European Biophysics Journal

The post-detachment drifting phase of macrophytes, during which they can be alive, dead, or senescent, plays a crucial ecological and biogeochemical role by influencing long-range dispersal, transporting rafting species, affecting carbon sequestration, promoting blooms, and leading to beaching events. In order to predict the dispersal of macrophytes and macroplastic particles and where they will affect the ecosystem, it is important to be able to model how their drift velocities are influenced by hydrodynamic and aerodynamic factors. In this study, we investigated the drift velocity of macrophytes with diverse morphologies and macroplastic particles in a racetrack flume under different current conditions, in combination with and without wind in the same direction as the water current. Our data show that the drift velocity of macrophytes is highly dependent on their buoyancy and affected by morphological characteristics. Wind increased the velocity of the surface water, which in turn increased the drift velocity of both macrophytes and macroplastic particles. However, wind-induced turbulences reduced the overall effect, especially for macrophytes, which protruded minimally above the water surface in comparison to macroplastic particles. For positively buoyant specimens, an existing particle model was experimentally confirmed to predict macrophyte and macroplastic particle drift velocities reliably, irrespective of shape. For negatively buoyant species, we propose a novel equation to predict drift velocity, incorporating the diverse shapes of macrophytes, as well as their interaction with the bottom. These results represent the first step toward the development of trait-based models that represent macrophytes more realistically in dispersal simulations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/709487v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@1ab9f6aorg.highwire.dtl.DTLVardef@6ef75dorg.highwire.dtl.DTLVardef@132334forg.highwire.dtl.DTLVardef@c6a3d8_HPS_FORMAT_FIGEXP M_FIG 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, in which 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 to faithfully capture 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. Author summaryCells often migrate through very narrow spaces in tissues, a process critical for cancer invasion, immune surveillance, and tissue development. In particular, the stiffness of the nucleus, the largest and most rigid organelle, can limit migration through tight pores. In this study, we present a mathematical model describing the motion of a cell and its nucleus through a microchannel during cell translocation, using a geometric formulation based on surface partial differential equations. The model is general and applicable to a variety of scenarios involving confined cell transport. The model is validated by reproducing key experiments on cell translocation through narrow microchannels. The framework incorporates essential surface features, including mechanical responses, bending rigidity, and surface tension. Sensitivity analysis highlights surface tension and channel geometry as the parameters that most strongly influence translocation. Overall, the model provides new insights into the mechanics of confined cell transport, grants access to cellular quantities that are difficult to measure experimentally, such as cell and nucleus areas, perimeters, and stresses, and establishes a foundation for future extensions incorporating more complex biochemical processes.

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.

Although rhizosphere microbiomes are known to enhance plants resistance to water stress, it is believed that only fungi actively contribute to the transport and uptake of water. We investigated the biomechanical impact of bacterial motility on water transport in soil by combining surface tension measurements and water infiltration experiments in soil microcosms. We observed that flagellar-based motility in Bacillus subtilis cells reduces the apparent surface tension of fluids by up to 15%. The effect reported depends on cell density and swimming speed, confirming its biomechanical origin, and was able to accelerate water infiltration and rewetting of soil. We conclude that Bacillus subtilis facilitates soil water transport through the deformation of air water interfaces in pores.

Many biochemical processes are dependent on the presence or absence of molecular oxygen (O2). Palladium-tetrapyrrol derivatives can be used to measure O2-concentrations and O2-turnover during biochemical reactions and microbial growth in standard microtiter plates (MTPs). Palladium(II)-5,10,15,20-(tetrapentafluorophenyl)-porphyrin (1; CAS 72076-09-6) and Palladium(II)-5,10,15,20-(tetraphenyl)tetrabenzoporphyrin (2; CAS 119654-64-7) are introduced with this study. Spectral analyses of both compounds revealed that fluorescence quenching by O2 is not evenly distributed throughout all wavelengths and can therefore be used ratiometrically. Experimentally determined fluorescence lifetimes are around 500 {micro}s and 300 {micro}s for 1 and 2, respectively. A simple protocol is disclosed, how to immobilize the indicators on the bottom of MTP wells to give clear transparent dye doped polymer layers. We propose a straightforward procedure of how fluorescence data can be processed and calibrated in terms of O2 concentrations. Diverse applications are demonstrated and discussed, which include oxygen consumption and production by microorganisms as well as by enzymatically catalysed biochemical reactions. Various aspects are critically considered, as there are e.g. the dependence of O2 solubility on temperature and salinity, the diffusion of O2 across diverse phase boundaries, the unwanted O2 ingress into the reaction volume, the oxygen binding capacity of the MTP plastic material and the pH-dependence of the sensor layer. The findings and methods presented here open up a broad variety of high throughput assays involving changes of dissolved O2 as measurands for biochemical and biological activity. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/718663v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@4daa4dorg.highwire.dtl.DTLVardef@e7ab8aorg.highwire.dtl.DTLVardef@1af1149org.highwire.dtl.DTLVardef@97fea5_HPS_FORMAT_FIGEXP M_FIG C_FIG

