Biological Rhythms Generated by a Single Activator-Repressor Loop with Inhomogeneity and Diffusion.

Common models of circadian rhythms are typically constructed as compartmental reactions of well-mixed biochemicals, incorporating a negative-feedback loop consisting of several intermediate reaction steps essentially required to produce oscillations. Spatial transport of each reactant is often represented as an extra compartmental reaction step. Contrary to this traditional understanding, in this Letter we demonstrate that a single activation-repression biochemical reaction pair is sufficient to generate sustained oscillations if the sites of both reactions are spatially separated and molecular transport is mediated by diffusion. Our proposed scenario represents the simplest configuration in terms of the participating chemical reactions and offers a conceptual basis for understanding biological oscillations and inspiring in vitro assays aimed at constructing minimal clocks.

Wearable Alcohol Monitoring Device for the Data-Driven Transcutaneous Alcohol Diffusion Model.

Wearable alcohol monitoring devices demand noninvasive, real-time measurement of blood alcohol content (BAC) reliably and continuously. A few commercial devices are available to determine BAC noninvasively by detecting transcutaneous diffused alcohol. However, they suffer from a lack of accuracy and reliability in the determination of BAC in real time due to the complex scenario of the human skin for transcutaneous alcohol diffusion and numerous factors (e.g., skin thickness, kinetics of alcohol, body weight, age, sex, metabolism rate, etc.). In this work, a transcutaneous alcohol diffusion model has been developed from real-time captured data from human wrists to better understand the kinetics of diffused alcohol from blood to different skin epidermis layers. Such a model will be a footprint to determine a base computational model in larger studies. Eight anonymous volunteers participated in this pilot study. A laboratory-built wearable blood alcohol content (BAC) monitoring device collected all the data to develop this diffusion model. The proton exchange membrane fuel cell (PEMFC) sensor was fabricated and integrated with an nRF51822 microcontroller, LMP91000 miniaturized potentiostat, 2.4 GHz transceiver supporting Bluetooth low energy (BLE), and all the necessary electronic components to build this wearable BAC monitoring device. The %BAC data in real time were collected using this device from these volunteers' wrists and stored in the end device (e.g., smartphone). From the captured data, we demonstrate how the volatile alcohol concentration on the skin varies over time by comparing the alcohol concentration in the initial stage (= 10 min) and later time (= 100 min). We also compare the experimental results with the outputs of three different input profiles: piecewise linear, exponential linear, and Hoerl, to optimize the developed diffusion model. Our results demonstrate that the exponential linear function best fits the experimental data compared to the piecewise linear and Hoerl functions. Moreover, we have studied the impact of skin epidermis thickness within ±20% and demonstrate that a 20% decrease in this thickness results in faster dynamics compared to thicker skin. The model clearly shows how the diffusion front changes within a skin epidermis layer with time. We further verified that 60 min was roughly the time to reach the maximum concentration, Cmax, in the stratum corneum from the transient analysis. Lastly, we found that a more significant time difference between BACmax and Cmax was due to greater alcohol consumption for a fixed absorption time.

Voltage mapping in subcellular nanodomains using electro-diffusion modeling.

Voltage distribution in sub-cellular micro-domains such as neuronal synapses, small protrusions, or dendritic spines regulates the opening and closing of ionic channels, energy production, and thus, cellular homeostasis and excitability. Yet how voltage changes at such a small scale in vivo remains challenging due to the experimental diffraction limit, large signal fluctuations, and the still limited resolution of fast voltage indicators. Here, we study the voltage distribution in nano-compartments using a computational approach based on the Poisson-Nernst-Planck equations for the electro-diffusion motion of ions, where inward and outward fluxes are generated between channels. We report a current-voltage (I-V) logarithmic relationship generalizing Nernst law that reveals how the local membrane curvature modulates the voltage. We further find that an influx current penetrating a cellular electrolyte can lead to perturbations from tens to hundreds of nanometers deep, depending on the local channel organization. Finally, we show that the neck resistance of dendritic spines can be completely shunted by the transporters located on the head boundary, facilitating ionic flow. To conclude, we propose that voltage is regulated at a subcellular level by channel organization, membrane curvature, and narrow passages.

