
To characterize the mechanisms governing the diffusion of particles in biological scenarios, it is essential to accurately determine their diffusive properties. To do so, we propose a machine-learning method to characterize diffusion processes with time-dependent properties at the experimental time resolution. Our approach operates at the single-trajectory level predicting the properties of interest, such as the diffusion coefficient or the anomalous diffusion exponent, at every time step of the trajectory. In this way, changes in the diffusive properties occurring along the trajectory emerge naturally in the prediction and thus allow the characterization without any prior knowledge or assumption about the system. We first benchmark the method on synthetic trajectories simulated under several conditions. We show that our approach can successfully characterize both abrupt and continuous changes in the diffusion coefficient or the anomalous diffusion exponent. Finally, we leverage the method to analyze experiments of single-molecule diffusion of two membrane proteins in living cells: the pathogen-recognition receptor DC-SIGN and the integrin α5β1. The analysis allows us to characterize physical parameters and diffusive states with unprecedented accuracy, shedding new light on the underlying mechanisms.
Topics: Deep Learning; Diffusion
PubMed: 37853693
DOI: 10.1016/j.bpj.2023.10.015 -
Photosynthesis Research Nov 2023Leaf photosynthetic capacity (light-saturated net assimilation rate, A) increases from bottom to top of plant canopies as the most prominent acclimation response to the... (Review)
Review
Leaf photosynthetic capacity (light-saturated net assimilation rate, A) increases from bottom to top of plant canopies as the most prominent acclimation response to the conspicuous within-canopy gradients in light availability. Light-dependent variation in A through plant canopies is associated with changes in key leaf structural (leaf dry mass per unit leaf area), chemical (nitrogen (N) content per area and dry mass, N partitioning between components of photosynthetic machinery), and physiological (stomatal and mesophyll conductance) traits, whereas the contribution of different traits to within-canopy A gradients varies across sites, species, and plant functional types. Optimality models maximizing canopy carbon gain for a given total canopy N content predict that A should be proportionally related to canopy light availability. However, comparison of model expectations with experimental data of within-canopy photosynthetic trait variations in representative plant functional types indicates that such proportionality is not observed in real canopies, and A vs. canopy light relationships are curvilinear. The factors responsible for deviations from full optimality include stronger stomatal and mesophyll diffusion limitations at higher light, reflecting greater water limitations and more robust foliage in higher light. In addition, limits on efficient packing of photosynthetic machinery within leaf structural scaffolding, high costs of N redistribution among leaves, and limited plasticity of N partitioning among components of photosynthesis machinery constrain A plasticity. Overall, this review highlights that the variation of A through plant canopies reflects a complex interplay between adjustments of leaf structure and function to multiple environmental drivers, and that A plasticity is limited by inherent constraints on and trade-offs between structural, chemical, and physiological traits. I conclude that models trying to simulate photosynthesis gradients in plant canopies should consider co-variations among environmental drivers, and the limitation of functional trait variation by physical constraints and include the key trade-offs between structural, chemical, and physiological leaf characteristics.
Topics: Acclimatization; Carbon; Diffusion; Nitrogen; Photosynthesis; Plant Leaves; Light
PubMed: 37615905
DOI: 10.1007/s11120-023-01043-9 -
Biophysical Journal Sep 2023To generate forces that drive migration of a eukaryotic cell, arrays of actin filaments (F-actin) are assembled at the cell's leading membrane edge. To maintain cell...
To generate forces that drive migration of a eukaryotic cell, arrays of actin filaments (F-actin) are assembled at the cell's leading membrane edge. To maintain cell propulsion and respond to dynamic external cues, actin filaments must be disassembled to regenerate the actin monomers (G-actin), and transport of G-actin from sites of disassembly back to the leading edge completes the treadmilling cycle and limits the flux of F-actin assembly. Whether or not molecular diffusion is sufficient for G-actin transport has been a long-standing topic of debate, in part because the dynamic nature of cell motility and migration hinders the estimation of transport parameters. In this work, we applied an experimental system in which cells adopt an approximately constant and symmetrical shape; they cannot migrate but exhibit fast, steady treadmilling in the thin region protruding from the cell. Using fluorescence recovery after photobleaching, we quantified the relative concentrations and corresponding fluxes of F- and G-actin in this system. In conjunction with mathematical modeling, constrained by measured features of each region of interest, this approach revealed that diffusion alone cannot account for the transport of G-actin to the leading edge. Although G-actin diffusion and vectorial transport might vary with position in the protruding region, good agreement with the fluorescence recovery after photobleaching measurements was achieved by a model with constant G-actin diffusivity ∼2 μm/s and anterograde G-actin velocity less than 1 μm/s.
Topics: Actins; Actin Cytoskeleton; Cell Movement; Diffusion; Fluorescence
PubMed: 37644720
DOI: 10.1016/j.bpj.2023.08.022