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Mucosal barriers are a natural defense system for preventing the entry of foreign objects into the body; however, they pose obstacles for effective drug delivery. Coated polymer nanoparticles (NPs) have been shown to possess improved rates of diffusion across mucus compared to their uncoated, or bare, counterparts. Choline carboxylic acid-based ionic liquids (ILs) are highly tunable and show high biocompatibility and mucus modulation properties, making them an ideal choice for the improvement of NP diffusion through mucosal barriers. This study aimed to investigate whether the use of choline-based ILs has a positive effect on the dispersibility of poly-(lactic-co-glycolic acid) (PLGA), poly-(ethylene glycol) methyl ether-block-poly-(lactide-co-glycolide) (PEG–PLGA), and poly-(ethylene glycol)–poly-(lactic acid) (PEG–PLA) NPs through nasal mucus by using a multiple particle tracking method. The samples, according to the IL used, showed altered rates of diffusion in both aqueous and mucosal environments. The use of CA2HE 1:1 with PEG–PLGA NPs slowed NP diffusion, while the use of the same IL increased diffusion for PEG–PLA. Additionally, UV–vis spectroscopy was used to identify the possible formation of complexes between the mucin polymer and NPs. Circular dichroism (CD) spectroscopy was used to analyze any potential changes in the secondary structure of mucin as a result of the introduction of polymeric NPs. It was demonstrated that the use of an IL can stabilize the interactions between polymer NPs and mucin polymers. Isothermal titration calorimetry was used to obtain quantitative measurement of the binding energies between NPs and mucus and serves to confirm the results obtained from CD spectroscopy. Last, an ex vivo porcine nasal mucosa model was used to explore their use in a nasal delivery context, disclosing a possible connection between the use of zwitterionic transport materials and more effective drug delivery. This research demonstrates the potential of choline carboxylic acid-based ILs to control the transport behavior of polymer NPs for intranasal drug delivery. [ABSTRACT FROM AUTHOR] more...

Bimetallic nanoclusters have a wide range of uses, and Re-W has been shown to be a catalyst due to its good properties, so it is crucial to study Re-W nanoclusters at the microscopic scale in order to obtain better-performing Re-W nanoclusters. This research investigates the diffusion and structural modification of Re on the surfaces of W nanoclusters at high temperatures. The EAM potential function is employed in this work to explain the interaction between Re and W, and the LAMMPS (large-scale atom/polar massively parallel simulation) package is used for the simulation. We observed the diffusion phenomenon in our investigation by depositing Re atoms on the surface of the W nanoclusters. The findings demonstrate that there are differences in the exchange energy barriers between the Re and W atoms at various locations. At the intersection of the faces, the more (110) faces there are, the lower the exchange energy barrier between the Re and W atoms. During diffusion, the mechanisms of vacancy formation and migration were investigated. The results of the analysis demonstrate that the formation and migration of these vacancies are facilitated by the presence of Re atoms. Furthermore, we noticed that the lattice structure changed throughout the entire deposition process. This observation offers a theoretical direction for producing Re-W bimetallic nanoclusters with a little lattice distortion. [ABSTRACT FROM AUTHOR] more...

Controlled evaporative self-assembly of colloidal particles based on particle size is desirable when designing efficient, single-step deposition coating processes such as those encountered in specialized antireflective silica coatings. Particle movement during the drying process is complex. We experimentally and numerically investigate particle concentration profiles in binary colloidal films as a function of the small particle volume fraction and particle size ratio. Using a chemical potential expression that incorporates dilute interactions and also accounts for different particle size ratios, initial concentrations, and Peclet values, we calculate small and big particle concentration profiles. By characterizing the full film profile, we observe complex sandwich structures that were previously not predicted by theoretical models of film stratification and are relevant to specific coating applications. We employ microbeam X-ray scattering to characterize dried film profiles as a function of the film depth. These concentration data also show complex sandwich structures and highlight the necessity of full film characterization as opposed to only examining the surface. The presented numerical model does not correctly predict the measured film configurations, implying that additional particle interactions may need to be considered. [ABSTRACT FROM AUTHOR] more...

Carbon mitigation is one challenging issue that the world is facing. To tackle the deleterious impacts of CO2, processes emerged, including chemisorption from amine-based solvents and, more recently, physisorption in nanoporous solids. Physisorption in metal–organic frameworks (MOFs) is currently attracting considerable attention; however, the selection of the optimum sorbent is still challenging. While CO2 adsorption by MOFs has been widely explored from a thermodynamics standpoint, dynamical aspects remain less explored. CALF-20-(Zn) MOF was recently proposed as a promising alternative to the commercially used CO2 13X zeolite sorbents; however, an in-depth understanding of the nanoscopic mechanisms originating its good performance still has to be achieved. To do so, we deliver some insights into the adsorption and diffusion of CO2, H2O, and mixtures in CALF-20 through atomistic simulations. CALF-20-(Zn) was revealed to exhibit unconventional guest–host behaviors that give rise to abnormal guest thermodynamics and dynamics. The hydrophobic nature of the nanoporous solid leads to a low water adsorption enthalpy at low loading, followed by a continuous increase, driven by strong water hydrogen bonds, found to arrange as quasi 1D molecular wires in MOF nanoporosity, recalling water behavior in small-diameter carbon nanotubes. While no superdiffusion was found in the CALF-20-(Zn) as compared to carbon nanotubes, this behavior was shown to impact the guest-loading diffusion coefficient profile, with the presence of a minimum that correlates with the inflection point in the adsorption isotherm corresponding to the H2O wires formation. Interestingly, the diffusion coefficients of CO2 and H2O were also found to be of the same order of magnitude, with similar nonlinear profiles as a function of the guest loading. We further demonstrated that the diffusion coefficient for CO2 in the presence of water decreases with increasing water loading. [ABSTRACT FROM AUTHOR] more...

To achieve a better catalytic performance, it is of great interest to synthesize nanosized zeolites with reduced internal diffusion limitations. Herein, c-axis shortened wheel-like mordenite nanoassemblies were synthesized. The crystal growth along the [001] direction was successfully inhibited with K+ cations as structure breaking agents. The wheel-like crystal is 1.5–2 μm in diameter and 200–300 nm in thickness. The growth of such a unique structure underwent a nonclassical crystallization process including the generation of amorphous worm-like particles and formation of wheel-like crystallites followed by a–b plane oriented growth of the crystals. The obtained MOR wheel-like assemblies possessed larger surface area and external surface area, displayed better mass transfer properties, and exhibited much better catalytic performance than MOR spheroid-like assemblies and conventional bulk MOR zeolite in dimethyl ether (DME) carbonylation reaction, with two and a half times higher the conversion of DME than the bulk MOR, although these samples had identical Si/Al ratios and acid properties. This work provides a simple route to control the zeolite morphology by alkali metal cations and brings forward an effective strategy to prepare zeolite materials with improved catalytic performance. [ABSTRACT FROM AUTHOR] more...

