Diffusiophoresis promotes phase separation and transport of biomolecular condensates.

The internal microenvironment of a living cell is heterogeneous and comprises a multitude of organelles with distinct biochemistry. Amongst them are biomolecular condensates, which are membrane-less, phase-separated compartments enriched in system-specific proteins and nucleic acids. The heterogeneity of the cell engenders the presence of multiple spatiotemporal gradients in chemistry, charge, concentration, temperature, and pressure. Such thermodynamic gradients can lead to non-equilibrium driving forces for the formation and transport of biomolecular condensates. Here, we report how ion gradients impact the transport processes of biomolecular condensates on the mesoscale and biomolecules on the microscale. Utilizing a microfluidic platform, we demonstrate that the presence of ion concentration gradients can accelerate the transport of biomolecules, including nucleic acids and proteins, via diffusiophoresis. This hydrodynamic transport process allows localized enrichment of biomolecules, thereby promoting the location-specific formation of biomolecular condensates via phase separation. The ion gradients further impart directional motility of condensates, allowing them to exhibit enhanced diffusion along the gradient. Coupled with a reentrant phase behavior, the gradient-induced enhanced motility leads to a dynamical redistribution of condensates that ultimately extends their lifetime. Together, our results demonstrate diffusiophoresis as a non-equilibrium thermodynamic force that governs the formation and transport of biomolecular condensates.

Diffusion of proteins in crowded solutions studied by docking-based modeling.

The diffusion of proteins is significantly affected by macromolecular crowding. Molecular simulations accounting for protein interactions at atomic resolution are useful for characterizing the diffusion patterns in crowded environments. We present a comprehensive analysis of protein diffusion under different crowding conditions based on our recent docking-based approach simulating an intracellular crowded environment by sampling the intermolecular energy landscape using the Markov Chain Monte Carlo protocol. The procedure was extensively benchmarked, and the results are in very good agreement with the available experimental and theoretical data. The translational and rotational diffusion rates were determined for different types of proteins under crowding conditions in a broad range of concentrations. A protein system representing most abundant protein types in the E. coli cytoplasm was simulated, as well as large systems of other proteins of varying sizes in heterogeneous and self-crowding solutions. Dynamics of individual proteins was analyzed as a function of concentration and different diffusion rates in homogeneous and heterogeneous crowding. Smaller proteins diffused faster in heterogeneous crowding of larger molecules, compared to their diffusion in the self-crowded solution. Larger proteins displayed the opposite behavior, diffusing faster in the self-crowded solution. The results show the predictive power of our structure-based simulation approach for long timescales of cell-size systems at atomic resolution.

Single-molecule digital sizing of proteins in solution.

The physical characterization of proteins in terms of their sizes, interactions, and assembly states is key to understanding their biological function and dysfunction. However, this has remained a difficult task because proteins are often highly polydisperse and present as multicomponent mixtures. Here, we address this challenge by introducing single-molecule microfluidic diffusional sizing (smMDS). This approach measures the hydrodynamic radius of single proteins and protein assemblies in microchannels using single-molecule fluorescence detection. smMDS allows for ultrasensitive sizing of proteins down to femtomolar concentrations and enables affinity profiling of protein interactions at the single-molecule level. We show that smMDS is effective in resolving the assembly states of protein oligomers and in characterizing the size of protein species within complex mixtures, including fibrillar protein aggregates and nanoscale condensate clusters. Overall, smMDS is a highly sensitive method for the analysis of proteins in solution, with wide-ranging applications in drug discovery, diagnostics, and nanobiotechnology.

Colloidal Hydrogel with Staged Sequestration and Release of Molecules Undergoing Competitive Binding.

