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Nucleic Acids Research Jul 2023Target search models of DNA-binding proteins in cells typically consider search mechanisms that include 3D diffusion and 1D sliding, which can be characterized by...
Target search models of DNA-binding proteins in cells typically consider search mechanisms that include 3D diffusion and 1D sliding, which can be characterized by single-molecule tracking on DNA. However, the finding of liquid droplets of DNA and nuclear components in cells cast doubt on extrapolation from the behavior in ideal non-condensed DNA conditions to those in cells. In this study, we investigate the target search behavior of DNA-binding proteins in reconstituted DNA-condensed droplets using single-molecule fluorescence microscopy. To mimic nuclear condensates, we reconstituted DNA-condensed droplets using dextran and PEG polymers. In the DNA-condensed droplets, we measured the translational movement of four DNA-binding proteins (p53, Nhp6A, Fis and Cas9) and p53 mutants possessing different structures, sizes, and oligomeric states. Our results demonstrate the presence of fast and slow mobility modes in DNA-condensed droplets for the four DNA-binding proteins. The slow mobility mode capability is correlated strongly to the molecular size and the number of DNA-binding domains on DNA-binding proteins, but only moderately to the affinity to single DNA segments in non-condensed conditions. The slow mobility mode in DNA-condensed droplets is interpreted as a multivalent interaction mode of the DNA-binding protein to multiple DNA segments.
Topics: DNA-Binding Proteins; Tumor Suppressor Protein p53; DNA; Protein Domains; Diffusion
PubMed: 37283050
DOI: 10.1093/nar/gkad471 -
Environmental Science and Pollution... Dec 2023An in-depth understanding of gas diffusion characteristics in coal is of great value to coalbed methane (CBM) production planning and coal mine safety management....
An in-depth understanding of gas diffusion characteristics in coal is of great value to coalbed methane (CBM) production planning and coal mine safety management. However, the mechanism and model of gas diffusion is still unclear, and some methods for determining diffusion coefficients are not accurate enough. Accordingly, a free gas density gradient (FGDG)-driven coal particle gas desorption and diffusion model was established in this work, and numerical solutions were performed via finite difference method (FDM) and dimensionless method. The variation rules of dimensionless gas pressure, gas content, desorption capacity, and desorption rate were obtained. Finally, the application of the dimensionless method in diffusion modeling and diffusion coefficient inversion was discussed. The results show that the dimensionless method can simplify mathematical equation processing and analyze the common phenomena of desorption and diffusion under different parameters. The gas desorption diffusion in coal particles is from the surface to the inside, and there is obvious desorption hysteresis effect. The larger the dimensionless radius or dimensionless time, the smaller the dimensionless gas pressure, gas content, and dimensionless desorption rate. The dimensionless cumulative gas desorption amount increased rapidly first and then tended to flat with dimensionless time. The simulated curve can be easily converted into the variation curves of several different measured parameters, and the diffusion coefficient can be calculated accurately. The prediction curve of the FGDG diffusion model is in good agreement with the experimentally measured data, which verifies its reasonableness. The research content aims to provide some ideas for modeling gas desorption and diffusion behavior.
Topics: Coal; Diffusion; Gases; Safety Management
PubMed: 37962760
DOI: 10.1007/s11356-023-30886-x -
Computer Methods and Programs in... Dec 2023Medical image analysis pipelines often involve segmentation, which requires a large amount of annotated training data, which is time-consuming and costly. To address...
BACKGROUND
Medical image analysis pipelines often involve segmentation, which requires a large amount of annotated training data, which is time-consuming and costly. To address this issue, we proposed leveraging generative models to achieve few-shot image segmentation.
METHODS
We trained a denoising diffusion probabilistic model (DDPM) on 480,407 pelvis radiographs to generate 256 ✕ 256 px synthetic images. The DDPM was conditioned on demographic and radiologic characteristics and was rigorously validated by domain experts and objective image quality metrics (Frechet inception distance [FID] and inception score [IS]). For the next step, three landmarks (greater trochanter [GT], lesser trochanter [LT], and obturator foramen [OF]) were annotated on 45 real-patient radiographs; 25 for training and 20 for testing. To extract features, each image was passed through the pre-trained DDPM at three timesteps and for each pass, features from specific blocks were extracted. The features were concatenated with the real image to form an image with 4225 channels. The feature-set was broken into random patches, which were fed to a U-Net. Dice Similarity Coefficient (DSC) was used to compare the performance with a vanilla U-Net trained on radiographs.
