Asymptotic analysis of particle cluster formation in the presence of anchoring sites.

The aggregation or clustering of proteins and other macromolecules plays an important role in the formation of large-scale molecular assemblies within cell membranes. Examples of such assemblies include lipid rafts, and postsynaptic domains (PSDs) at excitatory and inhibitory synapses in neurons. PSDs are rich in scaffolding proteins that can transiently trap transmembrane neurotransmitter receptors, thus localizing them at specific spatial positions. Hence, PSDs play a key role in determining the strength of synaptic connections and their regulation during learning and memory. Recently, a two-dimensional (2D) diffusion-mediated aggregation model of PSD formation has been developed in which the spatial locations of the clusters are determined by a set of fixed anchoring sites. The system is kept out of equilibrium by the recycling of particles between the cell membrane and interior. This results in a stationary distribution consisting of multiple clusters, whose average size can be determined using an effective mean-field description of the particle concentration around each anchored cluster. In this paper, we derive corrections to the mean-field approximation by applying the theory of diffusion in singularly perturbed domains. The latter is a powerful analytical method for solving two-dimensional (2D) and three-dimensional (3D) diffusion problems in domains where small holes or perforations have been removed from the interior. Applications range from modeling intracellular diffusion, where interior holes could represent subcellular structures such as organelles or biological condensates, to tracking the spread of chemical pollutants or heat from localized sources. In this paper, we take the bounded domain to be the cell membrane and the holes to represent anchored clusters. The analysis proceeds by partitioning the membrane into a set of inner regions around each cluster, and an outer region where mean-field interactions occur. Asymptotically matching the inner and outer stationary solutions generates an asymptotic expansion of the particle concentration, which includes higher-order corrections to mean-field theory that depend on the positions of the clusters and the boundary of the domain. Motivated by a recent study of light-activated protein oligomerization in cells, we also develop the analogous theory for cluster formation in a three-dimensional (3D) domain. The details of the asymptotic analysis differ from the 2D case due to the contrasting singularity structure of 2D and 3D Green's functions.

The Influence of the Variable Wettability Characteristics of Layers on the Transport of Nanoparticles in the Context of Drug Delivery in Skin Structures.

The rapid development of nanotechnology has offered the possibility of creating nanosystems that can be used as drug carriers. The use of such carriers offers real opportunities for the development of non-invasive drug delivery through skin structures. However, in addition to the ability to create suitable nanocarriers, it is also necessary to know how they move through dermal layers. The human skin consists of layers with different wettability characteristics, which greatly complicates how introduced substances move through it. In this work, an experimental study of the diffusion process of nanoparticles through partitions with different wettability properties was carried out. Conventional diffusion tests using Franz chambers were used for this purpose. We quantified how the wettability of the barrier, the number of layers, and their mutual configuration affect the transport of nanoparticles. Based on the results, an analysis of the phenomena taking place, depending on the wettability of the partition, was carried out. A model relationship was also proposed to determine the effective diffusion coefficient, taking into account the influence of the wettability and porosity of the barrier.

Hydrodynamic Radii of Intrinsically Disordered Proteins: Fast Prediction by Minimum Dissipation Approximation and Experimental Validation.

The diffusion coefficients of globular and fully unfolded proteins can be predicted with high accuracy solely from their mass or chain length. However, this approach fails for intrinsically disordered proteins (IDPs) containing structural domains. We propose a rapid predictive methodology for estimating the diffusion coefficients of IDPs. The methodology uses accelerated conformational sampling based on self-avoiding random walks and includes hydrodynamic interactions between coarse-grained protein subunits, modeled using the generalized Rotne-Prager-Yamakawa approximation. To estimate the hydrodynamic radius, we rely on the minimum dissipation approximation recently introduced by Cichocki et al. Using a large set of experimentally measured hydrodynamic radii of IDPs over a wide range of chain lengths and domain contributions, we demonstrate that our predictions are more accurate than the Kirkwood approximation and phenomenological approaches. Our technique may prove to be valuable in predicting the hydrodynamic properties of both fully unstructured and multidomain disordered proteins.

Investigations on the Diffusion Behavior of Smoke-Associated Aroma Compounds into the Sausage Matrix as Affected by Casing, Caliber, and Packaging.