A durable Li–Se battery is fabricated by implementing a rational and facile design strategy for the cathode. The cathode consists of a Se/graphitic carbon nitride (g-C3Nript>4) composite combined with a solid lithium titanate (Li4Ti5O12, LTO) layer applied as a solid coating over the separator. The solid LTO layer has pores large enough to allow Li+ ions to diffuse through to the anode during charging but small enough to effectively block the polyselenides formed during the discharging cycle and confine them to the cathode, thus inhibiting capacity fade and improving the operational lifespan. The micrometer-thick LTO barrier layer affords selective diffusion of Li+ ions, with an average Li+ diffusion coefficient of 6 × 10–11 cm2 s–1, enabling reasonably fast ion transport and kinetics. Simultaneously, g-C3N4, which is rich with active heteroatom (N) sites, also affords a very high Li+ ion adsorption, leading to an improved capacity compared to pristine Se. The Se/g-C3N4/LTO@separator-Li+/Li cell delivers a superior capacity (750 versus 538 mAh g–1 at 0.1 C-rate), rate capability (39% versus 22% capacity retention ongoing from 0.1 to 2 C-rate), and cycle life (498 versus 283 mAh g–1 reversible capacity after 400 cycles) compared to the equivalent cell devoid of the LTO layer. Extended long-term cycling metrics showed a 310 mAh g–1 reversible capacity at 2 C, with 78% retention after 1600 cycles, and reiterated the potential it has for scale-up and even commercial applications. [ABSTRACT FROM AUTHOR] more...

Surface-enhanced Raman scattering (SERS), a nondestructive, ultrasensitive detection method, has a wide range of potential applications. However, its application is limited due to the weak Raman scattering signals. Therefore, it is urgent to explore a simple physical method to prepare SERS substrates with high detection limits and excellent reproducibility. In this work, Ta–Ag alloy films were prepared by magnetron sputtering at room temperature, and a large number of Ag nanoparticles were self-formed on the alloy films' surface by adjusting the deposition time, Ag content, and annealing temperature. Further research reveals that this is because the amorphous Ta in the alloy films prevents the growth of Ag grains inside Ta–Ag alloy films, resulting in the diffusion of Ag atoms to the alloy film's surface to form Ag nanoparticles. The results demonstrate that Ag nanoparticles/Ta 55.5 at % Ag alloy films used as SERS substrates have excellent reproducibility and high sensitivity to detect 5 × 10–16 mol L–1 rhodamine 6G (R6G) solution and 5 × 10–12 mol L–1 crystal violet (CV) solution. This method provides a simple approach to developing high-performance SERS substrates. [ABSTRACT FROM AUTHOR] more...

Li 2 GeO 3 has gained attention as a potential anode material for lithium-ion batteries due to its high ion diffusion rate. This research uses advanced computational modeling to examine how different types of dopants and their substitution sites affect the defect properties, electronic structure, and lithium-ion diffusion in Li 2 GeO 3 . By analyzing isovalent and aliovalent dopants at various crystallographic positions, the study aims to uncover the mechanisms by which doping influences the material's performance as an anode. The findings indicate that halide dopants at the oxygen sites notably alter the electronic structure and ion diffusion rate. A decreasing trend in the band gap was observed with increasing concentrations of tetra- and trivalent dopants. Moreover, except for fluoride (F - ), other halide dopants at the 4a oxygen site exhibited the opposite effect on the electronic structure and ion diffusion rate. The 8b site was identified as the most favorable for F - substitution, showing the lowest formation energy. Substitution of F - at the 8b site significantly reduced the band gap (from 3.77 to 2.19 eV) by shifting the valence band maxima from the Z -point to the Y -point in high-symmetry representation and substantially increased the ion diffusion rate (1.70 × 10 -10 cm 2 /s) by broadening the diffusion pathway. more...

Diffusion at the molecular level involves random collisions between particles, the structure of local microscopic environments, and interactions among the molecules involved. Sampling all of these aspects, along with correcting for finite-size effects, can make the calculation of infinitely dilute diffusion coefficients computationally difficult. We present a new approach for estimating the translational diffusion coefficient of biomolecular structures by encapsulating these driving forces of diffusion through piecewise assembly of the component residues of the protein structure. By linking the local chemistry of a solvent-exposed patch of a molecule to its contribution to the overall hydrodynamic radius, an accurate prediction of the computationally and experimentally comparable diffusion coefficients can be constructed following a solvent-excluded surface area calculation. We demonstrate that the resulting predictions for diffusion coefficients from peptides through to protein structures are comparable to explicit molecular simulations and improve on statistical mass-based predictions, which tend to rely on limited training data. As this approach uses the chemical identity of molecular structures, we find that it is able to predict and identify differences in diffusivity for structures that would be indistinguishable by mass information alone. more...

The widespread use of aqueous film-forming foams (AFFFs) in firefighting has led to significant contamination by per- and polyfluoroalkyl substances (PFAS), including in building materials like concrete. This study investigated the initial phase of PFAS contamination in concrete, focusing on factors influencing PFAS retention and penetration. Laboratory experiments assessed the uptake kinetics of PFAS into concrete over one year, revealing that PFAS penetrated beyond surface layers, as confirmed by high-resolution mass spectrometry and desorption electrospray ionization mass spectrometry imaging. PFAS mass loss into the concrete was limited, with 0.99% to 18.5% (mean 6.6%) of initial spiked PFAS being retained. Uptake behaviors were influenced by PFAS chain length and chemistry, concrete surface characteristics, as well as wetting/drying cycles, which accelerated PFAS penetration through the wick effect. Damaged concrete surfaces also showed faster PFAS penetration due to the exposed interfacial transition zones. Field-impacted concrete samples from Canada revealed some similar migration trends with lab-exposed concrete, with shorter-chain PFAS exhibiting greater mobility in the concrete matrix, though notable differences were observed between field and lab samples. These findings highlight the complex dynamics of PFAS contamination in concrete and provide insights into factors affecting PFAS penetration and retention. more...

Nanostructured microelectrodes (NMEs) are an attractive alternative to yield sensitive bioassays in unprocessed samples. However, although valuable for different applications, nanoporous NMEs usually cannot boost the sensitivity of diffusion-limited analyses because of the enlarged Debye length within the nanopores, which reduces their accessibility. To circumvent this limitation, nanopore-free gold NMEs were electrodeposited from 45 μm SU-8 apertures, featuring nanoridged microspikes on a recessed surface of gold thin film while carrying interconnected crown-like and spiky structures along the edge of a SU-8 passivation layer. These structures were grown onto ultradense, vertical array chips that offer a promising strategy for translating reproducible, high-resolution, and cost-effective sensors into real-world applications. The NMEs yielded reproducible analyses, while machine learning allowed us to predict the analytical responses from NME electrodeposition data. By taking advantage of the high surface area and accessible structure of the NMEs, these structures provided a sensitivity for [Fe(CN) 6 ] 3-/4- that was 5.5× higher than that of bare WEs while also delivering a moderate antibiofouling property in undiluted human plasma. As a proof of concept, these electrodes were applied toward the fast (22 min) and simple determination of Staphylococcus aureus by monitoring the oxidation of [Fe(CN) 6 ] 4- , which acted as a cellular respiration rate redox reporter. The sensors also showed a wide dynamic range, spanning 5 orders of magnitude, and a calculated limit of detection of 0.2 CFU mL -1 . more...

In single-molecule Förster resonance energy transfer (FRET) experiments, characterizing conformational dynamics from photon bursts emitted by diffusing molecules can be challenging due to the interplay of molecular transitions, translational diffusion, and background noise. This paper extends the maximum likelihood analysis of photon bursts (burstML) to incorporate both conformational dynamics and diffusion through the laser spot, offering a comprehensive analysis of photon bursts from single diffusing molecules. The new approach integrates two previously developed methods: one accounting for diffusion without conformational dynamics and the other addressing conformational dynamics without diffusion. By combining these approaches, the extended burstML method allows determination of brightness, diffusion time, FRET efficiency in each state, and transition rates, even under challenging conditions, such as fast (comparable to photon count rates) and slow (one transition per several bursts) transition rates, high background noise, and unequal brightness or diffusivity of the states. The performance of burstML was demonstrated on simulated data of a two-state diffusing molecule and compared with the colorML method, which simplifies analysis by excluding translational diffusion. While colorML is computationally efficient and performs well under ideal conditions (low background noise and equal brightness and diffusivity of states), its accuracy diminishes when these conditions are not met. In contrast, burstML remains accurate across a broader range of experimental scenarios. Both burstML and colorML were applied to analyze folding of several proteins (Pin1 WW domain, FiP35 WW domain, FBP28 WW domain, villin, and a synthetic protein α 3 D) under various experimental conditions, highlighting where colorML differs from burstML and providing insights into the applicability of the methods in diverse experimental settings. more...

