European Biophysics Journal

Monte Carlo neutron ray-tracing simulations of time-of-flight (TOF)-Laue neutron macromolecular crystal diffraction (n-MX) using the McStas software package were done for the upcoming NMX Macromolecular Diffractometer at the European Spallation Source. Splitting neutron rays that arrive at the crystal lead to dramatic improvements in event formation with minimal computational overhead. The simulated event probability data was sampled using a new single-pass weighted reservoir sampling method, and processed like real n-MX data using DIALS. The effects of air and beamstop scatter on simulated data was investigated. SynopsisMonte Carlo simulations of neutron protein diffraction experiments provide useful data that models instrumental components that interact with neutrons, as well as the crystal diffraction itself. These data can be applied to instrument development, such as the commissioning of the NMX Macromolecular Diffractometer at ESS.

IntroductionTrabecular bone exhibits brittle behaviour governed by microscale deformation and damage processes, yet quantitative characterisation of crack progression remains challenging because classical fracture mechanics approaches do not apply to architecturally discontinuous porous tissues. This study evaluates whether synchrotron X-ray computed tomography (XCT) combined with digital volume correlation (DVC) can provide a practical experimental approach for quantifying crack opening behaviour in human trabecular bone. MethodSemicylindrical specimens harvested from femoral heads of hip-fracture donors (n = 5) and non-fracture controls (n = 5) underwent stepwise three-point-bending during XCT imaging. Full-field displacement maps enabled direct measurement of crack mouth opening displacement (CMOD), crack length (a), and their ratio, CMOD/a, used here as a geometry-normalised comparative descriptor of brittle response. Automated crack segmentation using phase-congruency crack detection (PCCD) was compared against manual measurements. ResultsXCT-DVC successfully resolved three-dimensional displacement discontinuities during crack initiation and propagation in all specimens. Hip-fracture donors exhibited significantly lower critical crack-opening ratios (CMOD/a)* than Controls (0.31 vs 0.47; p = 0.008) and reached mechanical instability at lower applied loads, consistent with a more brittle structural response under this test configuration. Despite these differences, total crack extension ({Delta}a*) was similar between groups. Automated crack tracking using phase-congruency-based segmentation showed excellent agreement with manual measurements (r{superscript 2} = 0.98), confirming reliable extraction of crack geometry from DVC displacement fields. DiscussionThese results indicate that XCT-DVC can provide a practical approach for quantifying crack-opening behaviour in trabecular bone when classical fracture-mechanics parameters are not applicable in anatomically constrained specimens. The reduced critical crack-opening ratios and earlier instability observed in Hip-fracture donors are consistent with a more brittle comparative mechanical response that is not captured by crack extension alone. The strong agreement between automated and manual crack measurements further supports displacement-based descriptors as reliable comparative indicators of brittle behaviour in porous, architecturally discontinuous tissues. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/714043v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@31c5d7org.highwire.dtl.DTLVardef@1b3d9a4org.highwire.dtl.DTLVardef@95df7borg.highwire.dtl.DTLVardef@1834216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

Understanding how cells migrate through confined environments is crucial for elucidating fundamental biological processes, including cancer invasion, immune surveillance, and tissue morphogenesis. The nucleus, as the largest and stiffest cellular organelle, often limits cellular deformability, making it a key factor in migration through narrow pores or highly constrained spaces. In this work, we introduce a geometric surface partial differential equation (GS-PDE) model in which the cell plasma membrane and nuclear envelope are described as evolving energetic closed surfaces governed by force-balance equations. We replicate the results of a biophysical experiment, where a microfluidic device is used to impose compressive stresses on cells by driving them through narrow microchannels under a controlled pressure gradient. The model is validated by reproducing cell entry into the microchannels. A parametric sensitivity analysis highlights the dominant influence of specific parameters, whose accurate estimation is essential for faithfully capturing the experimental setup. We found that surface tension and confinement geometry emerge as key determinants of translocation efficiency. Although tailored to this specific setup for validation purposes, the framework is sufficiently general to be applied to a broad range of cell mechanics scenarios, providing a robust and flexible tool for investigating the interplay between cell mechanics and confinement. It also offers a solid foundation for future extensions integrating more complex biochemical processes such as active confined migration.