Binary bilayer simulations for partitioning within membranes.

Membrane proteins (MPs) often show preference for one phase over the other, which is characterized by the partition coefficient, Kp. The physical mechanisms underlying Kp have been only inferred indirectly from experiments due to the unavailability of detailed structures and compositions of ordered phases. Molecular dynamics (MD) simulations can complement these details and thus, in principle, provide further insights into the partitioning of MPs between two phases. However, the application of MD has remained difficult due to long time scales required for equilibration and large system size for the phase stability, which have not been fully resolved even in free energy simulations. This chapter describes the recently developed binary bilayer simulation method, where the membrane is composed of two laterally attached membrane patches. The binary bilayer system (BBS) is designed to preserve the lateral packing of both phases in a significantly smaller size compared to that required for macroscopic phase separation. These characteristics are advantageous in partitioning simulations, as the length scale for diffusion across the system can be significantly smaller. Hence the BBS can be efficiently employed in both conventional MD and free energy simulations, though sampling in ordered phases remains difficult due to slow diffusion. Development of efficient lipid swapping methods and its combination with the BBS would be a useful approach for partitioning in coexisting phases.

Dynamic framework for large-scale modeling of membranes and peripheral proteins.

In this chapter, we present a novel computational framework to study the dynamic behavior of extensive membrane systems, potentially in interaction with peripheral proteins, as an alternative to conventional simulation methods. The framework effectively describes the complex dynamics in protein-membrane systems in a mesoscopic particle-based setup. Furthermore, leveraging the hydrodynamic coupling between the membrane and its surrounding solvent, the coarse-grained model grounds its dynamics in macroscopic kinetic properties such as viscosity and diffusion coefficients, marrying the advantages of continuum- and particle-based approaches. We introduce the theoretical background and the parameter-space optimization method in a step-by-step fashion, present the hydrodynamic coupling method in detail, and demonstrate the application of the model at each stage through illuminating examples. We believe this modeling framework to hold great potential for simulating membrane and protein systems at biological spatiotemporal scales, and offer substantial flexibility for further development and parametrization.

Role of diffusion and reaction of the constituents in spreading of histone modification marks.

Cells switch genes ON or OFF by altering the state of chromatin via histone modifications at specific regulatory locations along the chromatin polymer. These gene regulation processes are carried out by a network of reactions in which the histone marks spread to neighboring regions with the help of enzymes. In the literature, this spreading has been studied as a purely kinetic, non-diffusive process considering the interactions between neighboring nucleosomes. In this work, we go beyond this framework and study the spreading of modifications using a reaction-diffusion (RD) model accounting for the diffusion of the constituents. We quantitatively segregate the modification profiles generated from kinetic and RD models. The diffusion and degradation of enzymes set a natural length scale for limiting the domain size of modification spreading, and the resulting enzyme limitation is inherent in our model. We also demonstrate the emergence of confined modification domains without the explicit requirement of a nucleation site. We explore polymer compaction effects on spreading and show that single-cell domains may differ from averaged profiles. We find that the modification profiles from our model are comparable with existing H3K9me3 data of S. pombe.

Rotational and translational diffusion of biomolecules in complex liquids and HeLa cells.

Diffusive motion accompanies many physical and biological processes. The Stokes-Sutherland-Einstein relation for the translational diffusion coefficient, DT, agrees with experiments done in simple fluids but fails for complex fluids. Moreover, the interdependence between DT and rotational diffusion coefficient, DR, also deviates in complex fluids from the classical relation of DT/DR = 4r2/3 known in simple fluids. Makuch et al. Soft Matter, 2020, 16, 114-124 presented a generalization of the classical translational and rotational diffusion theory for complex fluids. In this work, we empirically verify this model based on simultaneous translational and rotational diffusion measurements. We use fluorescently stained cowpea chlorotic mottle virus (CCMV) particles as monodisperse probes and aqueous polyethylene glycol (PEG) solutions as a model complex fluid. The theory and experimental data obtained from fluorescence correlation spectroscopy (FCS) measurements agreed. Finally, we used the same model and analyzed the diffusion of Yo-Pro-1 stained large ribosomal subunits (LSU) in the cytoplasm and nucleus of living HeLa cells.