We report an experimental investigation of photocarrier dynamics in a heterostructure formed by a WSe 2 monolayer stacked on a multilayer α-RuCl 3 flake. The samples were fabricated using mechanical exfoliation and dry transfer techniques. Photoluminescence measurements showed that the excitonic photoluminescence of WSe 2 is quenched by more than 3 orders of magnitude upon contact with α-RuCl 3 . Transient absorption measurements revealed an ultrashort photocarrier lifetime of 0.5 ps in the heterostructure. Spatially resolved transient absorption microscopy measurements were employed to probe the transport properties of these photocarriers, resulting in a room-temperature diffusion coefficient of 370 cm 2 s -1 , which is higher than the exciton diffusion coefficients of most previously studied 2D semiconductors. These results suggest that α-RuCl 3 -doped WSe 2 could be utilized in high-speed optoelectronic devices. more...

The discharge of Fukushima radioactively contaminated water into the Pacific Ocean started in August 2023, posing comprehensive threats to marine ecosystems and human health globally. This study introduces the Fukushima Contaminated Water Risk Factor (FCWRF), which integrates three components─radionuclide diffusion, bioaccumulation, and global seafood trade─to evaluate the spatiotemporal distribution of risks based on actual discharge practices. Results suggest that comprehensive risks exceeding 2 orders of magnitude beyond the baseline will be transferred to six continents globally. Furthermore, the spread of such risks is projected to be six times faster than radionuclide diffusion. In the simulation, the results illustrated a small increase in radionuclide activity occurring in most regions of the Pacific Ocean. Nevertheless, the dimensionless FCWRF based on a novel integrated framework bridges the barriers among different fields in the risk assessment of radionuclides, thereby underpinning timely and effective responses from the global community. more...

Accurate prediction of molecular geometries is crucial for drug discovery and materials science. Existing fast conformer prediction algorithms often rely on approximate empirical energy functions, resulting in low accuracy. More accurate methods like ab initio molecular dynamics and Markov chain Monte Carlo can be computationally expensive due to the need for evaluating quantum mechanical energy functions. To address this, we introduce AGDIFF, a novel machine learning framework that utilizes diffusion models for efficient and accurate molecular structure prediction. AGDIFF extends previous models (such as GeoDiff) by enhancing the global, local, and edge encoders with attention mechanisms, an improved SchNet architecture, batch normalization, and feature expansion techniques. AGDIFF outperforms GeoDiff on both the GEOM-QM9 and GEOM-Drugs data sets. For GEOM-QM9, with a threshold (δ) of 0.5 Å, AGDIFF achieves a mean COV-R of 93.08% and a mean MAT-R of 0.1965 Å. On the more complex GEOM-Drugs data set, using δ = 1.25 Å, AGDIFF attains a median COV-R of 100.00% and a mean MAT-R of 0.8237 Å. These findings demonstrate AGDIFF's potential to advance molecular modeling techniques, enabling more efficient and accurate prediction of molecular geometries, thus contributing to computational chemistry, drug discovery, and materials design. https://github.com/ADicksonLab/AGDIFF. more...

Lead-halide hybrid perovskites (RNH 3 PbX 3 , X = halide, e.g., Cl, Br, I; R = organic moiety) show promise for next-generation optoelectronic devices due to their simple synthesis routes, strong light absorption, and high photoluminescence quantum yield. However, postsynthetic halide exchange in lead-halide perovskites poses a challenge for the functionality of many perovskite devices. For example, in all-perovskite heterostructures, halide diffusion results in the formation of undesired mixed alloys rather than sharp interfaces required for many optoelectronic applications. To address this issue, we incorporated lysine molecules, one of the 20 common amino acids, into a hybrid perovskite MAPbBr 3 (MA = CH 3 NH 3 ) host and investigated their impact on the host's ability to undergo postsynthetic halide exchange. We immersed lysine-incorporated MAPbBr 3 crystals in solutions containing Cl - or I - for varying durations and analyzed subsequent halide exchange-related changes using ion chromatography, high-resolution powder X-ray diffraction, and photoluminescence spectroscopy. Our findings unanimously indicate that incorporated lysine significantly impedes postsynthetic Cl - and I - diffusion into bulk MAPbBr 3 . Our new bioinspired approach opens a route toward mitigating postsynthetic halide exchange in lead-halide hybrid perovskites and improving the suitability of perovskite devices for optoelectronic applications. more...

The existence of the phenomenon of enhanced enzyme diffusion (EED) has been a topic of debate in recent literature. One proposed mechanism to explain the origin of EED is oligomeric enzyme dissociation. We used mass photometry (MP), a label-free single-molecule technique, to investigate the dependence of the oligomeric states of several enzymes on their ligands. The studied enzymes of interest are catalase, aldolase, alkaline phosphatase, and vanillyl-alcohol oxidase (VAO). We compared the ratios of oligomeric states in the presence and absence of the substrate as well as different substrate and inhibitor concentrations. Catalase and aldolase were found to dissociate into smaller oligomers in the presence of their substrates, independently of inhibition, while for alkaline phosphatase and VAO, different behaviors were observed. Thus, we have identified a possible mechanism which explains the previously observed diffusion enhancement in vitro . This enhancement may occur due to the dissociation of oligomers through ligand binding. more...

The aggregation and accumulation of amyloid β 42 (Aβ42) peptides on the surface of brain cells is associated with Alzheimer's disease (AD); however, the underlying molecular mechanisms remain unclear. Herein, we used a unique brain-mimetic open system that continuously flows Aβ42 solution to analyze the initial aggregation and adsorptive nature of Aβ42 at physiological concentrations on the lipid membrane. The open system accelerated the adsorption and dimerization kinetics. Upon the addition of Aβ42, monomeric Aβ42 was dominant on the lipid bilayer surface in the closed system with no flow, whereas dimers and high-order oligomers were dominant in the open system. Closed and open systems exhibited different oligomerization kinetics, lipid-Aβ42 interactions, and diffusive properties of monomers and oligomers. These results indicate the specific adsorptive and diffusive nature of Aβ42 on the cell membrane. The open system may help in elucidating the molecular mechanisms underlying AD progression. more...

Wood modification using low molecular weight thermosetting resins improves the biological durability and dimensional stability of wood while avoiding increasingly regulated biocides. During the modification process, resin monomers diffuse from the cell lumen to the cell wall, occupying micropore spaces before in situ curing at 150 °C. This study investigated the mechanism of cell wall diffusion at multiple scales, comparing two test groups where diffusion was either facilitated or restricted. Antiswelling efficiency tests demonstrated improved dimensional stability when diffusion was facilitated. Differential scanning calorimetry showed that bound water was excluded more effectively from the cell wall if cell wall diffusion was enabled. Solid-state NMR spectroscopy ( 1 H MAS and 13 C MAS) with relaxation time analysis indicated that resin migrated to distinct locations within the cell wall, influenced by diffusion and drying conditions. These findings highlight how optimizing cell wall diffusion can significantly improve the performance of wood modification processes using thermosetting resins. more...

