-
Journal of Dental Research Jul 2019The temporomandibular joint (TMJ) disc nutrient environment profoundly affects cell energy metabolism, proliferation, and biosynthesis. Due to technical challenges of in...
The temporomandibular joint (TMJ) disc nutrient environment profoundly affects cell energy metabolism, proliferation, and biosynthesis. Due to technical challenges of in vivo measurements, the human TMJ disc extracellular nutrient environment under load, which depends on metabolic rates, solute diffusion, and disc morphometry, remains unknown. Therefore, the study objective was to predict the TMJ disc nutrient environment under loading conditions using combined experimental and computational modeling approaches. Specifically, glucose consumption and lactate production rates of porcine TMJ discs were measured under varying tissue culture conditions ( = 40 discs), and mechanical strain-dependent glucose and lactate diffusivities were measured using a custom diffusion chamber ( = 6 discs). TMJ anatomy and loading area were obtained from magnetic resonance imaging of healthy human volunteers ( = 11, male, 30 ± 9 y). Using experimentally determined nutrient metabolic rates, solute diffusivities, TMJ anatomy, and loading areas, subject-specific finite element (FE) models were developed to predict the 3-dimensional nutrient profiles in unloaded and loaded TMJ discs (unloaded, 0% strain, 20% strain). From the FE models, glucose, lactate, and oxygen concentration ranges for unloaded healthy human TMJ discs were 0.6 to 4.0 mM, 0.9 to 5.0 mM, and 0% to 6%, respectively, with steep gradients in the anterior and posterior bands. Sustained mechanical loading significantly reduced nutrient levels ( < 0.001), with a critical zone in which cells may die representing approximately 13.5% of the total disc volume. In conclusion, this study experimentally determined TMJ disc metabolic rates, solute diffusivities, and disc morphometry, and through subject-specific FE modeling, revealed critical interactions between mechanical loading and nutrient supply and metabolism for the in vivo human TMJ disc. The results suggest that TMJ disc homeostasis may be vulnerable to pathological loading (e.g., clenching, bruxism), which impedes nutrient supply. Given difficulties associated with direct in vivo measurements, this study provides a new approach to systematically investigate homeostatic and degenerative mechanisms associated with the TMJ disc.
Topics: Adult; Animals; Biomechanical Phenomena; Diffusion; Energy Metabolism; Glucose; Humans; Lactic Acid; Male; Nutrients; Oxygen; Stress, Mechanical; Swine; Temporomandibular Joint Disc; Young Adult
PubMed: 31126205
DOI: 10.1177/0022034519851044 -
Magnetic Resonance in Medicine Jul 2022Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following...
PURPOSE
Relationships between diffusion-weighted MRI signals and hepatocyte microstructure were investigated to inform liver diffusion MRI modeling, focusing on the following question: Can cell size and diffusivity be estimated at fixed diffusion time, realistic SNR, and negligible contribution from extracellular/extravascular water and exchange?
METHODS
Monte Carlo simulations were performed within synthetic hepatocytes for varying cell size/diffusivity / , and clinical protocols (single diffusion encoding; maximum b-value: {1000, 1500, 2000} s/mm ; 5 unique gradient duration/separation pairs; SNR = { , 100, 80, 40, 20}), accounting for heterogeneity in and perfusion contamination. Diffusion ( ) and kurtosis ( ) coefficients were calculated, and relationships between and were visualized. Functions mapping to were computed to predict unseen values, tested for their ability to classify discrete cell-size contrasts, and deployed on 9.4T ex vivo MRI-histology data of fixed mouse livers RESULTS: Relationships between and are complex and depend on the diffusion encoding. Functions mapping to captures salient characteristics of and dependencies. Mappings are not always accurate, but they enable just under 70% accuracy in a three-class cell-size classification task (for SNR = 20, = 1500 s/mm , = 20 ms, and = 75 ms). MRI detects cell-size contrasts in the mouse livers that are confirmed by histology, but overestimates the largest cell sizes.
CONCLUSION
Salient information about liver cell size and diffusivity may be retrieved from minimal diffusion encodings at fixed diffusion time, in experimental conditions and pathological scenarios for which extracellular, extravascular water and exchange are negligible.