The aim of the study was to investigate how smoke-associated flavoring substances behave during storage in Frankfurter-type sausages. The diffusion behavior of seven selected aroma substances in the sausage matrix and the influence of the packaging and the casing were examined over a storage period of 28 days. The sausages were cut into uniformly thick layers at defined time intervals and examined by headspace-solid phase microextraction-gas chromatography-mass spectrometry. In general, three different groups could be distinguished: (1) even distribution over the entire product on the first day after smoking; (2) clear concentration gradient from outside to inside on the first day of storage, which leveled out until day 28 of storage; and (3) a clear concentration gradient that remained present throughout the storage period. In addition, only small effects were found in the distribution of flavorings between two types of packaging, selected casing, or different calibers.

Organic-solvent ditch overlap in reversed-phase liquid chromatography: A molecular dynamics simulation study in cylindrical 6-12 nm-diameter pores.

Mass transport through the mesopore space of a reversed-phase liquid chromatography (RPLC) column depends on the properties of the chromatographic interface, particularly on the extent of the organic-solvent ditch that favors the analyte surface diffusivity. Through molecular dynamics simulations in cylindrical RPLC mesopore models with pore diameters between 6 and 12 nm we systematically trace the evolution of organic-solvent ditch overlap due to spatial confinement in the mesopore space of RPLC columns for small-molecule separations. Each pore model of a silica-based, endcapped, C18-stationary phase is equilibrated with two mobile phases of comparable elution strength, namely 70/30 (v/v) water/acetonitrile and 60/40 (v/v) water/methanol, to consider the influence of the mobile-phase composition on the onset of organic-solvent ditch overlap. The simulations show that, as the pore diameter decreases from 9 to 6 nm, the bonded-phase density extends and compacts towards the pore center, which leads to increased accumulation of organic-solvent excess and thus enhanced organic-solvent diffusivity in the ditch. Because the acetonitrile ditch is more pronounced than the methanol ditch, acetonitrile ditch overlap sets in at less severe spatial confinement than methanol ditch overlap. The pore-averaged methanol and acetonitrile diffusivities are considerably raised by ditch overlap in the 6 nm-diameter pore, but also benefit from the ditch (without overlap) in the 7 to 12 nm-diameter pores, whereby local and pore-averaged effects are generally larger for acetonitrile than methanol.

Role of tumbling in bacterial scattering at convex obstacles.

Active propulsion, as performed by bacteria and Janus particles, in combination with hydrodynamic interaction results in the accumulation of bacteria at a flat wall. However, in microfluidic devices with cylindrical pillars of sufficiently small radius, self-propelled particles can slide along and scatter off the surface of a pillar, without becoming trapped over long times. This nonequilibrium scattering process has been predicted to result in large diffusivities, even at high obstacle density, unlike particles that undergo classical specular reflection. Here, we test this prediction by experimentally studying the nonequilibrium scattering of pusherlike swimmers in microfluidic obstacle lattices. To explore the role of tumbles in the scattering process, we microscopically tracked wild-type (run and tumble) and smooth-swimming (run only) mutants of the bacterium Escherichia coli scattering off microfluidic pillars. We quantified key scattering parameters and related them to previously proposed models that included a prediction for the diffusivity, discussing their relevance. Finally, we discuss potential interpretations of the role of tumbles in the scattering process and connect our work to the broader study of swimmers in porous media.

Vesicle and reaction-diffusion hybrid modeling with STEPS.

Vesicles carry out many essential functions within cells through the processes of endocytosis, exocytosis, and passive and active transport. This includes transporting and delivering molecules between different parts of the cell, and storing and releasing neurotransmitters in neurons. To date, computational simulation of these key biological players has been rather limited and has not advanced at the same pace as other aspects of cell modeling, restricting the realism of computational models. We describe a general vesicle modeling tool that has been designed for wide application to a variety of cell models, implemented within our software STochastic Engine for Pathway Simulation (STEPS), a stochastic reaction-diffusion simulator that supports realistic reconstructions of cell tissue in tetrahedral meshes. The implementation is validated in an extensive test suite, parallel performance is demonstrated in a realistic synaptic bouton model, and example models are visualized in a Blender extension module.

In situ pulmonary mucus hydration assay using rotational and translational diffusion of gold nanorods with polarization-sensitive optical coherence tomography.