Competitive binding of distinct molecules in the hydrogel interior can facilitate dynamic exchange between the hydrogel and the surrounding environment. The ability to control the rates of sequestration and release of these molecules would enhance the hydrogel's functionality and enable targeting of a specific task. Here, we report the design of a colloidal hydrogel with two distinct pore dimensions to achieve staged, diffusion-controlled scavenging and release dynamics of molecules undergoing competitive binding. The staged scavenging and release strategy was shown for CpG oligodeoxynucleotide (ODN) and human epidermal growth factor (hEGF), two molecules exhibiting different affinities to the quaternary ammonium groups of the hydrogel. Fast ODN scavenging from the ambient environment occurred via diffusion through submicrometer-size hydrogel pores, while delayed hEGF release from the hydrogel was governed by its diffusion through nanometer-size pores. The results of the experiments were in agreement with simulation results. The significance of staged ODN-hEGF exchange was highlighted by the dual anti-inflammation and tissue proliferation hydrogel performance.

Restriction-induced time-dependent transcytolemmal water exchange: Revisiting the Kӓrger exchange model.

The Kӓrger model and its derivatives have been widely used to incorporate transcytolemmal water exchange rate, an essential characteristic of living cells, into analyses of diffusion MRI (dMRI) signals from tissues. The Kӓrger model consists of two homogeneous exchanging components coupled by an exchange rate constant and assumes measurements are made with sufficiently long diffusion time and slow water exchange. Despite successful applications, it remains unclear whether these assumptions are generally valid for practical dMRI sequences and biological tissues. In particular, barrier-induced restrictions to diffusion produce inhomogeneous magnetization distributions in relatively large-sized compartments such as cancer cells, violating the above assumptions. The effects of this inhomogeneity are usually overlooked. We performed computer simulations to quantify how restriction effects, which in images produce edge enhancements at compartment boundaries, influence different variants of the Kӓrger-model. The results show that the edge enhancement effect will produce larger, time-dependent estimates of exchange rates in e.g., tumors with relatively large cell sizes (>10 µm), resulting in overestimations of water exchange as previously reported. Moreover, stronger diffusion gradients, longer diffusion gradient durations, and larger cell sizes, all cause more pronounced edge enhancement effects. This helps us to better understand the feasibility of the Kärger model in estimating water exchange in different tissue types and provides useful guidance on signal acquisition methods that may mitigate the edge enhancement effect. This work also indicates the need to correct the overestimated transcytolemmal water exchange rates obtained assuming the Kärger-model.

Simultaneous removal of ammonia nitrogen, sulfamethoxazole, and antibiotic resistance genes in self-corrosion microelectrolysis-enhanced counter-diffusion biofilm system.

A self-corrosion microelectrolysis (SME)-enhanced membrane-aerated biofilm reactor (eMABR) was developed for the removal of pollutants and reduction of antibiotic resistance genes (ARGs). Fe2+ and Fe3+ formed iron oxides on the biofilm, which enhanced the adsorption and redox process. SME can induce microorganisms to secrete more extracellular proteins and up-regulate the expression of ammonia monooxygenase (AMO) (0.92 log2). AMO exposed extra binding sites (ASP-69) for antibiotics, weakening the competition between NH4+-N and sulfamethoxazole (SMX). The NH4+-N removal efficiency in the S-eMABR (adding SMX and IC) increased by 44.87 % compared to the S-MABR (adding SMX). SME increased the removal performance of SMX by approximately 1.45 times, down-regulated the expressions of sul1 (-1.69 log2) and sul2 (-1.30 log2) genes, and controlled their transfer within the genus. This study provides a novel strategy for synergistic reduction of antibiotics and ARGs, and elucidates the corresponding mechanism based on metatranscriptomic and molecular docking analyses.

3D cell aggregates amplify diffusion signals.