Extracellular matrix (ECM) proteins assemble to form a heterogeneous connective scaffold that supports cells. Physical interactions between cells and the matrix regulate cellular behaviors and influence subsequent tissue construction. However, there is a lack of fundamental understanding regarding the contributions of individual native ECM proteins to the matrix. This gap arises from the need for nanoscopic characterization, which operates on a much smaller length scale than typical assessments in cell and tissue cultures, as well as in tissue reconstruction and clinical implantation. This study aims to systematically investigate how individual ECM proteins affect lipid membranes structurally and mechanically, and how these influences regulate cell migration. Results from Langmuir isotherm analysis, X-ray reflectivity measurements, and cell scratch assays demonstrate that strong collagen adsorption on the membrane surface disrupts lipid packing. However, its rigid network provides a sturdy scaffold for cell adhesion, thereby enhancing cell attachment and promoting cell migration. In contrast, elastin has a minimal structural or mechanical impact on the membrane during both adsorption and compression, but it benefits cells by facilitating migration and reducing the risk of infection. Fibronectin, on the other hand, exhibits complex mechanical responses to compression, characterized by significant structural rearrangements that occur during adsorption. This strong interaction with the membrane can result in excessively high adhesion forces, ultimately limiting cell motility. These findings lay the foundation for the design of artificial scaffolds that can manipulate cellular responses, a critical step toward advancing regenerative medicine and tissue engineering. SignificanceFabricating extracellular matrix (ECM) scaffolds from cells offers advantages over traditional approaches, such as decellularized tissues, which face donor limitations, and artificial scaffolds, which may hinder cellular communication. However, the slow harvesting process of cell-derived ECM has limited its clinical applications. This research is part of a larger mission to engineer ECM prescaffolds on lipid carriers tailored to cell requirements, enhancing ECM production and regulating cell behavior. The first step involves systematically analyzing the structural and mechanical effects of ECM on lipid membranes and how these effects regulate cellular behavior. This work confirms distinct characteristics of ECM proteins, advancing fundamental understanding of cell-matrix interactions and paving the way for scaffold engineering.

Methods to visualize and quantify the molecular responses of cells to local forces exerted at adhesions are crucial to elucidate how physical forces control cellular behavior. Of the many proteins involved in focal adhesions, vinculin plays a key role in mediating force-sensitive processes. Here, we combined optical tweezers and Forster resonance energy transfer (FRET) microscopy to measure the intensity and FRET efficiency of the vinculin tension sensor, VinTS, in response to a force. Fibroblasts expressing VinTS formed adhesions on fibronectin-coated, 3m-diameter, polystyrene beads. As the beads were displaced by the cell, we applied an optical trap to counteract this movement and increase the traction force required by the cell to maintain the bead displacement. The optical trap stiffness varied from zero (no laser) up to 0.26 pN/nm. In this range, the median bead displacement after 5 min was ~200nm in all trapping conditions inducing counteracting forces in the 10-100pN range. To maintain this displacement, vinculin recruitment increased (up to 35% in relative intensity at high stiffness) while tension increased but more moderately (1-2% decrease in absolute FRET efficiency). For higher trap stiffness, the main response was an increase in vinculin recruitment, while the tension did not increase significantly. The increase in vinculin intensity was correlated with the decrease in FRET efficiency at 0.26 pN/nm but not at lower stiffness. Thus, the presence of the high stiffness optical trap over 5 min appears to induce a positive correlation between vinculin recruitment and vinculin tension. In a few instances, vinculin puncta migrated a few microns away from the bead exceeding the bead movement speed while experiencing an increase in both vinculin intensity and tension. Taken together, the results suggest that combining an optical trap with vinculin tension measurements uncovers novel vinculin dynamics in the presence of a force.

The apparent pKa of ionizable lipids in lipid nanoparticles (LNPs) is a key determinant of RNA encapsulation during formulation and endosomal release after cellular uptake. However, it is difficult to predict the effective pKa of a given ionizable lipid solely from its solution pKa, because it is sensitive to the membranes composition, as well as solution conditions such as the salt concentration. We developed a simple continuum electrostatics model, based on Gouy-Chapman theory, to predict the shift in effective pKa for ionizable lipids in lipid bilayers as a function of salt concentration and membrane composition. We derive equations for the surface potential and fraction of lipids charged, which are solved self-consistently as a function of solution pH to extract the titration curve and effective pKa. The model shows that the shift in effective pKa is largest when the concentration of titratable lipid is high, and the effect is diminished by increasing salt concentration. We provide a python implementation of the model and an interactive notebook that will allow users to further easily explore the predicted pKa shifts as a function of formulation variables.