The formation of protein condensates (droplets) via liquid-liquid phase separation (LLPS) is a commonly observed phenomenon in vitro. Changing the environmental properties with cosolutes, molecular crowders, protein partners, temperature, pressure, etc. has been shown to favor or disfavor the formation of protein droplets by fine-tuning the water-water, water-protein, and protein-protein interactions. Therefore, these environmental properties and their spatiotemporal fine-tuning are likely to be important also in a cellular context at the existing protein expression levels. One of the key physicochemical properties of biomolecules impacted by molecular crowding is diffusion, which determines the viscoelastic behavior of the condensates. Here, we investigate the change in the rotational diffusion of γD-crystallin, undergoing LLPS in vitro in aqueous solutions in the absence and presence of cosolutes. We studied its rotational dynamics using molecular dynamics simulations (MD), electron paramagnetic resonance (EPR) spectroscopy, and fluorescence spectroscopy. MD simulations performed under dilute and crowded conditions show that the rotational diffusion of crystallin in water is retarded by 1 to 2 orders of magnitude in the condensed phase. To obtain the rotational dynamics in the dilute phase, we used fluorescence anisotropy and to extract the retardation factor in the condensed phase, we used spin-labeled γD-crystallin proteins as EPR viscosity nanoprobes. Aided by a viscosity nanoruler calibrated with solutions at increasing sucrose concentrations, we validated the rotational diffusion retardation predicted by MD simulations. This study underlines the predictive power of MD simulations and showcases the use of a sensitive EPR nanoprobe to extract the viscosity of biomolecular condensates. more...

Ultrasmall micro-light-emitting diodes (μLEDs), sized below 10 μm, are indispensable to create the next-generation augmented and virtual reality (AR/VR) devices. Their high brightness and low power consumption could not only enhance the user experience by providing vivid and lifelike visuals but also extend device longevity. However, a notable challenge emerges: a decrease in efficiency with a reduced size. This study casts light on this critical issue by investigating the lateral carrier diffusion in ion-implanted μLEDs. The implanted area restricts the carrier injection and defines the μLED size to diameters of 10, 5, and 2 μm without introduction of nonradiative recombination centers in the quantum well area. We observed a drop of efficiency for smaller devices, similar to the case of conventional μLEDs with etched sidewalls. Electroluminescence of μLEDs was studied using a Gaussian beam telescope to analyze light intensity profiles and hence the spatial carrier distribution within the active region of μLEDs. Lateral diffusion length was determined to be 11.2 μm at j = 1 A/cm 2 and decreased down to 2.4 μm for j = 1000 A/cm 2 . We explain the underlying mechanism behind the size-dependent efficiency observed in μLEDs, attributed to lateral carrier diffusion. more...

All-atom molecular dynamics simulations are powerful tools for studying cell membranes and their interactions with proteins and other molecules. However, these processes occur on time scales determined by the diffusion rate of phospholipids, which are challenging to achieve in all-atom models. Here, we present a new all-atom model that accelerates lipid diffusion by splitting phospholipid molecules into head and tail groups. The bilayer structure is maintained by using external lateral potentials, which compensate for the lipid split. This split model enhances lateral lipid diffusion more than ten times, allowing faster and cheaper equilibration of large systems with different phospholipid types. The current model has been tested on membranes containing PSM, POPC, POPS, POPE, POPA, and cholesterol. We have also evaluated the interaction of the split model membranes with the Disheveled DEP domain and amphiphilic helix motif of the transcriptional repressor Opi1 as representative of peripheral proteins as well as the dimeric fragment of the epidermal growth factor receptor transmembrane domain and the Human A2A Adenosine of G protein-coupled receptors as representative of transmembrane proteins. The split model can predict the interaction sites of proteins and their preferred phospholipid type. Thus, the model could be used to identify lipid binding sites and equilibrate large membranes at an affordable computational cost. more...

Language modeling applied to biological data has significantly advanced the prediction of membrane penetration for small-molecule drugs and natural peptides. However, accurately predicting membrane diffusion for peptides with pharmacologically relevant modifications remains a substantial challenge. Here, we introduce PeptideCLM, a peptide-focused chemical language model capable of encoding peptides with chemical modifications, unnatural or noncanonical amino acids, and cyclizations. We assess this model by predicting membrane diffusion of cyclic peptides, demonstrating greater predictive power than existing chemical language models. Our model is versatile and can be extended beyond membrane diffusion predictions to other target values. Its advantages include the ability to model macromolecules using chemical string notation, a largely unexplored domain, and a simple, flexible architecture that allows for adaptation to any peptide or other macromolecule data set. more...

Hydrogen peroxide (H 2 O 2 )-based advanced oxidation technology has emerged as a cost-effective and green solution for tackling soil pollution. Given the highly heterogeneous nature of soil, the effectiveness of H 2 O 2 remediation is significantly influenced by its diffusion distance in soils. However, the dynamics of H 2 O 2 diffusion and its effective range remain largely unexplored, primarily due to the lack of analytical methods for mapping H 2 O 2 in soils. This study introduces a precipitation-based fluorescent probe (PFP) method for in situ, high-resolution (micrometer scale) mapping of H 2 O 2 diffusion in soils. Using the PFP method, we visualized real-time H 2 O 2 diffusion in various types of soils, revealing distinct diffusion patterns with rates ranging from 0.011 to >0.56 mm min -1 . The observed differences in diffusion rates are associated with soil permeability. Additionally, soils exhibited a wide range of diffusion distances, from 0.22 to >11 mm in 20 min. Soil's reactivity for H 2 O 2 decomposition, a previously overlooked factor, is critical in determining the diffusion distance of H 2 O 2 . We further demonstrate that the efficacy of H 2 O 2 diffusion in soils is a pivotal factor in controlling pollutant degradation and soil remediation efficiency. These findings enhance our understanding of reagent diffusion processes in soil remediation, informing the optimization of more efficient soil remediation strategies. more...

Molecular oxygen (O 2 ) is essential for life, and continuous effort has been made to understand its pathways in cellular respiration with all-atom (AA) molecular dynamics (MD) simulations of, e.g., membrane permeation or binding to proteins. To reach larger length scales with models, such as curved membranes in mitochondria or caveolae, coarse-grained (CG) simulations could be used at much lower computational cost than AA simulations. Yet a CG model for O 2 is lacking. In this work, a CG model for O 2 is therefore carefully selected from the Martini 3 force field based on criteria including size, zero charge, nonpolarity, solubility in nonpolar organic solvents, and partitioning in a phospholipid membrane. This chosen CG model for O 2 (TC3 bead) is then further evaluated through the calculation of its diffusion constant in water and hexadecane, its permeability rate across pure phospholipid- and cholesterol-containing membranes, and its binding to the T4 lysozyme L99A protein. Our CG model shows semiquantitative agreement between CG diffusivity and permeation rates with the corresponding AA values and available experimental data. Additionally, it captures the binding to hydrophobic cavities of the protein, aligning well with the AA simulation of the same system. Thus, the results show that our O 2 model approximates the behavior observed in the AA simulations. The CG O 2 model is compatible with the widely used multifunctional Martini 3 force field for biological simulations, which will allow for the simulation of large biomolecular systems involved in O 2 's transport in the body. more...