Biophysical models can predict the behavior of cell cultures including 3D cell aggregates (3DCAs), thereby reducing the need for costly and time-consuming experiments. Specifically, mass transfer models enable studying the transport of nutrients, oxygen, signaling molecules, and drugs in 3DCA. These models require the defining of boundary conditions (BC) between the 3DCA and surrounding medium. However, accurately modeling the BC that relates the inner and outer boundary concentrations at the border between the 3DCA and the medium remains a challenge that this paper addresses using both theoretical and experimental methods. The provided biophysical analysis indicates that the concentration of molecules inside boundary is higher than that at the outer boundary, revealing an amplification factor that is confirmed by a particle-based simulator (PBS). Due to the amplification factor, the PBS confirms that when a 3DCA with a low concentration of target molecules is introduced to a culture medium with a higher concentration, the molecule concentration in the medium rapidly decreases. The theoretical model and PBS simulations were used to design a pilot experiment with liver spheroids as the 3DCA and glucose as the target molecule. Experimental results agree with the proposed theory and derived properties.

Accurate measurement of Soret coefficients in binary hydrocarbons mixtures based on composite methods.

The Soret effect is a significant factor in various scenarios, with thermodiffusion in binary systems serving as a common method for the study. Most research focuses rarely on the distribution characteristics of components in diffusion systems; and Soret coefficients in the porous media could not be obtained by typical methods based on the thermodiffusion column, which are particularly important in the field of oil and gas development. Moreover, experiments on ground conditions have struggled to determine the Soret coefficient accurately due to the convective effect caused by gravity differentiation. The thermodiffusion behavior of n-pentane (C5) and n-heptane (C7) binary mixtures in both bulk and porous media conditions have been investigated, aiming to provide corrected coefficients that mitigate the influence of gravity using theoretical derivation. A new method was proposed to calculate the Soret coefficients in this work by establishing a model based on gas chromatography technology. Dynamic variation of component concentration along the path was studied, and the corresponding Soret coefficients were calculated and analyzed in parallel. The results indicate that the concentration and temperature exhibit a logarithmic relationship with the distance from the heat source. The Soret coefficient values obtained from measurements in porous media are closer to the theoretically corrected values, which do not account for gravity effects. Additionally, as the permeability decreases, the counteracting effect of porous media on convection becomes more pronounced. Therefore, it presents a novel method for accurately measuring the Soret coefficient that ignores convection to some extent.

Hybrid Diffusion Model for Stable, Affinity-Driven, Receptor-Aware Peptide Generation.

The convergence of biotechnology and artificial intelligence has the potential to transform drug development, especially in the field of therapeutic peptide design. Peptides are short chains of amino acids with diverse therapeutic applications that offer several advantages over small molecular drugs, such as targeted therapy and minimal side effects. However, limited oral bioavailability and enzymatic degradation have limited their effectiveness. With advances in deep learning techniques, innovative approaches to peptide design have become possible. In this work, we demonstrate HYDRA, a hybrid deep learning approach that leverages the distribution modeling capabilities of a diffusion model and combines it with a binding affinity maximization algorithm that can be used for de novo design of peptide binders for various target receptors. As an application, we have used our approach to design therapeutic peptides targeting proteins expressed by Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) genes. The ability of HYDRA to generate peptides conditioned on the target receptor's binding sites makes it a promising approach for developing effective therapies for malaria and other diseases.

Dependency of crossover point on absorption changes in bilayer diffusion reflection measurements.

Significance: A better understanding of diffusion reflection (DR) behavior may allow it to be used for more noninvasive applications, including the development of in vivo non-damaging techniques, especially for medical topical diagnosis and treatments. Aim: For a bilayer opaque substance where the attenuation of the upper layer is larger than the attenuation of the lower layer, the DR crossover point ( C p ) is location where the photons coming from the bottom layer start affecting the DR. We aim to study the dependency of the C p on absorption changes in different layers for constant scattering and top layer thickness. Approach: Monolayer and bilayer optical tissue-like phantoms were prepared and measured using a DR system. The results were compared with Monte Carlo simulations. Results: There is an agreement between the experiments and the simulations. C p correlates with the square root of the absorption coefficient ratio of the lower layer to the top layer. Conclusion: The experimental findings support and validate the theoretical prediction describing the dependency of the C p on the square root of the ratio of the layers' absorption coefficients. In addition, a secondary breaking point is suggested to be observed experimentally at the entrance to the noise area.