Topics: Animals; Contrast Media; Diffusion; Diffusion Magnetic Resonance Imaging; Hepatocytes; Magnetic Resonance Imaging; Mice; Water
PubMed: 35181943
DOI: 10.1002/mrm.29174 -
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 -
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 -
Proceedings of the National Academy of... Sep 2023Metabolic scaling theory (MST) provides an understanding of scaling in organismal morphology. Empirical data on the apparently universal pattern of tip-to-base conduit...
Metabolic scaling theory (MST) provides an understanding of scaling in organismal morphology. Empirical data on the apparently universal pattern of tip-to-base conduit widening across vascular plants motivate a set of generalized MST (gMST) relationships allowing for variable rates of conduit coalescence and taper and a transition between transport and diffusive domains. Our model, with coalescence limited to the distalmost part of the conductive system, reconciles previous MST-based models and extends their applicability to the entire plant. We derive an inverse relationship between stem volume taper and conduit widening, which implies that plant morphology is dictated by vascular optimality and not the assumption of constant sapwood area across all branching levels, contradicting Leonardo's rule. Thus, energy efficiency controls conduit coalescence rate, lowering the carbon cost needed to sustain the vascular network. Our model shows that as a plant grows taller, it must increase conduit widening and coalescence, which may make it more vulnerable to drought. We calculated how our gMST model implies a lower carbon cost to sustain a similar network compared to previous MST-based models. We also show that gMST predicts the cross-sectional area of vessels and their frequency along the relative length better than previous MST models for a range of plant types. We encourage further research obtaining data that would allow testing other gMST predictions that remain unconfirmed empirically, such as conduit coalescence rate in stems. The premise of energy efficiency can potentially become instrumental to our understanding of plant carbon allocation.
Topics: Tracheophyta; Carbon; Cardiac Conduction System Disease; Diffusion; Droughts
PubMed: 37722036
DOI: 10.1073/pnas.2215047120 -
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 Nov 2015A large number (tens of thousands) of single molecular trajectories on a cell membrane can now be collected by superresolution methods. The data contains information... (Review)
Review
A large number (tens of thousands) of single molecular trajectories on a cell membrane can now be collected by superresolution methods. The data contains information about the diffusive motion of molecule, proteins, or receptors and here we review methods for its recovery by statistical analysis of the data. The information includes the forces, organization of the membrane, the diffusion tensor, the long-time behavior of the trajectories, and more. To recover the long-time behavior and statistics of long trajectories, a stochastic model of their nonequilibrium motion is required. Modeling and data analysis serve extracting novel biophysical features at an unprecedented spatiotemporal resolution. The review presents data analysis, modeling, and stochastic simulations applied in particular on surface receptors evolving in neuronal cells.
Topics: Data Interpretation, Statistical; Diffusion; Models, Molecular; Motion; Neurons; Stochastic Processes
PubMed: 26536253
DOI: 10.1016/j.bpj.2015.09.003 -
PloS One 2023Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been...
Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been proposed to meet this requirement, among which encryption can be considered as one of the first and most effective solutions. The continuous increase in the computational power of computers and the rapid development of artificial intelligence techniques have made many previous encryption solutions not secure enough to protect data. Therefore, there is always a need to provide new and more efficient strategies for encrypting information. In this article, a two-way approach for information encryption based on chaos theory is presented. To this end, a new chaos model is first proposed. This model, in addition to having a larger key space and high sensitivity to slight key changes, can demonstrate a higher level of chaotic behavior compared to previous models. In the proposed method, first, the input is converted to a vector of bytes and first diffusion is applied on it. Then, the permutation order of chaotic sequence is used for diffusing bytes of data. In the next step, the chaotic sequence is used for applying second diffusion on confused data. Finally, to further reduce the data correlation, an iterative reversible rule-based model is used to apply final diffusion on data. The performance of the proposed method in encrypting image, text, and audio data was evaluated. The analysis of the test results showed that the proposed encryption strategy can demonstrate a pattern close to a random state by reducing data correlation at least 28.57% compared to previous works. Also, the data encrypted by proposed method, show at least 14.15% and 1.79% increment in terms of MSE and BER, respectively. In addition, key sensitivity of 10-28 and average entropy of 7.9993 in the proposed model, indicate its high resistance to brute-force, statistical, plaintext and differential attacks.
Topics: Humans; Artificial Intelligence; Confusion; Correlation of Data; Diffusion; Entropy
PubMed: 37768960
DOI: 10.1371/journal.pone.0291759