Significance: Assessing the nanostructure of polymer solutions and biofluids is broadly useful for understanding drug delivery and disease progression and for monitoring therapy. Aim: Our objective is to quantify bronchial mucus solids concentration (wt. %) during hypertonic saline (HTS) treatment in vitro via nanostructurally constrained diffusion of gold nanorods (GNRs) monitored by polarization-sensitive optical coherence tomography (PS-OCT). Approach: Using PS-OCT, we quantified GNR translational (DT) and rotational (DR) diffusion coefficients within polyethylene oxide solutions (0 to 3 wt. %) and human bronchial epithelial cell (hBEC) mucus (0 to 6.4 wt. %). Interpolation of DT and DR data is used to develop an assay to quantify mucus concentration. The assay is demonstrated on the mucus layer of an air-liquid interface hBEC culture during HTS treatment. Results: In polymer solutions and mucus, DT and DR monotonically decrease with increasing concentration. DR is more sensitive than DT to changes above 1.5 wt. % of mucus and exhibits less intrasample variability. Mucus on HTS-treated hBEC cultures exhibits dynamic mixing from cilia. A region of hard-packed mucus is revealed by DR measurements. Conclusions: The extended dynamic range afforded by simultaneous measurement of DT and DR of GNRs using PS-OCT enables resolving concentration of the bronchial mucus layer over a range from healthy to disease in depth and time during HTS treatment in vitro.

Diffusion in Porous Rock Is Anomalous.

Molecular diffusion of chemical species in subsurface environments─rock formations, soil sediments, marine, river, and lake sediments─plays a critical role in a variety of dynamic processes, many of which affect water chemistry. We investigate and demonstrate the occurrence of anomalous (non-Fickian) diffusion behavior, distinct from classically assumed Fickian diffusion. We measured molecular diffusion through a series of five chalk and dolomite rock samples over a period of about two months. We demonstrate that in all cases, diffusion behavior is significantly different than Fickian. We then analyze the results using a continuous time random walk framework that can describe anomalous diffusion in heterogeneous porous materials such as rock. This methodology shows extreme long-time tailing of tracer advance as compared to conventional Fickian diffusion processes. The finding that distinct anomalous diffusion occurs ubiquitously implies that diffusion-driven processes in subsurface zones should be analyzed using tools that account for non-Fickian diffusion.

Quantification of diffusion coefficients of commonly used high-intensity sweeteners through mucin.

Low- and no-calorie sweeteners reduce the amount of carbohydrates in foods and beverages. However, concerns about taste perception surrounding the role of non-nutritive sweeteners in the oral cavity remain unanswered. One of the parameters that influences taste perception is the diffusion coefficient of the sweetener molecules inside the mucin layer lining the mouth. This study investigated the impact of diffusion coefficients of common high-intensity sweeteners on taste perception focusing on the sweeteners' diffusion through mucin. Transwell Permeable Support well plates were used to measure diffusion coefficients of samples that were collected at specific intervals to estimate the coefficients based on concentration measurements. The diffusion coefficients of acesulfame-K, aspartame, rebaudioside M, sucralose, and sucrose with and without NaCl were compared. We found that different sweeteners show different diffusion behavior through mucin and that the presence of salt enhances the diffusion. These findings contribute insights into the diffusion of high-intensity sweeteners, offer a way to evaluate diffusion coefficients in real-time, and inform the development of products with improved taste profiles.

Correlative single molecule lattice light sheet imaging reveals the dynamic relationship between nucleosomes and the local chromatin environment.

In the nucleus, biological processes are driven by proteins that diffuse through and bind to a meshwork of nucleic acid polymers. To better understand this interplay, we present an imaging platform to simultaneously visualize single protein dynamics together with the local chromatin environment in live cells. Together with super-resolution imaging, new fluorescent probes, and biophysical modeling, we demonstrate that nucleosomes display differential diffusion and packing arrangements as chromatin density increases whereas the viscoelastic properties and accessibility of the interchromatin space remain constant. Perturbing nuclear functions impacts nucleosome diffusive properties in a manner that is dependent both on local chromatin density and on relative location within the nucleus. Our results support a model wherein transcription locally stabilizes nucleosomes while simultaneously allowing for the free exchange of nuclear proteins. Additionally, they reveal that nuclear heterogeneity arises from both active and passive processes and highlight the need to account for different organizational principles when modeling different chromatin environments.

Travelling waves for a fast reaction limit of a discrete coagulation-fragmentation model with diffusion and proliferation.