Quantifying biomolecular organisation in membranes with brightness-transit statistics.

Cells crucially rely on the interactions of biomolecules at their plasma membrane to maintain homeostasis. Yet, a methodology to systematically quantify biomolecular organisation, measuring diffusion dynamics and oligomerisation, represents an unmet need. Here, we introduce the brightness-transit statistics (BTS) method based on fluorescence fluctuation spectroscopy and combine information from brightness and transit times to elucidate biomolecular diffusion and oligomerisation in both cell-free in vitro and in vitro systems incorporating living cells. We validate our approach in silico with computer simulations and experimentally using oligomerisation of EGFP tethered to supported lipid bilayers. We apply our pipeline to study the oligomerisation of CD40 ectodomain in vitro and endogenous CD40 on primary B cells. While we find a potential for CD40 to oligomerize in a concentration or ligand depended manner, we do not observe mobile oligomers on B cells. The BTS method combines sensitive analysis, quantification, and intuitive visualisation of dynamic biomolecular organisation.

Sonophoresis mediated diffusion of caffeine loaded Transcutol® enriched cerosomes for topical management of cellulite.

The goal of this research was to augment the deposition of caffeine loaded Transcutol® enriched cerosomes (TECs) gel for efficient topical treatment of cellulite utilizing the sonophoresis technique. Caffeine-loaded TECs were prepared using thin film hydration method applying 23 factorial design to study the impact of different factors, each with two levels on the entrapment efficiency (EE%), particle size (PS), polydispersity index (PDI), and zeta potential (ZP) of the formulated TECs. The studied factors were cetyl trimethyl ammonium bromide (CTAB) amount (mg) (X1), phosphatidylcholine (PC) amount (mg) (X2), and Transcutol® amount (mg) (X3). Design-Expert® software was utilized to determine the optimum TECs formulation. Afterward, the optimum TECs formulation was loaded into a gel and subjected to extra investigations. The optimum TECs formulation was (TEC5) which was prepared using 10 mg of CTAB, 150 mg of PC, and 10 mg of Transcutol®. TEC5 presented EE% of 87.44 ± 0.14 %, PS of 308.60 ± 13.38 nm, PDI of 0.455 ± 0.030, and ZP of 50.20 ± 1.55 mV. TEC5 had a fiber-like morphology, with elongated tubules of ceramide. Further, the optimum TECs formulation showed a high stability profile. Moreover, an in vivo dermatokinetic study showed superior deposition of caffeine from TEC5 gel coupled with the sonophoresis on rat skin compared to TEC5 gel and caffeine gel. Moreover, the histopathological study of TEC5 on rat skin confirmed the non-irritant nature of TEC 5 gel mediated by ultrasonic waves through the skin. Overall, the outcomes exposed the obvious superiority of sonophoresis delivered TECs-gel for topical delivery of caffeine for cellulite management.

On-site evaluation of DGT passive sampling for quantitatively measuring per- and polyfluoroalkyl substances in a river-estuary-sea water system.

The passive sampling technique of diffusive gradients in thin-films (DGT) is promising for monitoring emerging contaminants such as per- and polyfluoroalkyl substances (PFAS). It is urgent to evaluate the impacts of salinity and exposure time on DGT sampling before it can be set as a standard method. Herein, DGT sampler based on the binding gel of weak anion exchanger (WAX) resin was deployed in a representative water system of the Xiaoqing river-estuary-sea for representative sampling windows (<1 day to 28 days) with high pH (8.18 ± 0.04 to 8.51 ± 0.17) and wide ranges of salinity (0.95 ± 0.07‰ to 14.37 ± 3.92‰), total dissolved solids (1.20 ± 0.09 g/L to 15.29 ± 3.91 g/L) and dissolved organic matter (2.8-32 mg/L). The results showed that the WAX-DGT sampler exhibited good performance for most target PFAS except for short-chain perfluorocarboxylates (C ≤ 5) in 14 days. When the exposure time was over 14 days, biofouling of the sampler may deflect the mass accumulation of the PFAS in the sampler. Salinity played an important role in the mass binding of PFAS by DGT. The shorter the carbon chain of the compound, the greater the influence of the salinity. PFAS with carboxyl groups had greater affinities for the biofouled membrane filter than those with sulfonic groups. In the river-estuary-sea system, where PFAS concentrations changed dynamically, the temporal resolution of the monitoring strategy has been demonstrated to be more important than spatial resolution. DGT provided a better integral of PFAS exposure than grab sampling in the dynamic water system and offered equivalent sensitivity of grab sampling with exposure time <10 d and greater sensitivity with exposure time ≥10 d. Thus, DGT has the advantage of providing high temporal resolution monitoring. This study provided support for the standardization of the DGT technique.