Microplastic (MP) pollution, which is present in the ecosystem in vast quantities, adversely affects human health and the environment, making it imperative to develop methods for its mitigation. The challenge of detecting or capturing MPs could potentially be addressed using plastic-binding peptides (PBPs). The ideal PBP for MP remediation would not only bind strongly to plastic, but also have other properties such as high solubility in water or great binding specificity to a certain plastic. However, the scarcity or absence of known PBPs for common plastics along with the lack of methods that can discover PBPs with all of the desired properties precludes the development of peptide-based MP remediation strategies. In this study, we discovered short linear PBPs with high predicted water solubility and binding specificity by employing an in-silico discovery pipeline that combines deep learning and biophysical modeling. First, a long short-term memory (LSTM) network was trained on biophysical modeling data to predict peptide affinity to plastic. High affinity peptides were generated by pairing the trained LSTM with a Monte Carlo tree search (MCTS) algorithm. Molecular dynamics (MD) simulations showed that the PBPs discovered for polyethylene, the most common plastic, had 15% lower binding free energy than PBPs obtained using biophysical modeling alone. PBPs with both high affinity and high predicted solubility in water were found by including the CamSol solubility score in the MCTS peptide scoring function, increasing the average solubility score from 0.2 to 0.9, while only minimally decreasing affinity for polyethylene. The framework also discovered peptides with high binding specificity between polystyrene and polyethylene, two major constituents of MP pollution, using a competitive MCTS approach that optimized the difference in affinity between the two plastics. MD simulations showed that competitive MCTS increased the binding specificity of PBPs for polystyrene and identified peptides with relatively great preference for either of the two plastics. The framework can readily be applied to design PBPs for other types of plastic. Overall, the high-affinity PBPs with desirable properties discovered by marrying artificial intelligence and biophysics can be valuable for remediating MP pollution and protecting the health of humans and the environment.

This study investigates closed kinematic chain biomechanics in cycling with a focus on knee joint loading. Data from 16 cyclists collected on a standardized ergometer were analyzed in OpenSim using inverse dynamics, static optimization, and joint reaction analysis. To keep the pipeline consistent across all subjects, the report summarizes right-knee outputs over a steady-state interval between 120 and 124 s. Peak knee joint moments ranged from 15.79 to 44.85 Nm (mean 30.49 {+/-} 7.66 Nm), while peak resultant knee reaction forces ranged from 1187.61 to 3309.04 N (mean 2317.19 {+/-} 728.19 N). Static optimization showed strong contributions from the rectus femoris and vastus lateralis during power production, with additional stabilization from the biceps femoris long head and gastrocnemius medialis. Mean peak muscle activation was highest for the rectus femoris (0.72 {+/-} 0.19), followed by the biceps femoris long head (0.66 {+/-} 0.20). Mean peak muscle force was highest for the vastus lateralis (1078.1 {+/-} 305.8 N) and rectus femoris (994.1 {+/-} 379.2 N). The results confirm substantial inter-subject variability in knee loading and support the use of personalized training or rehabilitation strategies when cycling is used for performance development or joint recovery.

Mass-conserved reaction-diffusion systems are used as mathematical models for various phenomena such as cell polarity. Numerical simulations of this system present transient dynamics in which multiple stripe patterns converge to spatially monotonic patterns. Previous studies indicated that the transient dynamics are driven by a mass conservation law and by variations in the amount of substance contained in each pattern, which we refer to as "pattern flux". However, it is challenging to mathematically investigate these pattern dynamics. In this study, we introduce a reaction-diffusion compartment model to investigate the pattern dynamics in view of the conservation law and the pattern flux. This model is defined on multiple intervals (compartments), and diffusive couplings are imposed on each boundary of the compartments. Corresponding to the transient dynamics in the original system, we consider the dynamics around stripe patterns in the compartment model. We derive ordinary differential equations describing the pattern dynamics of the compartment model and analyze the existence and stability of equilibria for the reduced ODE with respect to the boundary parameters. For a specific parameter setting, we obtained results consistent with previous studies. Moreover, we present that the stripe patterns in the compartment model are potentially stabilized by changing the parameter, which is not observed in the original system. We expect that the methodology developed in this paper is extendable to various directions, such as membrane-induced pattern control.