RESULTS
Expert accuracy was 57.5 % in determining real versus generated images, while the model reached an FID = 7.2 and IS = 210. The segmentation UNet trained on the 20 feature-sets achieved a DSC of 0.90, 0.84, and 0.61 for OF, GT, and LT segmentation, respectively, which was at least 0.30 points higher than the naively trained model.
CONCLUSION
We demonstrated the applicability of DDPMs as feature extractors, facilitating medical image segmentation with few annotated samples.
Topics: Humans; Benchmarking; Bisacodyl; Diffusion; Femur; Image Processing, Computer-Assisted
PubMed: 37778140
DOI: 10.1016/j.cmpb.2023.107832 -
Food Research International (Ottawa,... Dec 2023The microstructural changes in papaya tissue during calcium diffusion, the effect on drying kinetics and texture parameters were investigated. Calcium pretreatment was...
The microstructural changes in papaya tissue during calcium diffusion, the effect on drying kinetics and texture parameters were investigated. Calcium pretreatment was applied to papaya samples for 3 h, at a solution concentration of 1.5 g Ca(OH)/100 mL HO, and a solution temperature of 25 °C; subsequently, the samples were convectively dried at 70 °C, air flow of 1.5 m/s, and a relative humidity of 5 ± 2%. Calcium content was determined using the Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) technique, the microstructure of the samples was analyzed by High-Resolution Scanning Electron Microscopy (HR-SEM), and the elementary analysis was performed by Energy-Dispersive X-ray Spectroscopy (EDS). Effective diffusivity of calcium (D) and moisture (D) were calculated during pretreatment and drying, respectively and texture parameters were determined by double compression using a texturometer. The transport mechanism determined during calcium pretreatment was diffusion with a D = 3.10 × 10 m/s. Also, branched calcium microstructures in the cell walls of tissue were observed due to the calcium effect, it was supported by elemental analysis, which showed an increase of calcium in section restructured compared to non-restructured. During drying, D = 1.86 × 10 m/s was higher in pretreated compared to non-pretreated samples with D = 1.17 × 10 m/s, indicating a higher drying rate and moisture loss. The texture values changed significantly (α ≤ 0.05) due to calcium pretreatment and drying; the calcium microstructures caused higher cohesiveness, springiness, gumminess, and chewiness. Calcium modifies the microstructure and composition of papaya tissue; therefore, drying kinetics and texture parameters depend on this modification.
Topics: Calcium; Carica; Desiccation; Temperature; Diffusion; Calcium, Dietary
PubMed: 37986494
DOI: 10.1016/j.foodres.2023.113491 -
PLoS Computational Biology Sep 2023Sedimentation velocity analytical ultracentrifugation (SV-AUC) is an indispensable tool for the study of particle size distributions in biopharmaceutical industry, for...
Sedimentation velocity analytical ultracentrifugation (SV-AUC) is an indispensable tool for the study of particle size distributions in biopharmaceutical industry, for example, to characterize protein therapeutics and vaccine products. In particular, the diffusion-deconvoluted sedimentation coefficient distribution analysis, in the software SEDFIT, has found widespread applications due to its relatively high resolution and sensitivity. However, a lack of suitable software compatible with Good Manufacturing Practices (GMP) has hampered the use of SV-AUC in this regulatory environment. To address this, we have created an interface for SEDFIT so that it can serve as an automatically spawned module with controlled data input through command line parameters and output of key results in files. The interface can be integrated in custom GMP compatible software, and in scripts that provide documentation and meta-analyses for replicate or related samples, for example, to streamline analysis of large families of experimental data, such as binding isotherm analyses in the study of protein interactions. To test and demonstrate this approach we provide a MATLAB script mlSEDFIT.
Topics: Commerce; Diffusion; Documentation; Records; Software
PubMed: 37669309
DOI: 10.1371/journal.pcbi.1011454 -
Bio Systems Oct 2023Calcium is one of the most versatile messengers for intracellular signaling. In the case of cilia and flagella calcium has the central role in transfer of communications...
Calcium is one of the most versatile messengers for intracellular signaling. In the case of cilia and flagella calcium has the central role in transfer of communications between extracellular stimuli and intracellular formation of frequency modulated signal and their deciphering by target proteins. In this paper, the diffusion of fluorescently or otherwise tagged and un-tagged Ca particles is analyzed by solving the system of pertaining reaction-diffusion equations. We used Fourier transform tools to get asymptotic eigenfunctions for tagged (un-tagged) free and buffered Ca ions. We made some numerical estimations for diffusion coefficients corroborating the fact that messages diffuse faster than Ca messengers. From the best of our knowledge, this is the first time that Ca signaling in living cells is biophysically elaborated within the framework of model presented here. We suggest the experimental assay on the basis of radioactive Ca as tagged probe.