The Physics of Antimicrobial Activity of Ionic Liquids.

The bactericidal potency of ionic liquids (ILs) is well-established, yet their precise mechanism of action remains elusive. Here, we show evidence that the bactericidal action of ILs primarily involves the permeabilization of the bacterial cell membrane. Our findings reveal that ILs exert their effects by directly interacting with the lipid bilayer and enhancing the membrane dynamics. Lateral lipid diffusion is accelerated, which in turn augments membrane permeability, ultimately leading to bacterial death. Furthermore, our results establish a significant connection: an increase in the alkyl chain length of ILs correlates with a notable enhancement in both lipid lateral diffusion and antimicrobial potency. This underscores a compelling correlation between membrane dynamics and antimicrobial effectiveness, providing valuable insights for the rational design and optimization of IL-based antimicrobial agents in healthcare applications.

Optimizing the feasibility of polyvinyl alcohol-potassium iodine gel for medical dosimeter.

This work aims to improve the post stabilty of reusable potassium iodide hydrogel dosimter. A reusable and low-cost radiochromic dosimeter containing a gel matrix of polyvinyl alcohol, potassium iodide dye, froctose as reducing agent and glutaraldehyde as cross-linking agent was developed for dose calibration in radiotherapy. The gel samples were exposed to different absorbed doses using a medical linear acceleration. UV-vis Spectrophotometry was utilized to investigate the changes in optical-properties of irradiated gels with regard to peak wavelength of 353 nm. The stability of the gel (one of the most limitation of using this dosimeter) was improved significantly by the addition of certain concentrations of dimethyl sulfoxide. The two-dimensional optical imaging system of charge-coupled-device (CCD) camera with a uniform RGB light-emitting-diode (LED) array source was used for diffusion coefficient purpose using two dimensional gel template. The value of diffusion coefficient reported is significant and highly reduced compared with other dosimeters reported in the literatures. Moreover, heating the improved gels to certain temperatures results in resetting their optical properties, which makes it possible to reuse for multiple times.

Molecular localization and exchange kinetics in pharmaceutical liposome and mRNA lipoplex nanoparticle products determined by small angle X-ray scattering and pulsed field gradient NMR diffusion measurements.

We have used pulsed field gradient (PFG)-NMR diffusion experiments, also known as DOSY, in combination with small angle X-ray scattering measurements to investigate structure and molecular exchange dynamics between pharmaceutical lipid nanoparticles and the bulk phase. Using liposomes and lipoplexes formed after complexation of the liposomes with messenger mRNA as test systems, information on dynamics of encapsulated water molecules, lipids and excipients was obtained. The encapsulated fraction, having a diffusivity similar to that of the liposomes, could be clearly identified and quantified by the NMR diffusion measurements. The unilamellar liposome membranes allowed a fast exchange of water molecules, while sucrose, used as an osmolyte and model solute, showed very slow exchange. Upon interactions with mRNA a topological transition from a vesicular to a lamellar organization took place, where the mRNA was inserted in repeating lipid bilayer stacks. In the lipoplexes, a small fraction of tightly bound water molecules was present, with a diffusivity that was influenced by the additional presence of sucrose. This extended information on dynamic coherencies inside pharmaceutical nanoparticle products, provided by the combined application of SAXS and PFG-NMR diffusion measurements, can be valuable for evaluation of quality and comparability of nanoscaled pharmaceuticals.

Diffusive delivery of plasmid DNA using zwitterionic carboxyalkyl poly(1-vinylimidazole) into skeletal muscle in vivo.

Zwitterionic carboxyalkyl poly(1-vinylimidazole) (CA-PVIm) polymers with imidazolium cations and carboxylate anions have been synthesized as a carrier for the in vivo delivery of plasmid DNA (pDNA) to skeletal muscle. From differential scanning calorimetry measurements, resulting CA-PVIm had intermediate water in hydration water as a biocompatible polymer. Notably, when the pDNA and resulting CA-PVIm were mixed, slight retarded bands of the pDNA were observed in agarose gel electrophoresis, suggesting the polyion complex (PIC) formation between the pDNA and CA-PVIm despite zwitterionic polymers. Resulting PICs maintained the higher-order structure of the pDNA. Using resulting pDNA PICs, the highest pDNA expression by intramuscular injection was achieved in the PIC with 7 mol% carboxymethylated PVIm, that is, CA1(7)-PVIm, observed in a widespread area by in vivo imaging system. These results suggest that the CA1(7)-PVIm/pDNA PIC is effective for the diffusive delivery of the pDNA into skeletal muscle for the treatment of serious muscle diseases.