Micro-elastography is an optical technique that studies elastic waves for the mechanical characterisation of micrometric objects, such as cells. We propose to adapt this technique for the characterisation of millimetre-sized samples using a white light microscope. The objective is to perform a rapid, global characterisation of the elasticity of a biopsy. The millimetre-sized samples to be characterized are embedded in an agarose gel. A vibrator generates shear waves in this gel that transmit naturally inside the sample. This technique removes the need for precise manipulation of the wave source. A high-speed camera records the propagation of the waves in the sample. Their velocity is calculated using a noise correlation approach. Due to the lack of millimetric phantoms of calibrated elasticity, we choose to validate this method with a three step process. The experimental setup is first validated on homogeneous gels, then on biological samples of increasing elasticity, biopsies of beef liver hardened by heating, and finally on biological samples of clinical interest: biopsies of mouse endometrium. This method can be applied to all types of biological tissue, paving the way for rapid mechanical characterization of biopsies.

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

Aims/hypothesisQuantitative nanoscale analysis of insulin secretory granules (ISGs) in human pancreatic tissue has been limited by the lack of imaging methods that combine high resolution with large-scale sampling. We aimed to establish expansion microscopy (ExM) as a platform for in situ, quantitative analysis of ISG organisation in human {beta}-cells and to assess whether type 2 diabetes (T2D) is associated with alterations in granule size, abundance or spatial organisation. MethodsWe applied Magnify ExM to PFA-fixed, paraffin-embedded pancreatic tissue sections from 6 human donors, 3 non-diabetic (ND) and 3 T2D, enabling super-resolution optical imaging of insulin-labelled granules. Insulin-positive structures were segmented and analysed using a morphometric pipeline to quantitatively assess size, shape and spatial features. Granule clustering was quantified based on combined area and roundness criteria. ResultsThe diameter distribution of highly circular granules was similar between ND and T2D samples and estimates of granule number per cell indicated only a modest reduction in T2D ([~]25%). In contrast, mapping insulin-positive structures in a roundness-area space revealed a marked enrichment of large, irregular objects consistent with granule clustering in T2D. The fraction of clustered granules was significantly increased in T2D and strongly inversely correlated with insulin stimulation index (r = -0.85). Conclusions/interpretationThese results establish expansion microscopy as a powerful platform for quantitative nanoscale analysis of human pancreatic tissue and identify altered spatial organisation of insulin granules, rather than marked granule depletion, as a prominent feature associated with {beta}-cell dysfunction in T2D. Research in contextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LI{beta}-cell dysfunction in type 2 diabetes is often attributed to reduced insulin content or {beta}-cell loss. C_LIO_LIInsulin secretory granules (ISGs) have been characterised ultrastructurally, but quantitative analysis in human tissue remains limited. C_LIO_LISuper-resolution approaches, including expansion microscopy, are emerging tools for nanoscale imaging in biological tissues. C_LI What is the key question?O_LIIs {beta}-cell dysfunction in type 2 diabetes associated with depletion of insulin granules or with altered spatial organisation? C_LI What are the new findings?O_LIInsulin granule size distribution is largely preserved in type 2 diabetes, with only a modest reduction in granule number per cell. C_LIO_LIA significant increase in insulin granule clustering is observed in diabetic {beta}-cells. C_LIO_LIGranule clustering is strongly inversely correlated with insulin secretion in the same donor tissues. C_LI How might this impact on clinical practice in the foreseeable future?O_LIIdentifying altered granule organisation as a feature of {beta}-cell dysfunction may help refine the understanding of disease mechanisms and guide future strategies targeting {beta}-cell function. C_LI