We study traveling wave solutions for a reaction-diffusion model, introduced in the article Calvez et al. (Regime switching on the propagation speed of travelling waves of some size-structured myxobacteriapopulation models, 2023), describing the spread of the social bacterium Myxococcus xanthus. This model describes the spatial dynamics of two different cluster sizes: isolated bacteria and paired bacteria. Two isolated bacteria can coagulate to form a cluster of two bacteria and conversely, a pair of bacteria can fragment into two isolated bacteria. Coagulation and fragmentation are assumed to occur at a certain rate denoted by k. In this article we study theoretically the limit of fast coagulation fragmentation corresponding mathematically to the limit when the value of the parameter k tends to + ∞ . For this regime, we demonstrate the existence and uniqueness of a transition between pulled and pushed fronts for a certain critical ratio θ ⋆ between the diffusion coefficient of isolated bacteria and the diffusion coefficient of paired bacteria. When the ratio is below θ ⋆ , the critical front speed is constant and corresponds to the linear speed. Conversely, when the ratio is above the critical threshold, the critical spreading speed becomes strictly greater than the linear speed.

Dose and DNA damage modelling of diffusing alpha-emitters radiation therapy using Geant4.

PURPOSE: Diffusing alpha-emitters radiation therapy (DaRT) is a brachytherapy technique using α-particles to treat solid tumours. The high linear energy transfer (LET) and short range of α-particles make them good candidates for the targeted treatment of cancer. Treatment planning of DaRT requires a good understanding of the dose from α-particles and the other particles released in the 224Ra decay chain. METHODS: The Geant4 Monte Carlo toolkit has been used to simulate a DaRT seed to better understand the dose contribution from all particles and simulate the DNA damage due to this treatment. RESULTS: Close to the seed α-particles deliver the majority of dose, however at radial distances greater than 4 mm, the contribution of ß-particles is greater. The RBE has been estimated as a function of number of double strand breaks (DSBs) and complex DSBs. A maximum seed spacing of 5.5 mm and 6.5 mm was found to deliver at least 20 Gy RBE weighted dose between the seeds for RBEDSB and RBEcDSB respectively. CONCLUSIONS: The DNA damage changes with radial distance from the seed and has been found to become less complex with distance, which is potentially easier for the cell to repair. Close to the seed α-particles contribute the majority of dose, however the contribution from other particles cannot be neglected and may influence the choice of seed spacing.

Two-Photon Microscopy for the Study of Tendons.

Two-photon microscopy has emerged as a potent tool for evaluating deep tissue cells and characterizing the alignment of the extracellular matrix (ECM) in various biological systems. This technique relies on nonlinear light-matter interactions to detect two distinct signals: the second harmonic generated (SHG) diffusion signal, which facilitates the visualization of collagen fibers and their orientation, and the near-infrared excitation signal for imaging ultraviolet excited autofluorescence. SHG imaging proves especially effective in visualizing collagen fibers due to the non-centrosymmetric crystalline structure of fibrillar collagen I. Given that tendons are matrix-rich tissues with a limited number of cells, their high collagen content makes them ideal candidates for analysis using two-photon microscopy. Consequently, two-photon microscopy offers a valuable means to analyze and characterize collagen abnormalities in tendons. Its application extends to studying tendon development, injuries, healing, and aging, enabling the comprehensive characterization of tendon cells and their interactions with the ECM under various conditions using two-photon microscopy tools. This protocol outlines the use of two-photon microscopy in tendon biology and presents an adapted methodology to achieve effective imaging and characterization of tendon cells during development and after injury. The method allows the utilization of thin microscopic sections to create a comprehensive image of the ECM within tendons and the cells that interact with this matrix. Most notably, the article showcases a technique to generate 3D images using two-photon microscopy in animal models.

Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model.

Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows "one size fits all" approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100-1000 nmol), receptor density (10-500 nmol•l-1), and recycling rate of receptors (10-4 to 10-1 min-1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min-1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.

MAM-E: Mammographic Synthetic Image Generation with Diffusion Models.

Generative models are used as an alternative data augmentation technique to alleviate the data scarcity problem faced in the medical imaging field. Diffusion models have gathered special attention due to their innovative generation approach, the high quality of the generated images, and their relatively less complex training process compared with Generative Adversarial Networks. Still, the implementation of such models in the medical domain remains at an early stage. In this work, we propose exploring the use of diffusion models for the generation of high-quality, full-field digital mammograms using state-of-the-art conditional diffusion pipelines. Additionally, we propose using stable diffusion models for the inpainting of synthetic mass-like lesions on healthy mammograms. We introduce MAM-E, a pipeline of generative models for high-quality mammography synthesis controlled by a text prompt and capable of generating synthetic mass-like lesions on specific regions of the breast. Finally, we provide quantitative and qualitative assessment of the generated images and easy-to-use graphical user interfaces for mammography synthesis.

A Study of the Drift Phenomena of Gate-Functionalized Biosensors and Dual-Gate-Functionalized Biosensors in Human Serum.