Quantum Dot-Based Three-Dimensional Single-Particle Tracking Characterizes the Evolution of Spatiotemporal Heterogeneity in Necrotic Cells.

Cell death is a fundamental biological process with different modes including apoptosis and necrosis. In contrast to programmed apoptosis, necrosis was previously considered disordered and passive, but it is now being realized to be under regulation by certain biological pathways. However, the intracellular dynamics that coordinates with cellular structure changes during necrosis remains unknown, limiting our understanding of the principles of necrosis. Here, we characterized the spatiotemporal intracellular diffusion dynamics in cells undergoing necrosis, using three-dimensional single-particle tracking of quantum dots. We found temporally increased diffusion rates in necrotic cells and spatially enhanced diffusion heterogeneity in the cell periphery, which could be attributed to the reduced molecular crowding resulting from cell swelling and peripheral blebbing, respectively. Moreover, the three-dimensional intracellular diffusion transits from strong anisotropy to nearly isotropy, suggesting a remodeling of the cytoarchitecture that relieves the axial constraint on intracellular diffusion during necrosis. Our results reveal the remarkable alterations of intracellular diffusion dynamics and biophysical properties in necrosis, providing insight into the well-organized nonequilibrium necrotic cell death from a biophysical perspective.

Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction.

Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. But PET suffers from a low signal-to-noise ratio, while MRI are time-consuming. To address time-consuming, an effective strategy involves reducing k-space data collection, albeit at the cost of lowering image quality. This study aims to leverage the inherent complementarity within PET-MRI data to enhance the image quality of PET-MRI.Approach. A novel PET-MRI joint reconstruction model, termed MC-Diffusion, is proposed in the Bayesian framework. The joint reconstruction problem is transformed into a joint regularization problem, where data fidelity terms of PET and MRI are expressed independently. The regular term, the derivative of the logarithm of the joint probability distribution of PET and MRI, employs a joint score-based diffusion model for learning. The diffusion model involves the forward diffusion process and the reverse diffusion process. The forward diffusion process adds noise to transform a complex joint data distribution into a known joint prior distribution for PET and MRI simultaneously, resembling a denoiser. The reverse diffusion process removes noise using a denoiser to revert the joint prior distribution to the original joint data distribution, effectively utilizing joint probability distribution to describe the correlations of PET and MRI for improved quality of joint reconstruction.Main results. Qualitative and quantitative improvements are observed with the MC-Diffusion model. Comparative analysis against LPLS and Joint ISAT-net on the ADNI dataset demonstrates superior performance by exploiting complementary information between PET and MRI. The MC-Diffusion model effectively enhances the quality of PET and MRI images.Significance. This study employs the MC-Diffusion model to enhance the quality of PET-MRI images by integrating the fundamental principles of PET and MRI modalities and leveraging their inherent complementarity. Furthermore, utilizing the diffusion model to learn the joint probability distribution of PET and MRI, thereby elucidating their latent correlation, facilitates a more profound comprehension of the priors obtained through deep learning, contrasting with black-box prior or artificially constructed structural similarities.

Biological invasion with a porous medium type diffusion in a heterogeneous space.

The knowledge of traveling wave solutions is the main tool in the study of wave propagation. However, in a spatially heterogeneous environment, traveling wave solutions do not exist, and a different approach is needed. In this paper, we study the generation and the propagation of hyperbolic scale singular limits of a KPP-type reaction-diffusion equation when the carrying capacity is spatially heterogeneous and the diffusion is of a porous medium equation type. We show that the interface propagation speed varies according to the carrying capacity.

Glycerol-slaved 1H-1H NMR cross-relaxation in quasi-native lysozyme.