The design of drug molecules is a critical stage in the drug discovery process. The structure-based drug design has long played an important role in efficient development. Significant progress has been made in recent years in the generation of 3D molecules via deep generation models. However, while many existing models have succeeded in incorporating structural information on target proteins, they have not been able to address important interactions between protein and drug molecules, especially hydrogen bonds. In this study, we propose DiffInt as a novel structure-based approach that explicitly addresses interactions. The model naturally incorporates hydrogen bonds between protein and ligand molecules by treating them as pseudoparticles. The experimental results show that DiffInt reproduces hydrogen bonds, and the hydrogen binding energies significantly outperform those of existing models. To facilitate the use of our tool for generating new drug molecules based on any protein's three-dimensional structure, we have made the source code and trained model available on GitHub (https://github.com/sekijima-lab/DiffInt) under the MIT license, with the execution environment provided on Google Colab. more...

Diffusion of mobile charge carriers, such as ferredoxin and plastocyanin, often constitutes a rate-determining step in photosynthetic energy conversion. The diffusion time scales typically exceed that of other primary bioenergetic processes and remain beyond the reach of direct simulation at the molecular level. We characterize the diffusive kinetics of ferredoxin and plastocyanin upon the photosystem I-rich domain of Prochlorococcus , the most abundant phototroph on Earth by mass. A modeling approach for ferredoxin and plastocyanin diffusion is presented that uses ensembles of coarse-grained molecular dynamics simulations in Martini 2.2P with GROMACS 2021.2. The simulation ensembles are used to construct the diffusion coefficient and drift for ferredoxin and plastocyanin as spatial functions in the photosystem I domain of the MIT9313 ecotype. Four separate models are constructed, corresponding to ferredoxin and plastocyanin in reduced and oxidized states. A single scaling constant of 0.7 is found to be sufficient to adjust the diffusion coefficient obtained from the Martini simulation ensemble to match the in vitro values for both ferredoxin and plastocyanin. A comparison of Martini versions (2.2P, 2.2, 3) is presented with respect to diffusion scaling. The diffusion coefficient and drift together quantify the inhomogeneity of diffusive behavior. Notably, a funnel-like convergence toward the corresponding putative binding positions is observed for both ferredoxin and plastocyanin, even without such a priori foreknowledge supplied in the simulation protocol. The approach presented here is of relevance for studying diffusion kinetics in photosynthetic and other bioenergetic processes. more...

As injected drugs finally diffuse to the target cells, a quantitative understanding of the diffusion behavior of drug molecules or drug carriers is essential for the determination of their efficacy or optimal doses. Here, we propose a method for determining the diffusivity (D, diffusion coefficient) of drug carriers in tissue-mimicking collagen in the lab-on-a-chip (LOC) platform and predict their spatiotemporal distribution using the calculated D. By controlling the concentrations of fluorescent mesoporous silica nanoparticles (MSNs) in each channel, the diffusion of fluorescent MSNs was induced and fluorescence gradients in collagen were produced and captured as images. The D of the MSNs by size was obtained by fitting the fluorescence profiles to the solution of Fick's second law. The D of MSNs varied by size from 2.98 × 10–10 m2/s (MSNs of 10 nm) to 1.14 × 10–11 m2/s (MSNs of 1 μm). The spatiotemporal profiles of MSNs were calculated using the obtained D, and it was demonstrated that the concentration of MSNs with a size >200 nm at 100 μm from the gel–liquid interface will remain <50% of that in the vessel-mimicking channel even after 3 h. As the analysis and prediction procedures based on fluorescence profile image processing and a least-squares fit to the solution are relatively simple, our results can be extended to various studies to narrow the gap between in vitro tests and animal experiments in drug or particle transport research through the calculation of the diffusion coefficient of drug candidates before animal experiments and might replace some parts of animal experiments of drug delivery studies. [ABSTRACT FROM AUTHOR] more...

The recent COVID-19 pandemic and the prospect of future global pandemics highlight the long-standing need to passively eliminate viruses and bacteria on surfaces. Conventional antimicrobial surfaces and coatings are typically constrained by a trade-off between antimicrobial efficacy and physical durability. A biphasic polyurethane coating has been developed that breaks this trade-off by incorporating a durability-imparting polycarbonate (PC) discrete phase with a continuous poly(ethylene glycol) (PEG) transport phase that absorbs, stores, and releases antimicrobial active compounds for extended microbial inactivation. The biphasic polymer was shown to absorb carboxylic acid and quaternary ammonium antimicrobial active compounds, maintained their levels after five years of simulated cleaning, and inactivated up to 99.99% of Human Coronavirus 229E and Influenza A H1N1. Furthermore, the levels of antimicrobial active compounds on the biphasic coating could be augmented by cleaning the substrate with a disinfectant. The practicality of biphasic coatings for automotive and commercial aerospace environments was demonstrated by showing control of hardness and stain resistance through biphasic composition, showing environmental durability through heat, humidity, and light exposure, and passing flammability protocols. more...

Understanding and predicting the diverse conformational states of membrane proteins is essential for elucidating their biological functions. Despite advancements in computational methods, accurately capturing these complex structural changes remains a significant challenge. Here, we introduce a computational approach to generate diverse and biologically relevant conformations of membrane proteins using a conditional diffusion model. Our approach integrates forward and backward diffusion processes, incorporating state classifiers and additional conditioners to control the generation gradient of conformational states. We specifically targeted the P-type ATPases, a critical family of membrane transporters, and constructed a comprehensive data set through a combination of experimental structures and molecular dynamics simulations. Our model, incorporating a graph neural network with specialized membrane constraints, demonstrates exceptional accuracy in generating a wide range of P-type ATPase conformations associated with different functional states. This approach represents a meaningful step forward in the computational generation of membrane protein conformations using AI and holds promise for studying the dynamics of other membrane proteins. more...

Macromolecular crowding in the cellular cytoplasm can potentially impact diffusion rates of proteins, their intrinsic structural stability, binding of proteins to their corresponding partners as well as biomolecular organization and phase separation. While such intracellular crowding can have a large impact on biomolecular structure and function, the molecular mechanisms and driving forces that determine the effect of crowding on dynamics and conformations of macromolecules are so far not well understood. At a molecular level, computational methods can provide a unique lens to investigate the effect of macromolecular crowding on biomolecular behavior, providing us with a resolution that is challenging to reach with experimental techniques alone. In this review, we focus on the various physics-based and data-driven computational methods developed in the past few years to investigate macromolecular crowding and intracellular protein condensation. We review recent progress in modeling and simulation of biomolecular systems of varying sizes, ranging from single protein molecules to the entire cellular cytoplasm. We further discuss the effects of macromolecular crowding on different phenomena, such as diffusion, protein-ligand binding, and mechanical and viscoelastic properties, such as surface tension of condensates. Finally, we discuss some of the outstanding challenges that we anticipate the community addressing in the next few years in order to investigate biological phenomena in model cellular environments by reproducing in vivo conditions as accurately as possible. more...