Silver (Ag+) ions are known to be toxic to bacteria, cells, organisms and living systems; yet its impacts on the locomotion of surface-crawling organisms remain poorly quantified. Here we investigated the short-term (0-6 hours) effects of Ag+ ions on the locomotion of Drosophila melanogaster larvae on flat agarose surfaces containing Ag+ ions at different concentrations (0, 1, 10, and 100 mM). By quantifying their locomotion, we found that Drosophila larvae showed shorter accumulated distances and reduced crawling speed. Additionally, we quantified the go/stop dynamics and peristalsis of the larvae and observed that Ag+ ions disrupted the normal, rhythmic, peristaltic contraction of the larvae and "trapped" them in the stop phase. Such toxic effects were dependent on Ag+ concentration and exposure duration.

SignificanceQuantifying lipid droplet (LD) remodeling in 3D hepatic organoids is often limited to endpoint staining or phototoxic live fluorescence imaging, thereby obscuring droplet-level kinetics. AimWe aimed to develop a label-free method to track LD dynamics in living hepatic organoids under different fatty-acid loads. ApproachTime-lapse 3D refractive-index tomograms were acquired using holotomography and analyzed with a depth-adaptive, multi-threshold segmentation pipeline to quantify LD number, volume, sphericity, and refractive-index-derived concentration and dry mass at single-droplet resolution. ResultsOleic acid and linoleic acid induced LD accumulation while preserving organoid integrity, whereas palmitic acid triggered rapid structural collapse. Despite increases in total LD burden under both oleic acid and linoleic acid, droplet-level dynamics diverged: oleic acid produced volume-dominated accumulation via enlargement of fewer LDs and increased size heterogeneity, whereas linoleic acid produced number-dominated accumulation via sustained increases in LD number, yielding a more uniform population of small droplets. ConclusionsLabel-free holotomography with depth-adaptive analysis enables non-invasive, longitudinal, and multi-scale quantification of LD dynamics in intact organoids and reveals fatty-acid- dependent temporal modes of lipid storage. Statement of DiscoveryWe developed a label-free, longitudinal 3D holotomography framework with depth-adaptive lipid droplet segmentation that quantifies single-droplet dynamics in living mouse hepatic organoids. Using this platform, we found that oleic acid and linoleic acid induce LD accumulation via distinct strategies--oleic acid via droplet enlargement and linoleic acid via sustained increases in droplet number--while palmitic acid rapidly compromises organoid integrity.

Staphylococcus aureus (S. aureus) is a clinically relevant pathogen capable of adapting its membrane composition in response to environmental stress. In this adaptive process, bacterial carotenoids play a crucial role. Although staphyloxanthin (STX) is the main carotenoid produced by the bacterium, S. aureus also synthesizes other pigmented intermediates that play an unknown role in regulating membrane biophysical properties. In this study, we purified 4,4-diaponeurosporenoic acid (4,4'-DNPA) from S. aureus carotenoid extracts and evaluated its effect on the thermotropic and biophysical properties of representative membrane models. The highly rigid triterpenoid 4,4'-DNPA is one of the last precursors in the biosynthesis of STX and is found in high concentrations in the stationary phase of S. aureus. Phase transition temperatures were determined using infrared spectroscopy, while interfacial hydration and hydrophobic core dynamics were investigated using fluorescence spectroscopy through Laurdan generalized polarization and DPH anisotropy. The results show that 4,4'-DNPA increases the main phase transition temperature of lipid bilayers in a concentration-dependent manner. This is in contrast to STX that decreases the transition temperature. This difference is consistent with the additional fatty acid present in STX that changes its effect on the phase behavior. Furthermore, 4,4'-DNPA reduced the interfacial hydration levels and restricted hydrophobic-core dynamics at higher concentrations, consistent with increased molecular order and stability. 4,4'-DNPA therefore complements STX in increasing membrane order and lipid packing. These findings support the notion that the production of bacterial carotenoids functions as a biophysical regulatory mechanism of lipid packing in S. aureus membranes.

Fluorescent reporters such as fluorescent proteins or chemigenetic indicators are indispensable tools for studying biological processes using light microscopy. Choosing an appropriate fluorescent tag is a crucial step in experimental design not only for imaging but also for quantitative measurements such as fluorescence fluctuation spectroscopy. Two key parameters should be considered: Fluorescent brightness and photo-bleaching. Change to fluorescence intensity due to photobleaching is relatively easy to assess in different biological environments, while brightness is more elusive. Here, we develop and employ a fluorescence correlation spectroscopy (FCS) based excitation scan assay that determines fluorescent protein performance and validate it in tissue culture and zebrafish embryos. We employ our FCS pipeline to compare a set of 10 established fluorescent proteins as well as HALO and SNAP tags for both cellular imaging and measurements of diffusion dynamics with FCS. We show that mNeonGreen outperforms mEGFP in tissue culture and zebrafish embryos. We also compare StayGold variants against other green fluorescent proteins and chemigenetic reporters in tissue culture. Overall, we present a broadly applicable approach for determining fluorescent reporter brightness in the living system of interest.

