European Biophysics Journal

Nile Red is widely used for the detection of microplastics because its fluorescence emission is sensitive to local polarity and can distinguish hydrophobic plastics from hydrophilic ones. The fluorescence of the molecular rotor, 9-(dicyanovinyl)-julolidine (DCVJ) is less sensitive to polarity but more to viscosity. DCVJ is less widely used for microplastic analysis, although it has been used to detect polystyrene nanobeads. Here, we compared these dyes with standard samples from the Hawaii Pacific University Polymer Kit 1.0 and confirmed that Nile Red, in general, was better for the detection and identification of microplastics. Fluorescence emission was analyzed using photography, as well as spectroscopy. The color and peak emission wavelength of some stained environmental microplastics were affected by additives. Raman spectroscopy was used to confirm the chemical identity of such samples. Although DCVJ emits green fluorescence on binding to some microplastics, a peak at 620 nm has been reported with polystyrene nanobeads, attributed to dimer/excimer formation. We confirmed this property and directly observed diffraction-limited spots using fluorescence microscopy, attributed to single or just a few nanobeads. Nile Red also stains polystyrene nanobeads and gave stronger signals than with DCVJ, but Nile Red was prone to false positives due to dye aggregation in aqueous solutions.

This study aimed to (1) develop an elasticity framework for the sprint force-velocity (F-V) relationship and (2) examine how maximal force (F_{0}), maximal velocity (v_{0}), and sprint distance modulate the four derived elasticity metrics, and (3) explore these elasticity metrics' interrelation. After modelling the F-V relationship differential equation, four elasticity metrics were defined as force elasticity (F_{e}), the elasticity of sprint time to F_{0}; velocity elasticity (v_{e}), the elasticity of sprint time to v_{0}; the force-velocity elasticity norm {(\mathrm{F}-\mathrm{V}}_{\mathrm{EN}}=\sqrt{F_{e}^{2}+v_{e}^{2}}), capturing the combined sprint time sensitivity to proportional changes in F_{0} and v_{0}; and the force-velocity elasticity ratio {(\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=F_{e}{\div v}_{e}), indicating which variable dominates the sprint time response. Model simulations showed that F_{e} decreased with rising F_{0} and increased with rising v_{0}, while v_{e} showed the opposite pattern. With increasing sprint distance, F_{e} decreased and v_{e} increased. Given its negligible effect on sprint time, ignoring air resistance yields a conservation law (2F_{e}+v_{e}\equiv 1), indicating that a gain in one elasticity metric necessarily diminishes the other in a fixed proportion. This framework also identifies a valley distance (d_{valley}) at {\mathrm{F}-\mathrm{V}}_{\mathrm{ER}}=2, where {\mathrm{F}-\mathrm{V}}_{\mathrm{EN}} is minimized (\sqrt{0.2}) and sprint time is least responsive to changes in F-V relationship variables. Empirical data confirmed that the two theoretical laws still hold approximately when air resistance is considered. By linking changes in F_{0} and v_{0} to sprint time across different distances, the elasticity framework provides a quantitative basis for estimating the theoretical sprint time response to documented changes in F-V relationship variables.

This paper presents and critically reviews the results of original and some literature based experimental studies conducted by the authors last years on the structural organization of DNA in dormant (starvation stress), anabiotic dormant (4 HR treatment) E. coli cells, as well as the K12 {Delta}dps strain, which lacks the Dps protein (Dps null E. coli). The experimental data includes small-angle synchrotron radiation diffraction (SAXS) and transmission electron microscopy (TEM) data. Synchrotron radiation diffraction experiments on K12{Delta}dps cells allowed us to conclude that peaks at 44.3, 22.1, and 14.8 angstrom resolutions are associated exclusively with ordered DNA organization. Peaks at 44.3, 22.1, and 14.8 angstrom resolutions are also observed for samples of dormant (starvation stress) cells and anabiotically dormant cells. Therefore, this ordered DNA organization also applies to samples of dormant and anabiotically dormant cells. A model is proposed that considers the ordered DNA organization in the cell as a cholesteric liquid crystal. The powder diffraction pattern calculated based on this model is compared with experimental small angle X ray scattering (SAXS) data obtained on Dps-null cell samples. The model completely reproduces the key features of the experimental diffraction pattern from Dps-null cell samples. Accordingly, the cholesteric liquid crystal model corresponds to DNA packaging in dormant and anabiotically dormant cells. Cholesteric liquid crystal ordering should be further considered in all models of cellular DNA packaging. To address the question of which structural organization of DNA predominates in the cell: the cholesteric liquid crystal or nanocrystalline or whether they coexist and fully manifest themselves under different external conditions, it is necessary to utilize the latest methodological advances in structural analysis.