Biofilm extracellular matrix (ECM) varies with environmental conditions and substrate properties. Understanding the surface-biofilm relationship helps to perfect antibacterial strategies and to design new engineered living materials (ELMs). In this work, we studied how cationic and anionic polyelectrolyte coatings affect macroscopic features of Escherichia coli curli-producing biofilms, as well as the properties of their curli amyloid fibers. Cationic coatings limited biofilm spreading, increased their surface density and water absorption, which correlated with a higher yield of curli amyloid fibers with looser structure. In contrast, anionic surfaces allowed for standard biofilm spreading, with a lower fiber yield but a more compact and chemically stable fiber structure. Higher biofilm rigidity and adhesion were measured on both types of charged surfaces. Thus, we propose that the differences in biofilm macroscopic properties result from a trade-off between curli quantity and quality in the ECM, namely fiber density and molecular packing, as well as their interaction with water. Our findings provide insights on how the biophysical properties of the ECM can be controlled by tuning the substrate physico-chemical characteristics with charged coatings. This work opens up new avenues for developing antimicrobial strategies, as well as tailoring the properties of amyloid-based ELMs. TOC figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/721109v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@191cd79org.highwire.dtl.DTLVardef@148f914org.highwire.dtl.DTLVardef@1d8c2f8org.highwire.dtl.DTLVardef@1e84eaf_HPS_FORMAT_FIGEXP M_FIG C_FIG

With the development of microfluidics, it has now become possible to assess the susceptibility of bacteria to antibiotics at the single-cell level instead of relying on population measurements. Such studies are particularly relevant when the growth of bacterial population in the presence of antibiotics is heterogeneous. Here, we build a model to describe such a case, and apply it to experimental measurements on a small population of E. Coli exposed to ciprofloxacin, a drug which is well known for triggering a bistable response.

Extracellular vesicles (EVs) are cell-secreted biological nanoparticles that play a crucial role in intercellular communication and are gaining increasing attention as diagnostic biomarkers, therapeutic agents, and drug delivery vehicles. Consequently, the development of robust and sensitive methods for their characterization is essential. Herein we present the use of a microscope-mounted nanofluidic device for direct size determination and multi-parametric (3-color) fluorescence-based phenotyping of single biological nanoparticles that are in the size range of 20-200 nm in a method we denote Nano-SMF (SMF; size and multiplexed fluorescence). We demonstrate that it is possible to accurately determine the size of nanoparticles by analyzing their one-dimensional Brownian motion during directional flow through nanochannels, achieving size distributions for monodisperse nanoparticle solutions that are on par with TEM analysis, and size discrimination of nanoparticle mixtures that is significantly improved compared to conventional nanoparticle tracking analysis (NTA). Furter, we demonstrate that the method can be applied to analyze EVs directly in minute volumes of cell supernatant, avoiding pre-isolation or concentration steps. The method was applied to phenotype CD63- and CD81-positive EVs from a human embryonic kidney cell model, demonstrating that vesicle sub-populations defined by these two tetraspanin biomarkers differ significantly in size.

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.

Staphylococcus aureus (S. aureus) is an opportunistic pathogen that is a global health concern for its ability to cause a wide spectrum of clinical infections. Due to the emergence of resistance to commonly used antibiotics, there has been interest in exploring the use of antimicrobial peptides to treat S. aureus infections. However, changes in the lipid composition of the lipid bilayer membrane can alter the activity of peptides, and S. aureus is able to induce variations in lipid composition in response to environmental stress. Here, we explore how the main lipid components in S. aureus are altered when exposed to LL-37, a human cathelicidin involved in primary immune response, and ATRA-1, a short antimicrobial peptide derived from the snake Naja atra venom. A lipidomic study is conducted through HPLC-MS-MS (LC-ESI-MS/MS) to quantify phosphatidylglycerol, cardiolipin, lysyl-phosphatidylglycerol, monogalacto- and digalacto-diacylglycerol, and carotenoids. In addition, menaquinones, responsible for electron transport during oxidative phosphorylation, were also quantified. Biophysical properties such as membrane electric surface potential and lipid packing were assessed. We find that lipid adaptation is specific to the type of antimicrobial peptide, where ATRA-1 mainly induces changes in the electric surface potential through variations in Lysyl-PG, while exposure to LL-37 changes carotenoid levels, inducing an increase in membrane rigidity as measured by FTIR. In addition, both peptides induce a reduction in menaquinone and DGDG levels. These findings highlight the role of membrane lipid remodeling as a peptide-specific response mechanism in S. aureus, with implications for the development of AMP-based therapies. HighlightsO_LIStaphylococcus aureus responds through shifts in lipid composition and membrane biophysical properties to exposure to the antimicrobial peptides LL-37 and ATRA-1. C_LIO_LIBoth LL-37 and ATRA-1 lead to shifts in the glycolipids MGDG and DGDG; two lipids involved in regulating negative membrane curvature stress and responsible for shifting resistance to antimicrobial peptide activity in Staphylococcus aureus. C_LIO_LILL-37 treatment leads to an overall reduction in carotenoid content in Staphylococcus aureus, including the carotenoid end-product staphyloxanthin and the precursor 4,4-diaponeurosporenoic acid. Both lipids regulate membrane biophysical properties and protect Staphylococcus aureus from oxidative stress. C_LIO_LIBoth LL-37 and ATRA-1 lead to a reduction in menaquinone levels, which are involved in the electron transport chain during oxidative phosphorylation. Reduction in these menaquinones have been associated to the formation of small colony variants that are often observed in chronic Staphylococcus aureus infections. C_LI