Nucleic acid mimics (NAMs) have demonstrated high potential as antibacterial drugs. However, very few studies have assessed their possible diffusion across the bacterial envelope. In this work, we studied NAMs' diffusion in lipid bilayer systems that mimic the bacterial outer membrane using molecular dynamics (MD) simulations. Additionally, we examined the interactions of a NAM sequence with lipid membranes and ascertained the partition constants ( K p -glycero-3-phospho-(1'-rac-glycerol) (POPG) phospholipids. The parametrization protocol followed was validated against literature data and demonstrated the reliability of our approach for simulating NAM sequences. Investigation into the interaction of the sequences with zwitterionic and anionic membranes revealed a preference for hydrogen bond formation with the anionic model over the zwitterionic one. Additionally, potential of mean force (PMF) calculations unveiled a lower free energy barrier for translocation across the zwitterionic bilayer model. Contrarily, the partition constants derived suggested a slightly higher partitioning within the anionic membrane, emphasizing a nuanced interplay of factors. Finally, spectroscopic partition measurements with liposomes presented challenges in quantifying the partition of NAMs due to minimal signal variations. However, a tendency for quenching in anionic vesicles suggested a potential, albeit small, partitioning effect that warrants further investigation. In summary, our study revealed that NAMs will not, in principle, be able to cross an intact bacterial outer membrane by passive diffusion.sn -glycero-3-phospho-(1'-rac-glycerol) (POPG) phospholipids. The parametrization protocol followed was validated against literature data and demonstrated the reliability of our approach for simulating NAM sequences. Investigation into the interaction of the sequences with zwitterionic and anionic membranes revealed a preference for hydrogen bond formation with the anionic model over the zwitterionic one. Additionally, potential of mean force (PMF) calculations unveiled a lower free energy barrier for translocation across the zwitterionic bilayer model. Contrarily, the partition constants derived suggested a slightly higher partitioning within the anionic membrane, emphasizing a nuanced interplay of factors. Finally, spectroscopic partition measurements with liposomes presented challenges in quantifying the partition of NAMs due to minimal signal variations. However, a tendency for quenching in anionic vesicles suggested a potential, albeit small, partitioning effect that warrants further investigation. In summary, our study revealed that NAMs will not, in principle, be able to cross an intact bacterial outer membrane by passive diffusion. more...

Liquid-liquid phase separation (LLPS) constitutes a crucial phenomenon in biological self-organization, not only intervening in the formation of membraneless organelles but also triggering pathological protein aggregation, which is a hallmark in neurodegenerative diseases. Employing incoherent quasi-elastic neutron spectroscopy (QENS), we examine the short-time self-diffusion of a model protein undergoing LLPS as a function of phase splitting and temperature to access information on the nanosecond hydrodynamic response to the cluster formation both within and outside the LLPS regime. We investigate the samples as they dissociate into microdroplets of a dense protein phase dispersed in a dilute phase as well as the separated dense and dilute phases obtained from centrifugation. By interpreting the QENS results in terms of the local concentrations in the two phases determined by UV-vis spectroscopy, we hypothesize that the short-time transient protein cluster size distribution is conserved at the transition point while the local volume fractions separate. more...

Spherical biosamples such as immunobeads, cells, and cell aggregates have been widely used in bioapplications. The bioactivity of individual spherical biosamples in highly sensitive assays and individual analyses must be evaluated in a high-throughput manner. Electrochemiluminescence (ECL) imaging was recently proposed for the high-throughput analysis of diffusive molecules from spherical biosamples. ECL imaging involves the placing of spherical biosamples on a flat electrode filled with a solution. The biosamples produce (or consume) biological/chemical molecules such as H 2 O 2 and O 2 , which diffuse to form a concentration gradient at the electrode. The ECL signals from the molecules are then measured to obtain the concentration profile, which allows the flux to be estimated, from which their bioactivities can be successfully calculated. However, no studies on theoretical approaches for spherical biosamples on flat surfaces have been conducted using ECL imaging. Therefore, this paper presents a novel spherical diffusion theory for spherical biosamples on a flat surface, which is based on the common spherical diffusion theory and was designated as the extended spherical diffusion theory. First, the concepts behind this theory are discussed. The theory is then validated by comparison with a simulated analysis. The resulting equation successfully expresses the concentration profile for the entire area. The glucose oxidase activity in the hydrogel beads is subsequently visualized using ECL imaging, and the enzymatic product flux is calculated using the proof-of-concept theory. Finally, a time-dependent simulation is conducted to fill the gap between the theoretical and experimental data. This paper presents novel guidelines for this analysis. more...

The viscosity and diffusion properties of crowded protein systems were investigated with molecular dynamics simulations of SH3 mixtures with different crowders, and results were compared with experimental data. The simulations accurately reproduced experimental trends across a wide range of protein concentrations, including highly crowded environments up to 300 g/L. Notably, viscosity increased with crowding but varied little between different crowder types, while diffusion rates were significantly reduced depending on protein-protein interaction strength. Analysis using the Stokes-Einstein relation indicated that the reduction in diffusion exceeded what was expected from viscosity changes alone, with the additional slow-down attributable to transient cluster formation driven by weakly attractive interactions. Contact kinetics analysis further revealed that longer-lived interactions contributed more significantly to reduced diffusion rates than short-lived interactions. This study also highlights the accuracy of current computational methodologies for capturing the dynamics of proteins in highly concentrated solutions and provides insights into the molecular mechanisms affecting protein mobility in crowded environments. more...

Vapor phase infiltration (VPI) facilitates the incorporation of inorganic components into organic polymers, emerging as an effective technique for fabricating organic-inorganic hybrid materials. However, the complexity of diffusion behavior during the VPI process presents challenges in studying diffusion kinetics, particularly for highly reactive precursor-polymer systems such as trimethylaluminum (TMA) and poly(ethylene oxide) (PEO). In this study, we investigate the VPI process of TMA in PEO using in situ quartz crystal microgravimetry (QCM), which enables measurement of diffusion behavior and kinetics with high precision due to its high temporal resolution. Our results indicate that the VPI process consists of two main regions: a rapid diffusion process, corresponding to the initial penetration of the precursor into the film, followed by a slower relaxation process, attributed to the ongoing chemical reaction. The equivalent diffusion coefficient ( D e ) was estimated to be on the order of 10 -9 cm 2 /s and decreased with increasing aluminum content. Using energy application as a proof-of-concept, when optimized, VPI-modified PEO films were successfully utilized as solid polymer electrolytes (SPEs) for lithium metal batteries (LMBs), showcasing superior performance in mitigating lithium dendrite growth. This study offers valuable insights into the VPI process for PEO-TMA systems and provides guidance for optimizing VPI conditions to enhance the performance of advanced materials. more...

Accurate sampling of protein conformations is pivotal for advances in biology and medicine. Although there has been tremendous progress in protein structure prediction in recent years due to deep learning, models that can predict the different stable conformations of proteins with high accuracy and structural validity are still lacking. Here, we introduce UFConf, a cutting-edge approach designed for robust sampling of diverse protein conformations based solely on amino acid sequences. This method transforms AlphaFold2 into a diffusion model by implementing a conformation-based diffusion process and adapting the architecture to process diffused inputs effectively. To counteract the inherent conformational bias in the Protein Data Bank, we developed a novel hierarchical reweighting protocol based on structural clustering. Our evaluations demonstrate that UFConf outperforms existing methods in terms of successful sampling and structural validity. The comparisons with long-time molecular dynamics show that UFConf can overcome the energy barrier existing in molecular dynamics simulations and perform more efficient sampling. Furthermore, We showcase UFConf's utility in drug discovery through its application in neural protein-ligand docking. In a blind test, it accurately predicted a novel protein-ligand complex, underscoring its potential to impact real-world biological research. Additionally, we present other modes of sampling using UFConf, including partial sampling with fixed motif, Langevin dynamics, and structural interpolation. more...