Impaired diffusion at submaximal lung inflation in asthma and copd patients.

INTRODUCTION: Dissolved-phase 129Xe MRI metrics suggest that gas diffusion may be more compromised at submaximal lung inflation compared to maximal inflation. We hypothesized that this diffusion deficit could be detected by comparing the carbon monoxide transfer coefficient (Kco) at submaximal lung inflation to that measured routinely at total lung capacity (TLC). METHODS: Asthma and COPD patients performed carbon monoxide diffusion tests, first at maximal lung inflation for routine Kco and alveolar volume VA and then, at a 30 % reduced inflation (redux; obtaining Kcoredux and VAredux). At both inflations mixing efficiency was determined as VA/TLC and VAredux/TLCredux to examine a potential effect on Kcoredux/Kco behavior. RESULTS: In normal subjects (n=36), median Kcoredux/Kco amounted to 130 [IQR:122-136]% as expected for normal Kco recruitment response. However, 60 % of asthma patients (49/83) and 80 % of COPD patients (44/55) showed reduced Kco recruitment at submaximal inflation (Kcoredux/Kco<122 %). In the asthma group, with otherwise normal routine Kco, Kcoredux/Kco was significantly correlated with RV/TLC ratio (r=-0.53;P<0.001), but not with VA/TLC. In COPD patients, all with abnormal routine Kco, abnormal Kcoredux/Kco response occurred in those patients with lower FEV1, higher RV/TLC and lower VA/TLC (P<0.01 for all). CONCLUSION: Sizeable portions of COPD and asthma patients showed a lack of normal Kco recruitment at submaximal lung inflation, related to high RV/TLC. In asthma, this was the case despite normal Kco at full lung inflation, suggesting that hyperinflation at lung volumes less than TLC affects the carbon monoxide diffusion rate constant by distorting pulmonary capillaries and alveolar-capillary membranes.

Linear diffusion noise boosted deep image prior for unsupervised sparse-view CT reconstruction.

Objective.Deep learning has markedly enhanced the performance of sparse-view computed tomography reconstruction. However, the dependence of these methods on supervised training using high-quality paired datasets, and the necessity for retraining under varied physical acquisition conditions, constrain their generalizability across new imaging contexts and settings.Approach.To overcome these limitations, we propose an unsupervised approach grounded in the deep image prior framework. Our approach advances beyond the conventional single noise level input by incorporating multi-level linear diffusion noise, significantly mitigating the risk of overfitting. Furthermore, we embed non-local self-similarity as a deep implicit prior within a self-attention network structure, improving the model's capability to identify and utilize repetitive patterns throughout the image. Additionally, leveraging imaging physics, gradient backpropagation is performed between the image domain and projection data space to optimize network weights.Main Results.Evaluations with both simulated and clinical cases demonstrate our method's effective zero-shot adaptability across various projection views, highlighting its robustness and flexibility. Additionally, our approach effectively eliminates noise and streak artifacts while significantly restoring intricate image details.Significance. Our method aims to overcome the limitations in current supervised deep learning-based sparse-view CT reconstruction, offering improved generalizability and adaptability without the need for extensive paired training data.

Understanding retention and intra-particle diffusivity of alkylsulfobetaine-bonded Ethylene Bridged Particles with different mesopore sizes for hydrophilic interaction liquid chromatography applications.