IntroductionStereological estimates of villous membrane thickness and surface area are widely used to infer the diffusive exchange capacity of the human placenta. A key geometric determinant of exchange capacity can be expressed as an effective diffusive length scale. Here we combine virtual histological sections with computational modelling in realistic villous geometries to assess the accuracy of classical stereological estimates of this diffusive length scale. MethodsTwo terminal villi, reconstructed from three-dimensional imaging, were digitally sectioned to generate random two-dimensional geometries containing fetal capillaries and surrounding villous tissue. For each section, we simulated steady diffusive transport between the fetal capillary and intervillous space boundaries to obtain a physics-based diffusive length scale as a reference case. Using the same geometries, we applied standard line-intercept stereology to measure harmonic-mean barrier thickness and boundary-length densities, from which a stereological estimate of diffusive length scale was derived. ResultsAcross both villi, stereology systematically overestimated the diffusive length scale by approximately 15-25%, depending on villus and section. We identified sources of this discrepancy, including interface curvature and assumptions underpinning the stereological correction factors, using idealised models of villus structure. ConclusionThese findings highlight the need for stereological approaches that account for curvature when interpreting placental structure-function relationships.

Black extremotolerant fungi form persistent biofilms on a wide range of natural and engineered substrates. Able to weather minerals, affect stone monument surfaces, and colonize solar panels, they demonstrate a strong capacity to interact with and modify material surfaces, even under most extreme conditions. In this study, we establish a methodological workflow for the structural and mechanical characterization of melanized biofilms formed by the black fungus Knufia petricola. This species represents a broader group of resilient surface colonizers and provides a model for in-depth investigation. When grown on solid agar/air interface, this species predominantly forms a compact biofilm, composed of spherical cells, while retaining the capacity for filamentous growth, providing a suitable framework to explore morphology-dependent biomechanical responses. The proposed toolbox combines complementary analytical techniques spanning multiple spatial scales, including shear-rheology to quantify bulk viscoelastic behavior, micro-indentation to resolve local stiffness of the biofilm surface, micro-computed tomography for non-destructive three-dimensional visualization of biofilm architecture, and cryogenic preparation methods and electron microscopy for high-resolution ultrastructural analysis. As a case study, we applied this workflow to compare biofilms grown on two nitrogen sources (NO3- vs. NH4+). Our results reveal that the nitrogen source plays a key role in biofilm morphology across multiple hierarchical levels - ranging from cell division patterns and distribution of extracellular polymeric substances (EPS) to overall mechanical properties, where NO3- leads to budding-dominated growth and increased stiffness, whereas NH4+ promotes meristematic growth and softer biofilms. The successful transfer and integration of methods originally developed for bacterial biofilm research highlights the feasibility of quantitative mechanical analyses in fungal systems. This multiscale toolbox provides a foundation for advancing the mechanistic understanding of fungal biofilms and biofilm-material interactions, with implications for geomicrobiology, material biodeterioration, and the design of bio-inspired functional materials. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/720134v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@7fd08borg.highwire.dtl.DTLVardef@15476c2org.highwire.dtl.DTLVardef@40be50org.highwire.dtl.DTLVardef@8e9410_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

As the duration of space flights increases, so does the need to optimize off-planet microbial growth. Microbes can both be unintentionally brought into space and cause human disease or be intentionally harnessed for on-site bioengineering functions. However, optimizing microbial growth is challenging due to an insufficient understanding of how microbial communities are affected by the extraterrestrial environment. To address this gap, we have modified a previously developed model for cell growth in microgravity. By improving the functional form used for cell growth as well as the code usability, we enable further research into how microbial communities are influenced by gravity. Applying this model to isolate individual effects of gravity on cell growth indicates that a lack of gravity-driven flow decreases cell growth in microgravity, while the absence of sedimentation increases cell growth in microgravity. These opposite effects likely contribute to the system-dependent effects of microgravity observed experimentally.