1H-1H nuclear cross-relaxation experiments have been carried out with lysozyme in variable glycerol viscosity to study intramolecular motion, self-diffusion, and isotropic rigid-body rotational tumbling at 298 K, pH 3.8. Dynamics of intramolecular 1H-1H cross-relaxation rates, the increase in internuclear spatial distances, and lateral and rotational diffusion coefficients all show fractional viscosity dependence with a power law exponent κ in the 0.17-0.83 range. The diffusion coefficient of glycerol Ds with the bulk viscosity itself is non-Stokesian, having a fractional viscosity dependence on the medium viscosity (Ds âˆ¼ Î·-κ, κ ≈ 0.71). The concurrence and close similarity of the fractional viscosity dependence of glycerol diffusion on the one hand, and diffusion and intramolecular cross-relaxation rates of the protein on the other lead to infer that relaxation of glycerol slaves protein relaxations. Glycerol-transformed native lysozyme to a quasi-native state does not affect the conclusion that both global and internal fluctuations are slaved to glycerol relaxation.

DiffuseRT: predicting likely anatomical deformations of patients undergoing radiotherapy.

Objective. Predicting potential deformations of patients can improve radiotherapy treatment planning. Here, we introduce new deep-learning models that predict likely anatomical changes during radiotherapy for head and neck cancer patients.Approach. Denoising diffusion probabilistic models (DDPMs) were developed to generate fraction-specific anatomical changes based on a reference cone-beam CT (CBCT), the fraction number and the dose distribution delivered. Three distinct DDPMs were developed: (1) theimage modelwas trained to directly generate likely future CBCTs, (2) the deformable vector field (DVF) model was trained to generate DVFs that deform a reference CBCT and (3) thehybrid modelwas trained similarly to the DVF model, but without relying on an external deformable registration algorithm. The models were trained on 9 patients with longitudinal CBCT images (224 CBCTs) and evaluated on 5 patients (152 CBCTs).Results. The generated images mainly exhibited random positioning shifts and small anatomical changes for early fractions. For later fractions, all models predicted weight losses in accordance with the training data. The distributions of volume and position changes of the body, esophagus, and parotids generated with the image and hybrid models were more similar to the ground truth distribution than the DVF model, evident from the lower Wasserstein distance achieved with the image (0.33) and hybrid model (0.30) compared to the DVF model (0.36). Generating several images for the same fraction did not yield the expected variability since the ground truth anatomical changes were only in 76% of the fractions within the 95% bounds predicted with the best model. Using the generated images for robust optimization of simplified proton therapy plans improved the worst-case clinical target volume V95 with 7% compared to optimizing with 3 mm set-up robustness while maintaining a similar integral dose.Significance. The newly developed DDPMs generate distributions similar to the real anatomical changes and have the potential to be used for robust anatomical optimization.

Diffusion in biological media: a comprehensive numerical-analytical study via surface analysis and diffusivities calculation.

The study of diffusion in biological materials is crucial for fields like food science, engineering, and pharmaceuticals. Research that combines numerical and analytical methods is needed to better understand diffusive phenomena across various dimensions and under variable boundary conditions within food matrices. This study aims to bridge this gap by examining the diffusion of substances through biological materials analytically and numerically, calculating diffusivity and conducting surface analysis. The research proposes a process for sweetening Bing-type cherries (Prunus avium) using sucrose/xylitol solutions and a staining technique utilising erythrosine and red gardenia at varying concentrations (119, 238 and 357 ppm) and temperatures (40, 50 and 60 °C). Given the fruit's epidermis resistance, the effective diffusivities of skin were inferior to those in flesh. Temperature and concentration synergise in enhancing diffusion coefficients and dye penetration within the food matrix (357 ppm and 60 °C). Red gardenia displayed significant temperature-dependent variation (p = 0.001), whereas erythrosine dye remained stable by temperature changes (p > 0.05). Gardenia's effective diffusivities in cherry flesh and skin, at 357 ppm and 60 °C, 3.89E-08 and 6.61E-09 m2/s, respectively, significantly differed from those obtained at lower temperatures and concentrations. The results highlight the temperature-concentration impacts on mass transfer calculations for food colouring processes and preservation methodologies.

Dynamic evaluation of corneal cross-linking and osmotic diffusion effects using optical coherence elastography.