The role of the average pore diameter (APD) of 1.7µm AtlantisTM Premier BEHTM Particles derivatized with a zwitterionic group (propylsulfobetaine) on the efficiency of their 2.1 × 50 mm hydrophilic interaction liquid chromatography (HILIC) packed columns is investigated experimentally. Van Deemter plots for toluene (neutral, hydrophobic), cytosine (neutral, polar), tosylate (negatively charged), bretylium and atenolol (positively charged) were measured on three HILIC columns packed with BEH Z-HILIC Particles having APDs of 95 Å, 130 Å, and 300 Å. The intraparticle diffusivities of the analytes across these three BEH Z-HILIC Particles were measured by the peak parking method. The experimental data reveal that the slope of the C-branch of the van Deemter plots can be reduced by factors of about 15 for toluene, 2.5 for cytosine, 6 for atenolol, 5 for tosylate, and 14 for bretylium with increasing the APD from 95 Å to 300 Å. This observation is explained by: (1) the reduced amount of the highly viscous water diffuse layer and subsequent increase of the amount of acetonitrile-rich eluent in the mesopores, (2) the localized electrostatic adsorption of the retained analytes onto the zwitterion-bonded BEH Particles, and (3) depletion/excess of the analytes into the water diffuse layer. A general model of intraparticle diffusivity was then proposed to account for the impact of the APD of Z-HILIC Particles on the solid-to-liquid mass transfer resistance of small molecules. The model highlights the relevance of the thickness of the water diffuse layer, the access of the bulk eluent into the mesopore, the localized electrostatic adsorption, and the partitioning constant of the retained analyte between the bulk eluent and the water diffuse layer.

The Diffusion Exchange Ratio (DEXR): A minimal sampling of diffusion exchange spectroscopy to probe exchange, restriction, and time-dependence.

Water exchange is increasingly recognized as an important biological process that can affect the study of biological tissue using diffusion MR. Methods to measure exchange, however, remain immature as opposed to those used to characterize restriction, with no consensus on the optimal pulse sequence (s) or signal model (s). In general, the trend has been towards data-intensive fitting of highly parameterized models. We take the opposite approach and show that a judicious sub-sample of diffusion exchange spectroscopy (DEXSY) data can be used to robustly quantify exchange, as well as restriction, in a data-efficient manner. This sampling produces a ratio of two points per mixing time: (i) one point with equal diffusion weighting in both encoding periods, which gives maximal exchange contrast, and (ii) one point with the same total diffusion weighting in just the first encoding period, for normalization. We call this quotient the Diffusion EXchange Ratio (DEXR). Furthermore, we show that it can be used to probe time-dependent diffusion by estimating the velocity autocorrelation function (VACF) over intermediate to long times (∼2-500ms). We provide a comprehensive theoretical framework for the design of DEXR experiments in the case of static or constant gradients. Data from Monte Carlo simulations and experiments acquired in fixed and viable ex vivo neonatal mouse spinal cord using a permanent magnet system are presented to test and validate this approach. In viable spinal cord, we report the following apparent parameters from just 6 data points: τk=17±4ms, fNG=0.72±0.01, Reff=1.05±0.01µm, and κeff=0.19±0.04µm/ms, which correspond to the exchange time, restricted or non-Gaussian signal fraction, an effective spherical radius, and permeability, respectively. For the VACF, we report a long-time, power-law scaling with ≈t-2.4, which is approximately consistent with disordered domains in 3-D. Overall, the DEXR method is shown to be highly efficient, capable of providing valuable quantitative diffusion metrics using minimal MR data.

Translational Diffusion and Self-Association of an Intrinsically Disordered Protein κ-Casein Using NMR with Ultra-High Pulsed-Field Gradient and Time-Resolved FRET.