Carbon capture and storage (CCS) in subsurface reservoirs represents a highly promising and viable strategy for mitigating global carbon emissions. In the context of CCS implementation, it is particularly crucial to understand the complex molecular diffusive and adsorptive behaviors of anthropogenic carbon dioxide (CO 2 ) in the subsurface at the nanoscale. Yet, conventional molecular models typically represent only single-slit pores and overlook the complexity of interconnected nanopores. In this work, finite kaolinite lamellar assemblages with abundant nanopores ( r < 2 nm) were used. Molecular dynamics simulations were performed to quantify the spatial distribution correlations, adsorption preference, diffusivity, and residence time of the CO 2 molecules in kaolinite nanopores. The movement of the CO 2 molecules primarily occurs in the central and proximity regions of the siloxane surfaces, progressing from larger to smaller nanopores. CO 2 prefers smaller nanopores over larger ones. The diffusion coefficients increase, while residence times decrease, with the pore size increasing, differing from typical slit-pore models due to the pore shape and interconnectivity. The perspectives in this study, which would be challenging in conventional slit-pore models, will facilitate our comprehension of the CO 2 molecular behaviors in the complex subsurface clay sediments for developing quantitative estimation techniques throughout the CCS project durations. more...

Overexpression and remodeling of the extracellular matrix (ECM) in cancer and other diseases may significantly reduce the ability of nanoparticles to reach target sites, preventing the effective delivery of therapeutic cargo. Here, we evaluate how tissue-specific properties of the ECM affect nanoparticle diffusion using fluorescence video microscopy and cellular uptake via flow cytometry. In addition, we determined how poly(ethylene glycol) (PEG) chain length and branching influence the ability of PEGylated nanoparticles to overcome the ECM barrier from different tissues. We found that purified collagen, in the absence of other ECM proteins and polysaccharides, presented a greater barrier to nanoparticle diffusion compared to the decellularized ECM from the liver, lung, and small intestine submucosa. Nanoparticles with dense PEG coatings achieved up to ∼2000-fold enhancements in diffusion rate and cellular uptake up to ∼5-fold greater than non-PEGylated nanoparticles in the presence of the ECM. We also found nanoparticle mobility in the ECM varied significantly between tissue types, and the optimal nanoparticle PEGylation strategy to enhance ECM penetration was strongly dependent on ECM concentration. Overall, our data support the use of low molecular weight PEG coatings which provide an optimal balance of nanoparticle penetration through the ECM and uptake in target cells. However, tissue-specific enhancements in ECM penetration and cellular uptake were observed for nanoparticles bearing a branched PEG coating. These studies provide insights into tissue specific ECM barrier functions, which can facilitate the design of nanoparticles that effectively transport through target tissues, improving their therapeutic efficacy. more...

Noninterface-active polysaccharides can acquire better emulsifying properties through microgelation, yet optimizing their emulsifying performance remains a significant challenge. This study introduces a novel approach to enhance the emulsifying performance of polysaccharide microgels by leveraging the cross-interfacial diffusion of polyphenols, which promotes the interfacial adsorption of microgels. Tannic acid (TA) was predispersed in oil phases and subsequently emulsified with agarose microgel (AM) suspensions, and the impacts of TA diffusion on the emulsifying performance of AMs was investigated. In addition, the transmittance profiles of oil-water biphasic systems were found to innovatively indicate the cross-interfacial diffusion of TA and the interfacial adsorption of AMs. The current results suggest that an appropriate level of TA incorporation can benefit the emulsifying performance of AMs, correlating with decreased droplet sizes and improved physical stability of the emulsion. However, excessive TA might trigger the clustering of AMs before they reach the interfacial layer, adversely affecting the emulsion stability. In conclusion, the cross-interfacial diffusion of polyphenols offers a promising strategy to overcome the stability challenges encountered in polysaccharide microgel-stabilized emulsions. more...

Tracking nanoparticle movement is highly desirable in many scientific areas, and various imaging methods have been employed to achieve this goal. Interferometric scattering (iSCAT) microscopy has been particularly successful in combining very high spatial and temporal resolution for tracking small nanoparticles in all three dimensions. However, previous works have been limited to an axial range of only a few hundred nanometers. Here, we present a robust and efficient measurement and analysis strategy for three-dimensional tracking of nanoparticles at high speed and with nanometer precision. After discussing the principle of our approach using synthetic data, we showcase the performance of the method by tracking gold nanoparticles with diameters ranging from 10 to 80 nm in water, demonstrating an axial tracking range from 4 μm for the smallest particles up to over 30 μm for the larger ones. We point out the limitations and robustness of our system across various noise levels and discuss its promise for applications in cell biology and material science, where the three-dimensional motion of nanoparticles in complex media is of interest. more...

The particle drifting effect, where nanosized colloidal drug particles overcome the diffusional resistance of the aqueous boundary layer adjacent to the intestinal wall and increase drug absorption rates, is drawing increasing attention in pharmaceutical research. However, mechanistic understanding and accurate prediction of the particle drifting effect remain lacking. In this study, we systematically evaluated the extent of the particle drifting effect affected by drug and colloidal properties, including the size, number, and type of the moving species using biphasic diffusion experiments combined with computational fluid dynamics simulations and mass transport analyses. The results showed that the particle drifting effect is a sequential reaction of particle dissolution/dissociation in the diffusional boundary layer, followed by absorption of the free drug. Therefore, factors affecting the rate-limiting step, which can be either process or both under different circumstances, alter the particle drifting effect. Experimental results also agree with the theory that the particle dissolution rate is dependent on particle size, concentration, and drug solubility. In addition, rapid bile micelle dissociation and bile salt absorption facilitated drug absorption by the particle drifting effect. Our findings explain the highly dynamic nature of the particle drifting effect and will contribute to rational formulation development and better bioavailability prediction for formulations containing colloidal particles. more...

The mechanism of active pharmaceutical ingredient (API) mobility during release in microparticle formulation was investigated using periodically structured illumination combined with spatial Fourier transform fluorescence recovery after photobleaching (FT-FRAP). FT-FRAP applies structured photobleaching across a given field of view, allowing for the monitoring of molecular mobility through the analysis of recovery patterns in the FT domain. Encoding molecular mobility in the FT domain offers several advantages, including improved signal-to-noise ratio, simplified mathematical calculations, reduced sampling requirements, compatibility with multiphoton microscopy for imaging API molecules within the formulations, and the ability to distinguish between exchange and diffusion processes. To prepare microparticles for FT-FRAP analysis, a homogeneous mixture of dipyridamole and pH-independent methyl methacrylate polymer (Eudragit RS and RL) was processed using laminar jet breakup induced by vibration in a frequency-driven encapsulator. The encapsulated microparticles were characterized based on particle size distribution, encapsulation efficiency, batch size, and morphology. Utilizing FT-FRAP, the internal diffusion and exchange molecular mobility within RL and RS microparticles were discriminated and quantified. Theoretical modeling of exchange- and diffusion-controlled release revealed that both RL and RS microparticles exhibited similar exchange decay rates, but RL displayed a significantly higher diffusion coefficient. This difference in diffusion within RL and RS microparticles was correlated with their macroscopic dissolution performance. more...

Extracellular vesicles (EVs) are a diverse population of membrane structures produced and released by cells into the extracellular space for the intercellular trafficking of cargo molecules. They are implicated in various biological processes, including angiogenesis, immunomodulation, and cancer cell signaling. While much research has focused on their biogenesis or their effects on recipient cells, less is understood about how EVs are capable of traversing diverse tissue environments and crossing biological barriers. Their interactions with extracellular matrix components are of particular interest, as such interactions govern diffusivity and mobility, providing a potential basis for organotropism. To start to untangle how EV-matrix interactions affect diffusivity, we use high speed epifluorescence microscopy, single particle tracking, and confocal reflectance microscopy to analyze particle mobility and localization in extracellular matrix-mimicking hydrogels composed of collagen I. EVs are compared with synthetic liposomes and extruded plasma membrane vesicles to better understand the importance of membrane composition on these interactions. By treating EVs with trypsin to digest surface proteins, we determine that proteins are primarily responsible for EV immobilization in collagen I hydrogels. We next use a synthetic peptide competitive inhibitor to narrow down the identity of the proteins involved to argynylglycylaspartic acid (RGD) motif-binding integrins, which interact with unincorporated or denatured nonfibrillar collagen. Moreover, the effect of integrin inhibition with RGD peptides has strong implications for the use of RGD-peptide-based drugs to treat certain cancers, as integrin inhibition appears to increase EV mobility, improving their ability to infiltrate tissue-like environments. more...