Neutron scattering is a powerful technique to investigate atomic structures and molecular dynamics of proteins at the nano-scale. When it comes to dynamics, incoherent and coherent scattering respectively provide information on the single and collective dynamics of nuclei. In proteins, hydrogen has the highest incoherent cross-section, and it is common practice to overlook the contribution of coherent terms stemming from all nuclei. However, the fast collective dynamics of heavier nuclei could also be studied if coherent scattering and incoherent scattering were experimentally separated. The recent advent of polarized neutron spectroscopy with sufficient flux and energy resolution has made it possible, and opens new perspectives to investigate the relative importance of coherent scattering and the information it provides on biological samples. The present study reports on the use of polarized quasi-elastic neutron scattering (QENS) and the application of a minimalistic model adapted to both individual and collective dynamics. Using a perdeuterated green fluorescent protein as a model globular protein, the study provides an interpretation of the dynamical parameters obtained with QENS, and a comparative study of the Elastic Coherent and Incoherent Scattering Factor. Based on both experiments and calculations, we discuss the relative importance of distinct and self components of coherent scattering, which is often wrongly assumed to be representative of collective dynamics only. The results highlight the current impediments rendering complicated a straightforward analysis of fast collective dynamics in hydrated protein samples.

Microplicae are ridge-like membrane projections that are prominent features of many epithelial surfaces, yet little is known about the principles governing their spatial organisation. Determining whether microplicae represent stochastic membrane folds or biologically organised surface architectures is essential for understanding their formation and functional roles. Here, differential interference contrast images of human buccal epithelial cells were analysed using quantitative image-processing approaches. Ridge networks were segmented and characterised using complementary measurements of characteristic wavelength, including medial-axis and nearest-neighbour Voronoi analyses, together with skeleton-based metrics describing network architecture. Analysis of n=100 buccal epithelial cells sampled from n=10 donors revealed a reproducible sub-micron characteristic wavelength. Mean medial-axis spacing was 0.511 {+/-} 0.042 {micro}m and mean Voronoi nearest-neighbour spacing was 0.588 {+/-} 0.057 {micro}m. Characteristic wavelength exhibited CV of between only 8.26% and 9.67% across the dataset. However, metrics describing network architecture, including ridge density, branching and connectivity, varied by up to 109%. Donor-level analysis reported the same overall trends, with conservation of the characteristic wavelength while network parameters had considerably greater variation. These findings identify a previously unrecognised organising principle of microplical architecture, suggesting that epithelial membrane organisation is regulated through conservation of an intrinsic geometric length scale while network topology remains comparatively free to remodel.

The rising incidence of invasive fungal diseases emphasizes the need for novel therapeutic strategies, including membrane-targeting antifungal agents, which require representative lipid models for detailed molecular-level studies. In this work, we propose a consensus quinary fungal plasma membrane model based on lipidomic literature data, specifically PC:PE:PI:PA:PS phospholipid model with ratio of 44:29:13:8:6. Using a bottom-up approach, we characterized the biophysical properties of this system - with particular emphasis on mechanical parameters such as bending rigidity and area compressibility - by combining molecular dynamics simulations with experimental flicker-noise and ATR-FTIR spectroscopies. Furthermore, we investigated the effect of two key non-phospholipid components: ergosterol and triacylglycerols. Biophysical analysis revealed that DPPI and its specific interactions with DSPS induced the most substantial deviations in baseline membrane parameters, particularly area per lipid, membrane thickness, and area compressibility, while DSPS influenced bending rigidity change and DLiPA primarily affected lipid packing defects. In addition, ergosterol and TGs were found to influence all of the investigated parameters to different degree. Notably, the overall biophysical profile of the proposed FPMM closely mimicked that of natural vesicles derived from yeast lipid extracts, establishing this model may provide a reliable platform for studying fungal membrane biophysics and lipid-targeting interactions.