In this paper, we study the drift behavior of organic electrochemical transistor (OECT) biosensors in a phosphate-buffered saline (PBS) buffer solution and human serum. Theoretical and experimental methods are illustrated in this paper to understand the origin of the drift phenomenon and the mechanism of ion diffusion in the sensing layer. The drift phenomenon is explained using a first-order kinetic model of ion adsorption into the gate material and shows very good agreement with experimental data on drift in OECTs. We show that the temporal current drift can be largely mitigated using a dual-gate OECT architecture and that dual-gate-based biosensors can increase the accuracy and sensitivity of immuno-biosensors compared to a standard single-gate design. Specific binding can be detected at a relatively low limit of detection, even in human serum.

A psycholinguistic study of intergroup bias and its cultural propagation.

Intergroup bias is the tendency for people to inflate positive regard for their in-group and derogate the out-group. Across two online experiments (N = 922) this study revisits the methodological premises of research on language as a window into intergroup bias. Experiment 1 examined (i) whether the valence (positivity) of language production differs when communicating about an in- vs. out-group, and (ii) whether the extent of this bias is influenced by the positivity of input descriptors that were initially presented to participants as examples of how an in-group or out-group characterize themselves. Experiment 2 used the linear diffusion chain method to examine how biases are transmitted through cultural generations. Valence of verbal descriptions were quantified using ratings obtained from a large-scale psycholinguistic database. The findings from Experiment 1 indicated a bias towards employing positive language in describing the in-group (exhibiting in-group favoritism), particularly in cases where the input descriptors were negative. However, there was weak evidence for increased negativity aimed at the out-group (i.e., out-group derogation). The findings from Experiment 2 demonstrated that in-group positivity bias propagated across cultural generations at a higher rate than out-group derogation. The results shed light on the formation and cultural transmission of intergroup bias.

Size-dependent steady state saturation limit in biomolecular transport through nuclear membranes.

The nucleus preserves the genomic DNA of eukaryotic organisms and maintains the integrity of the cell by regulating the transport of molecules across the nuclear membrane. It is hitherto assumed that small molecules having a size below the passive permeability limit are allowed to diffuse freely to the nucleus while the transport of larger molecules is regulated via an active mechanism involving energy. Here we report on the kinetics of nuclear import and export of dextran molecules having a size below the passive permeability limit. The studies carried out using time-lapse confocal fluorescence microscopy show a clear deviation from the passive diffusion model. In particular, it is observed that the steady-state concentration of dextran molecules inside the nucleus is consistently less than the concentration outside, in contradiction to the predictions of the passive diffusion model. Detailed analysis and modeling of the transport show that the nuclear export rates significantly differ from the import rates, and the difference in rates is dependent on the size of the molecules. The nuclear export rates are further confirmed by an independent experimental study where we observe the diffusion of dextran molecules from the nucleus directly. Our experiments and transport model would suggest that the nucleus actively rejects exogenous macromolecules even below the passive permeability limit. This result can have a significant impact on biomedical research, especially in areas related to targeted drug delivery and gene therapy.

Biomolecular Interaction Analysis Quantification with a Low-Volume Microfluidic Chip and Particle Diffusometry.

Microfluidic techniques are widely applied in biomolecular analysis and disease diagnostic assays. While the volume of the sample that is directly used in such assays is often only femto-to microliters, the "dead volume" of solutions supplied in syringes and tubing can be much larger, even up to milliliters, increasing overall reagent use and making analysis significantly more expensive. To reduce the difficulty and cost, we designed a new chip using a low volume solution for analysis and applied it to obtain real-time data for protein-protein interaction measurements. The chip takes advantage of air/aqueous two-phase droplet flow, on-chip rapid mixing within milliseconds, and a droplet capture method, that ultimately requires only 2 µL of reagent solution. The interaction is analyzed by particle diffusometry, a nonintrusive and precise optical detection method to analyze the properties of microparticle diffusion in solution. Herein, we demonstrate on-chip characterization of human immunodeficiency virus p24 antibody-antigen protein binding kinetics imaged via fluorescence microscopy and analyzed by PD. The measured kon and koff are 1 × 106 M-1 s-1 and 3.3 × 10-4 s-1, respectively, and agree with independent measurement via biolayer interferometry and previously calculated p24-antibody binding kinetics. This new microfluidic chip and the protein-protein interaction analysis method can also be applied in other fields that require low-volume solutions to perform accurate measurement, analysis, and detection.