Much attention has been given to studying the translational diffusion of globular proteins, whereas the translational diffusion of intrinsically disordered proteins (IDPs) is less studied. In this study, we investigate the translational diffusion and how it is affected by the self-association of an IDP, κ-casein, using pulsed-field gradient nuclear magnetic resonance and time-resolved Förster resonance energy transfer. Using the analysis of the shape of diffusion attenuation and the concentration dependence of κ-casein diffusion coefficients and intermolecular interactions, we demonstrate that κ-casein exhibits continuous self-association. When the volume fraction of κ-casein is below 0.08, we observe that κ-casein self-association results in a macroscopic phase separation upon storage at 4 °C. At κ-casein volume fractions above 0.08, self-association leads to the formation of labile gel-like networks without subsequent macroscopic phase separation. Unlike α-casein, which shows a strong concentration dependence and extensive gel-like network formation, only one-third of κ-casein molecules participate in the gel network at a time, resulting in a more dynamic and less extensive structure. These findings highlight the unique association properties of κ-casein, contributing to a better understanding of its behavior under various conditions and its potential role in casein micelle formation.

A finite volume approach to dosimetric calculations in diffusing alpha-emitters radiation therapy.

Objective.In diffusing alpha-emitters radiation therapy ('Alpha DaRT'), the diffusion-leakage (DL) model is used to determine the spatial distributions of the emitters and the corresponding alpha dose, critical for a successful treatment. This work first introduces a finite volume (FV) approach to develop numerical schemes to simulate the DL model in one, two and three dimensions then presents how variations over realistic ranges of the DL model parameters related to desorption, diffusion and leakage processes affect the alpha dose distribution and the position of the clinically significant alpha particle10Gy isodose. This work also presents the effects of three modeling approximations: two source geometry approximations (solid cylinder instead of hollow, pixelized cross section instead of circular), and one dosimetric approximation (single-source dose superposition instead of multiple-sources direct dose calculation).Approach.The introduced FV approach was used to obtain spatial distributions of the emitters, from which the corresponding alpha dose distributions were calculated under the assumption of a local deposition of the alpha particles' energies. Variation ranges of the DL model parameters were based on previously published data. For each modeling approximation studied, the error and relative error on the alpha dose distribution were calculated and the displacement of the10Gy isodose was evaluated.Main results.Over realistic ranges, the desorption probabilities, diffusion lengths, and leakage probabilities affect the position of the alpha particle10Gy isodose by∼0.1mm,∼1.5mm and∼0.5mm, respectively. The three modeling approximations studied have a negligible effect on the alpha particle10Gy isodose position, with displacements⩽0.01mm.Significance.This work quantitatively evaluates the relative importance of different parameters and approximations in Alpha-DaRT alpha dose calculations based on their impact not only on the dose variation at a given distance from the source but also on the displacement of clinically significant isodoses.

Light in evaluation of molecular diffusion in tissues: Discrimination of pathologies.

The evaluation of the diffusion properties of different molecules in tissues is a subject of great interest in various fields, such as dermatology/cosmetology, clinical medicine, implantology and food preservation. In this review, a discussion of recent studies that used kinetic spectroscopy measurements to evaluate such diffusion properties in various tissues is made. By immersing ex vivo tissues in agents or by topical application of those agents in vivo, their diffusion properties can be evaluated by kinetic collimated transmittance or diffuse reflectance spectroscopy. Using this method, recent studies were able to discriminate the diffusion properties of agents between healthy and diseased tissues, especially in the cases of cancer and diabetes mellitus. In the case of cancer, it was also possible to evaluate an increase of 5% in the mobile water content from the healthy to the cancerous colorectal and kidney tissues. Considering the application of some agents to living organisms or food products to protect them from deterioration during low temperature preservation (cryopreservation), and knowing that such agent inclusion may be reversed, some studies in these fields are also discussed. Considering the broadband application of the optical spectroscopy evaluation of the diffusion properties of agents in tissues and the physiological diagnostic data that such method can acquire, further studies concerning the optimization of fruit sweetness or evaluation of poison diffusion in tissues or antidote application for treatment optimization purposes are indicated as future perspectives.