Accurate ion force fields are essential for molecular dynamics simulations of biomolecular systems, particularly in combination with modern water models such as OPC. While OPC water improves the description of bulk water and biomolecules, the transferability of existing ion force fields to this model remains an open question. Here, we systematically assess the transferability of monovalent and divalent ion force field parameters (Li+, Na+, K+, Cs+, Mg2+,Ca2+, Sr2+, Ba2+, Cl- and Br-) to OPC water by comparing single-ion and ion-pairing properties with experimental data. Our analysis reveals that no single literature parameter set provides accurate results for all ions when directly transferred to OPC water. We hence introduce the MS/G-LB(OPC) force field, which combines Mamatkulov-Schwierz-Grotz cation parameters with Loche-Bonthuis anion parameters. MS/G-LB(OPC) reproduces hydration free energies, first-shell structural properties and activity derivatives at low salt concentrations. Our results demonstrate that transferring ion parameters to OPC can lead to significant and ion-specific deviations from experimental data, making careful validation essential. At the same time, the systematic transfer and combination of ion parameters from existing force fields can provide a practical and computationally efficient alternative to full reparameterization. MS/G-LB(OPC) is available at https://git.rz.uni-augsburg.de/cbio-gitpub/opc-ion-force-fields.

ObjectiveTo investigate the effects of different gait patterns on knee joint biomechanics and dynamic stability during stair ascent. MethodsFourteen healthy males were recruited to ascend stairs using two distinct gait patterns: the "single-step" (leading with the same leg) and "cross-step" (alternating legs) strategies. Kinematic and kinetic data were collected synchronously using a Qualisys infrared motion capture system and a Kistler 3D force plate. Dynamic stability was quantified using the Margin of Stability (MOS), and knee joint biomechanics were evaluated using Patellofemoral Joint Stress (PFJS) and other relevant metrics. ResultsThroughout the gait cycle, there was no significant difference in the Medio-Lateral (ML) MOS between the single-step and cross-step patterns (P=0.318). However, in the Anterior-Posterior (AP) direction, the MOS for both patterns remained negative and decreased over time, with the cross-step pattern exhibiting significantly lower AP MOS values than the single-step pattern (P=0.002). At the moment of left foot-off, significant differences were observed in the right knee joint angle, right knee joint moment, net joint moment, effective quadriceps muscle lever arm, Quadriceps Force (QF), the angle between the quadriceps tendon and patellar ligament, Patellofemoral Joint Force (PFJF), patellofemoral joint stress, and patellofemoral contact area (all P<0.001). ConclusionsDuring stair ascent, the cross-step pattern reduces body stability, thereby increasing the risk of backward falls. Furthermore, this pattern increases patellofemoral joint stress, subjecting the knee to greater loading. Therefore, it is recommended to enhance lower limb muscle strength through targeted training to reduce fall risk. Additionally, adopting a more cautious gait strategy (such as the single-step pattern) can help minimize patellofemoral joint loading and mitigate the risk of patellofemoral pain.

It is an essential element of mechanobiology to measure the forces of biological cells. In microparticle traction force microscopy, they are inferred from the deformation of elastic microparticles. Two complementary variants have been introduced before: the volume method, which reconstructs surface stresses from the displacements of fiducial markers embedded inside the particles, and the surface method, which infers stresses directly from the deformation of the particle surface. However, a systematic comparison of the two methods has been lacking. Here, we quantitatively compare both approaches using simulated traction fields representing biologically relevant loading scenarios. We find that the surface method consistently reconstructs traction profiles with substantially lower errors than the volume method, which suffers from displacement tracking and stress calculation at the surface. At high noise levels, however, the performance gap becomes smaller. To compare the performance of the two methods in a realistic experimental setting, we developed DNA-based hydrogel microparticles equipped with both fluorescent surface labels and embedded fluorescent nanoparticles, enabling the direct comparison of the two methods within the same system. Compression experiments produced traction profiles consistent with Hertzian contact mechanics and confirmed the trends observed in the simulations. While our computational workflow establishes a framework to apply both methods, our experimental workflow establishes DNA microparticles as versatile and biocompatible probes for measuring cellular forces.