Topics: Calcium; Flagella; Cilia; Communication; Diffusion
PubMed: 37625514
DOI: 10.1016/j.biosystems.2023.105003 -
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 -
Communications Biology Sep 2023Biological tissues are highly organized structures where spatial-temporal gradients (e.g., nutrients, hypoxia, cytokines) modulate multiple physiological and...
Biological tissues are highly organized structures where spatial-temporal gradients (e.g., nutrients, hypoxia, cytokines) modulate multiple physiological and pathological processes including inflammation, tissue regeneration, embryogenesis, and cancer progression. Current in vitro technologies struggle to capture the complexity of these transient microenvironmental gradients, do not provide dynamic control over the gradient profile, are complex and poorly suited for high throughput applications. Therefore, we have designed Griddent, a user-friendly platform with the capability of generating controllable and reversible gradients in a 3D microenvironment. Our platform consists of an array of 32 microfluidic chambers connected to a 384 well-array through a diffusion port at the bottom of each reservoir well. The diffusion ports are optimized to ensure gradient stability and facilitate manual micropipette loading. This platform is compatible with molecular and functional spatial biology as well as optical and fluorescence microscopy. In this work, we have used this platform to study cancer progression.
Topics: Humans; Microfluidics; Cytokines; Diffusion; Exobiology; Neoplasms; Tumor Microenvironment
PubMed: 37689746
DOI: 10.1038/s42003-023-05282-3 -
Nature May 2024Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques are uniquely...
Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques are uniquely suited to resolving molecular diversity and new label-free approaches are reshaping the power of single-molecule measurements. A label-free single-molecule method capable of revealing details of molecular conformation in solution would allow a new microscopic perspective of unprecedented detail. Here we use the enhanced light-molecule interactions in high-finesse fibre-based Fabry-Pérot microcavities to detect individual biomolecules as small as 1.2 kDa, a ten-amino-acid peptide, with signal-to-noise ratios (SNRs) >100, even as the molecules are unlabelled and freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of subpopulations in mixed samples. Notably, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight and composition but different conformation can also be resolved. Detection is based on the creation of a new molecular velocity filter window and a dynamic thermal priming mechanism that make use of the interplay between optical and thermal dynamics and Pound-Drever-Hall (PDH) cavity locking to reveal molecular motion even while suppressing environmental noise. New in vitro ways of revealing molecular conformation, diversity and dynamics can find broad potential for applications in the life and chemical sciences.
Topics: Diffusion; Isomerism; Light; Peptides; Signal-To-Noise Ratio; Single Molecule Imaging; Solutions; Protein Conformation; Molecular Weight; Motion
PubMed: 38720082
DOI: 10.1038/s41586-024-07370-8 -
Journal of Chromatography. A Aug 2023We report on a new homogenization approach to solve, with drastically improved speed and accuracy, the general advection-diffusion equation in hierarchical porous media...
We report on a new homogenization approach to solve, with drastically improved speed and accuracy, the general advection-diffusion equation in hierarchical porous media with localized diffusion and adsorption/desorption processes, thus opening the way to a much deeper understanding of the band broadening process in chromatographic systems. The proposed robust and efficient moment-based approach allows us to compute the exact local and integral concentration moments and hence provides exact solutions for the effective velocity and dispersion coefficients of migrating solute particles. Innovative to the proposed method is also that it not only produces the exact effective transport parameters of the long-time asymptotic solution, but also their entire transient. The analysis of the transient behaviour can be used, for example, to properly identify the time and length scales needed to achieve the macro-transport conditions. If the hierarchical porous media can be represented as the periodic repetition of a unit lattice cell, the method only requires the solution of the time-dependent advection-diffusion equations for the zeroth order and first-order exact local moments, exclusively on the unit cell. This implies an enormous reduction of the computational efforts and a significant improvement of the accuracy of the results when compared to the direct numerical simulation (DNS) approaches which require flow domains that are long enough to achieve steady-state conditions, and hence often cover tens to hundreds of unit cells. The reliability of the proposed method is verified by comparing its predictions with DNS results, in one, two and three dimensions, in both transient and asymptotic conditions. The influence of top and bottom no-slip walls on the separation performance of chromatographic columns with micromachined porous and nonporous pillars is discussed in detail.
Topics: Porosity; Reproducibility of Results; Diffusion; Computer Simulation; Adsorption
PubMed: 37271084
DOI: 10.1016/j.chroma.2023.464099