Quantum kernel methods offer a potential advantage for classification tasks in high-dimensional feature spaces, yet their practical benefit critically depends on how input features are prepared. We compare five dimensionality reduction strategies--principal component analysis (PCA), Gaussian random projection (RP Gaussian), sparse random projection (RP Sparse), partial least squares (PLS), and uniform manifold approximation and projection (UMAP) -- as pre-processing steps for quantum kernel support vector machines (SVMs) applied to trabecular bone classification from synthetic micro-computed tomography (micro-CT) data. Using a custom procedural generator based on Gaussian random field zero-crossings, we produced 500 synthetic trabecular bone volumes with controlled morphometric properties such as bone volume fraction (BV/TV), trabecular thickness (Tb.Th), number (Tb.N) and spacing (Tb.Sp). Texture features extracted from grayscale slices are reduced to 8-dimensional quantum circuit inputs via each method, then classified using both classical radial basis function (RBF)-SVMs and quantum kernel SVMs with ZZ feature maps on a statevector simulator, both evaluated with 5 x 5 repeated stratified cross-validation (25 folds). Our results show that UMAP is the only reduction method where the quantum kernel remains competitive with the classical baseline. Under repeated cross-validation, UMAP showed a +0.032 accuracy gap favouring the quantum kernel (Dietterich 5 x 2 CV p = 0.177); however, validation on 10 fully independent datasets--each with independently generated samples, separate reduction fits, and separate kernel matrices -- reversed the sign to -0.030 (paired t-test p = 0.123; Wilcoxon p = 0.193; quantum wins 3/10 datasets), indicating that the apparent advantage was likely inflated by fold dependence. Nevertheless, UMAPs gap remains small and non-significant in both analyses, whereas all linear methods (PCA, RP Gaussian, PLS) show substantial quantum deficits of -0.090 to -0.116 across BV/TV classification, with PCA and PLS remaining significant under corrected tests (5 x 2 CV p = 0.004 and p = 0.007 respectively). We additionally evaluate quantum kernel ridge regression for continuous morphometric prediction, finding that ZZ quantum kernels fail uniformly at regression (negative R2 for all methods except PLS at 4 qubits), suggesting that the ZZ kernel captures decision boundaries but not smooth metric structure. These findings provide practical guidance for feature engineering in near-term quantum machine learning pipelines and demonstrate that the choice of dimensionality reduction can determine whether quantum kernels remain competitive with classical baselines.

Significant cellular processes, including protein sorting, signal transduction, and pathogen entry, amongst others, are associated with membrane microdomains, also known as lipid rafts. Lipid rafts, due to their unique biophysical properties compared to their surrounding environment, which stem from their distinct lipid and protein profiles, have garnered interest in methods and techniques that tune their coexisting liquid-ordered/liquid-disordered state, aiming to disrupt or destabilize them. Since cholesterol stabilizes the membrane domain, cholesterol-depleting compounds like cyclodextrin can be used to destabilize and disrupt the membrane rafts. Overall, given the membrane rafts importance in biological processes, it is crucial to understand the biophysical factors that influence its stability. In this study, we present a new method for disrupting and dissolving lipid rafts in a model system of phase-separated supported lipid bilayer (SLB) patches composed of DOPC, DPPC, and cholesterol. Using fluorescence microscopy to monitor the liquid ordered (Lo) and liquid disordered (Ld) phases of the SLB patches, we observed that adding DOPC liposomes causes a transformation of the co-existing Ld and Lo phases into a single-phase bilayer. On the other hand, adding liposomes that match the lipid content of the phase-separated SLB patch increase the areas of the existing Ld and Lo phases. This work also offers a new method for redistributing raft-localized molecules, confirmed by tracking the redistribution of cholera toxin bound to GM1 after domain dissolution with DOPC liposomes. The work describes an alternative method for dynamically altering membrane composition and dissolving domains via liposome addition, rather than lipid depletion or exchange.

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.