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} (A{beta}), yet the specific link between plaque burden and cognitive decline remains a subject of intense investigation. This paper presents a mathematical model that simulates the coupled dynamics of A{beta} monomers, soluble oligomers, and fibrillar species in the brain tissue. By modifying existing moment equations to include a dedicated conservation equation for A{beta} monomers, the model explores how various microscopic processes, such as primary nucleation, surface-catalyzed secondary nucleation, fibril elongation, and fragmentation, contribute to macroscopic disease progression. Central to this study is the concept of "accumulated neurotoxicity" as a surrogate marker of biological age, defined as the time-integrated concentration of soluble A{beta} oligomers. Unlike plaque burden, accumulated neurotoxicity cannot be reversed, and the harm it causes depends critically on the sequence of events that produced it. Numerical results demonstrate that while plaque burden and neurotoxicity both increase over time, their relationship is non-linear and highly sensitive to the efficiency of protein degradation machinery. Specifically, impaired degradation leads to a rapid advancement of biological age relative to calendar age. The model further identifies oligomer dissociation and fibril fragmentation as potential protective mechanisms that can counterintuitively reduce neurotoxic burden by diverting monomers away from the soluble oligomer pool. These findings provide a quantitative framework for understanding why individuals with similar plaque burdens may experience vastly different cognitive outcomes, underscoring the importance of targeting soluble oligomers early in therapeutic interventions.

Proteins with intrinsically disordered regions (IDRs) migrate at a higher apparent molecular weight in sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) complicating their analysis and identification. Here, we investigate the sequence determinants of the hypomobility of IDRs using a series of synthetic low complexity domains. We find that negative charge increases the apparent molecular weight, but neutral polar tracts also have abnormally slow migration. Positive charge and hydrophobic residues decrease the apparent molecular weight, although lysine residues show a biphasic effect with decreased migration at high fractional contents. Combinations of residues show that different sequence contributions to the apparent molecular weight are not additive. The results can be rationalized by the protein-decorated micelle model by considering both SDS binding and the compaction of protein SDS-complexes.

Cerebrospinal fluid (CSF) is a Newtonian fluid that bathes the brain and spinal cord and oscillates in response to the physiological periodic changes in brain volume, of which the cardiac cycle is a major driver. Understanding this motion is essential for clarifying its contribution to solute transport, waste clearance, and drug delivery. In this work, we study oscillatory and steady streaming flow in the cranial subarachnoid space using a lubrication-based theoretical framework. The model represents the cranial CSF compartment as a thin fluid layer bounded internally by the brain surface and externally by the dura, driven by time-dependent brain surface displacements. We first derive simplified governing equations for flow over an arbitrary smooth sphere-like brain surface and obtain analytical solutions for an idealised spherical geometry with uniform displacements. We then incorporate realistic displacement fields reconstructed from MRI measurements in healthy subjects and solve the reduced equations numerically. The results show that oscillatory forcing produces a steady streaming component that may enhance solute transport compared with diffusion alone. This work provides a mechanistic description of the flow generated by physiological brain motion and highlights the potential presence of steady streaming in cranial subarachnoid fluid dynamics.

Phase separated condensates are recognized as a ubiquitous mechanism of spatial organization in cell biology. Biophysical modeling of condensates provides critical insights into the dynamics and functions of these subcellular structures that are difficult to extract via experiments. Here we present an efficient computational pipeline, CASPULE (Condensate Analysis of Sticker Spacer Polymers Using the LAMMPS Engine), to simulate and analyze the biological condensates made of sticker-spacer polymers. CASPULE implements a unique force field that combines traditional Langevin dynamics with a "detailed balance proof" protocol for single-valent bond formation between stickers. This framework allows us to study the non-trivial biophysics that emerge out of the single-valent sticker interactions coupled with the effect of separation in energetic contribution by stickers and spacers. We provide detailed documentation on how to setup the simulation environment, perform simulations and analyze the results. Through case studies, we highlight the utility and efficacy of our pipeline. Importantly, we provide statistical parameters to characterize the cluster size distribution often observed in biological systems. We envision this tool to be broadly useful in decoding the interplay of kinetics and thermodynamics underlying the formation and function of biological condensates.