Dynamic deformation events induced by osmosis or photochemical stiffening substantially influence geometrical and mechanical assessments in post-mortem corneas, therefore need to be carefully monitored in experimental settings. In this study, we employed optical coherence elastography (OCE) to quantify dynamic deformation processes at high resolution in freshly enucleated porcine corneas. Osmotic effects were studied by immerging n = 9 eyes in preservation media of three different tonicities. Dynamic processes underlying corneal cross-linking (CXL) were studied by subjecting n = 6 eyes to standard Dresden treatment, while three control groups were used. The entire procedures were performed under an OCE setup during up to 80 min, acquiring a volumetric scan every 20 s. Changes in OCE-derived axial deformations were incrementally calculated between consecutive scans. Preservation conditions had a strong influence on the observed strain patterns, which were consistent with the tonicity of the medium (swelling in hypotonic, deswelling in hypertonic environment). In the CXL group, we observed deswelling of the anterior stroma 10 min after starting the UV irradiation, which was not observed in any control group (p = 0.007). The presented results proved OCE to be a valuable technique to quantify subtle dynamic biomechanical alterations in the cornea resulting from CXL and preservation solutions.

Head and neck tumor segmentation from [18F]F-FDG PET/CT images based on 3D diffusion model.

Objective.Head and neck (H&N) cancers are among the most prevalent types of cancer worldwide, and [18F]F-FDG PET/CT is widely used for H&N cancer management. Recently, the diffusion model has demonstrated remarkable performance in various image-generation tasks. In this work, we proposed a 3D diffusion model to accurately perform H&N tumor segmentation from 3D PET and CT volumes.Approach.The 3D diffusion model was developed considering the 3D nature of PET and CT images acquired. During the reverse process, the model utilized a 3D UNet structure and took the concatenation of 3D PET, CT, and Gaussian noise volumes as the network input to generate the tumor mask. Experiments based on the HECKTOR challenge dataset were conducted to evaluate the effectiveness of the proposed diffusion model. Several state-of-the-art techniques based on U-Net and Transformer structures were adopted as the reference methods. Benefits of employing both PET and CT as the network input, as well as further extending the diffusion model from 2D to 3D, were investigated based on various quantitative metrics and qualitative results.Main results.Results showed that the proposed 3D diffusion model could generate more accurate segmentation results compared with other methods (mean Dice of 0.739 compared to less than 0.726 for other methods). Compared to the diffusion model in 2D form, the proposed 3D model yielded superior results (mean Dice of 0.739 compared to 0.669). Our experiments also highlighted the advantage of utilizing dual-modality PET and CT data over only single-modality data for H&N tumor segmentation (with mean Dice less than 0.570).Significance.This work demonstrated the effectiveness of the proposed 3D diffusion model in generating more accurate H&N tumor segmentation masks compared to the other reference methods.

Similar experimental study on diffusion and distribution of diesel exhaust in confined space of a coal mine.

In the confined space of the underground coal mine, which is dominated by transportation lanes, explosion-proof diesel-powered trackless rubber-wheeled vehicles are becoming the main transportation equipment, and the exhaust gas produced by them is hazardous to the health of workers and pollutes the underground environment. In this experiment, a similar test platform is built to study the effects of wind speed, vehicle speed, and different wind directions on the diffusion characteristics of exhaust gas. In this paper, CO and SO2 are mainly studied. The results show that the diffusion of CO and SO2 gas is similar and the maximum SO2 concentration only accounts for 11.4% of the CO concentration. Exhaust gas is better diluted by increasing the wind speed and vehicle speed, respectively. Downwind is affected by the reverse wind flow and diffuses to the driver's position, which is easy to cause occupational diseases. When the wind is a headwind, the exhaust gases spread upwards and make a circumvention movement, gathering at the top. When the wind speed and vehicle speed are both 0.6 m/s, the CO concentration corresponds to the change trend of the Lorentz function when the wind is downwind and the CO concentration corresponds to the change trend of the BiDoseResp function when the wind is headwind. The study of exhaust gas diffusion characteristics is of great significance for the subsequent purification of the air in the restricted mine space and the protection of the workers' occupational health.