Diffusion is one of the most fundamental concepts in materials science, playing a pivotal role in materials synthesis, forming, and degradation. Of particular importance is solid state interdiffusion of metals which defines the usable parameter space for material combinations in the form of alloys. This parameter space can be explored on the macroscopic scale by using diffusion couples. However, this method reaches its limit when going to low temperatures, small scales, and when testing ultrathin diffusion barriers. Therefore, this work transfers the principle of the diffusion couples to small scales by using core-shell nanowires and in situ heating. This allows us to delve into the interdiffusion dynamics of copper and gold, revealing the interplay between diffusion and the disorder-order phase transition. Our in situ TEM experiments in combination with chemical mapping reveal the interdiffusion coefficients of Cu and Au at low temperatures and highlight the impact of ordering processes on the diffusion behavior. The formation of ordered domains within the solid-solution is examined using high-resolution imaging and nanodiffraction including strain mapping. In addition, we examine the effectiveness of ultrathin Al 2 O 3 barrier layers to control interdiffusion of the diffusion couple. Our findings indicate that a 5 nm thick layer serves as an efficient diffusion barrier. This research provides valuable insights into the interdiffusion behavior of Cu and Au on the nanoscale, offering potential applications in the development of miniaturized integrated circuits and nanodevices. more...

Isothermal nucleic acid amplification tests, NAATs, such as reverse transcription-loop-mediated isothermal amplification (RT-LAMP), offer promising capabilities to perform real-time semiquantitative detection of viral pathogens. These tests provide rapid results, utilize simple instrumentation for single-temperature reactions, support efficient user workflows, and are suitable for field use. Herein, we present a novel and robust method for real-time monitoring of HIV-1 RNA RT-LAMP utilizing a novel implementation of particle diffusometry (PD), a diffusivity quantification technique using fluorescent particles, to quantify viral concentration in nuclease-free water. We monitor changes in particle diffusion dynamics of 400 nm fluorescently labeled particles throughout the RT-LAMP of HIV-1 RNA in nuclease-free water, enabling measurement within 20 min and detection of concentrations as low as 25 virus particles per μL. Moreover, in a single-blind study, we demonstrate semiquantitative detection by accurately determining the initial concentration of an unknown HIV-1 RNA within a 10% absolute error margin. These results highlight the potential of real-time PD readout for quantifying HIV-1 RNA via RT-LAMP, offering promise for viral load monitoring of HIV and other chronic infections. more...

The detection of noble gas radioisotopes following a suspected underground nuclear explosion is the surest indicator that nuclear detonation has occurred. However, the accurate interpretation and attribution of radioisotopic signatures is only possible with a complete understanding of transport processes occurring between the nuclear cavity and surface. In the far-field, diffusive forces contributing to gas transport are impacted by temperature gradients and subsurface lithology. In the current study, we investigate diffusive transport of xenon (Xe), krypton (Kr), and sulfur hexafluoride (SF 6 ) through intact Bandelier tuff at elevated temperatures using a newly developed high temperature diffusion cell. Diffusion coefficients determined using Finite Element Heat and Mass transfer code simulations and the Parameter ESTimation tool range from 2.6-3.1 × 10 -6 m 2 /s at 20 °C, 3.4-5.1 × 10 -6 m 2 /s at 40 °C, and 4.3-7.0 × 10 -6 m 2 /s at 70 °C. Sorption was found to be an important transport mechanism at ambient temperatures (20 °C). Most critically, our study shows that empirical porosity-based diffusion estimates for these gases through tuff captured neither the magnitude nor trends relative to a nonsorbing sandstone. These new insights highlight the importance of experimental transport investigations and will be used to improve models for subsurface gas propagation relevant to proliferation detection and environmental contamination. more...

Biologic drugs have emerged as a rapidly expanding and important modality, offering promising therapeutic solutions by interacting with previously "undruggable" targets, thus significantly expanding the range of modern pharmaceutical applications. However, the inherent complexity of these drugs also introduces liabilities and poses challenges in their development, necessitating efficient screening methods to evaluate the structural stability and behavior. Although nuclear magnetic resonance (NMR) spectroscopy is well-suited for detecting weak interactions, changes in dynamics, high-order structure, and association states of macromolecules in fully formulated samples, the inherent low sensitivity limits its utility as a fast screening and characterization tool. In this study, we present two fast pulsing NMR experiments, namely the band-Selective Optimized Flip-Angle Internally encoded Relaxation (SOFAIR) and the band-Selective Optimized Flip-angle Internally encoded Translational diffusion (SOFIT)), which enable rapid and reliable measurements of transverse relaxation rates and diffusion coefficients with more than 10-fold higher sensitivity compared to commonly used methods, like Carr-Purcell-Meiboom-Gill and diffusion-ordered spectroscopy, allowing the rapid assessment of biologics even at low concentrations. We demonstrated the effectiveness and versatility of these experiments by evaluating several examples, including thermally stressed proteins, proteins at different concentrations, and a therapeutic protein in various formulations. We anticipate that these novel approaches will greatly facilitate the analysis and characterization of biologics during drug discovery. more...

Diffusion models have emerged as powerful tools for molecular generation, particularly in the context of 3D molecular structures. Inspired by nonequilibrium statistical physics, these models can generate 3D molecular structures with specific properties or requirements crucial to drug discovery. Diffusion models were particularly successful at learning the complex probability distributions of 3D molecular geometries and their corresponding chemical and physical properties through forward and reverse diffusion processes. This review focuses on the technical implementation of diffusion models tailored for 3D molecular generation. It compares the performance, evaluation methods, and implementation details of various diffusion models used for molecular generation tasks. We cover strategies for atom and bond representation, architectures of reverse diffusion denoising networks, and challenges associated with generating stable 3D molecular structures. This review also explores the applications of diffusion models in de novo drug design and related areas of computational chemistry, such as structure-based drug design, including target-specific molecular generation, molecular docking, and molecular dynamics of protein-ligand complexes. We also cover conditional generation on physical properties, conformation generation, and fragment-based drug design. By summarizing the state-of-the-art diffusion models for 3D molecular generation, this review sheds light on their role in advancing drug discovery and their current limitations. more...

The secretion rate of albumin is a key indicator of function in liver tissue models used for hepatotoxicity and pharmacokinetic testing. However, it is not generally clear how to determine molecular secretion rates from measurements of the molecular concentration in supernatant media. Here, we develop computational and analytical models of molecular transport in an experimental system that enable determination of albumin secretion rates based on measurements of albumin concentration in supernatant media. The experimental system is a 3D-bioprinted human liver tissue construct embedded in a 3D culture environment made from packed microgel particles swollen in liquid growth media. The mathematical models reveal that the range of albumin synthesis rates necessary to match experimentally measured albumin concentrations corresponds to reaction-limited conditions, where a steady state of albumin spatial distribution is rapidly reached between media exchanges. Our results show that temporally resolved synthesis rates can be inferred from serial concentration measurements of collected supernatant media. This link is critical to confidently assessing in vitro tissue performance in applications where critical quality attributes must be quantified, like in drug development and screening. more...