Obtaining sufficient amounts of pure protein for downstream applications such as native mass spectrometry (nMS) is often challenging, especially when expression yields are low or proteins are unstable. In these cases, the commonly required buffer-exchange step is a major bottleneck, as it often leads to substantial protein loss and compromises biophysical characterization. These challenges are exacerbated in insect or eukaryotic expression systems, where protein yields are typically lower than in bacteria, making protein loss during purification particularly detrimental. Standard lysis and purification buffers contain non-volatile components such as Tris, phosphate, HEPES and sodium chloride, which form adducts during electrospray ionization (ESI) interfering with the signal and therefore must be re-moved prior to nMS. To address protein loss associated with this mandatory buffer-exchange, we evaluated an affinity-purification workflow, in which non-volatile salts are excluded throughout purification and proteins are directly eluted into nMS-compatible ammonium acetate-based buffers. This approach eliminates the need for a separate buffer exchange step and enables rapid nMS analysis immediately after affinity purification. We show that common eluents used in His- and Strep- based affinity purification, such as imidazole, biotin, and desthiobiotin, are well tolerated at relevant concentrations, allowing acquisition of high-quality spectra suitable for determining protein stoichiometry and for monitoring enzymatic or assembly processes. Together, this fast-track affinity workflow increases protein recovery, shortens sample preparation and complements online exchange protocols, which are less suited for monitoring processes. It hence expands the applicability of nMS to proteins and protein complexes that are difficult to obtain in sufficient quantity using conventional purification and buffer exchange strategies.

Cardiolipin (CL) is a phospholipid found in the inner mitochondrial membrane (IMM) where it increases the efficiency of ATP regeneration. We have investigated the hypothesis that this increase may result in part from CL concentrating H+ at the IMM surface through electrostatic interactions as the CL polar head is a dianion at physiological pH. To this aim, we compared the concentrations and movements of H+ at the surface of giant planar phosphatidylcholine (PC) membranes and 20% CL enriched PC membranes by recording their surface pH with the membrane-grafted pH probe fluorescein DHPE. CL enrichment of the membranes increased their surface H+ activity by a ~4 factor. Moreover, we observed non-gaussian spatial H+ concentration profiles with distance from a point H+ source with both PC and CL membranes suggesting that both lipids also induce interactions between probe molecules. A whole bath pH variation revealed that these interactions allow the traveling of reversible acidification fronts with constant speed over the membrane between high and low pH states. A reaction-diffusion model of these observations suggests that membranes support these fronts through a mechanism of autocatalytic (de)protonation of the membrane surface. In mitochondria, these fronts would result in transitions between high and low pH states, the low one having a larger H+ concentration in CL-enriched regions of the IMM. Such an increase at the inner leaflet of the IMM may increase efficiency of the respiratory chain whereas the increase at the outer leaflet may boost the ATP synthase rate.

Tumor spheroid mechanics arise from both the mechanical properties of individual cells and the adhesive interactions that organize them into tissues. The relative contribution of these two factors to the bulk mechanical behavior, however, remains difficult to disentangle experimentally. Here, we develop a computational model of micropipette aspiration to compare the mechanical response of isolated cells and multicellular spheroids within a common computational framework. By independently varying single-cell stiffness and cell-cell adhesion, we quantify their effects on aspiration dynamics, effective elastic modulus, and viscoelastic relaxation. Our results show that increasing single-cell stiffness substantially alters the mechanics of isolated cells but has limited influence on the effective elastic modulus of multicellular spheroids. In contrast, changes in cell-cell adhesion produce pronounced effects on spheroid effective elastic modulus. Nevertheless, both parameters increase the retardation time governing the transition from the initial elastic response to long-time viscous deformation. These findings suggest that multicellular elasticity is governed primarily by intercellular mechanical coupling, whereas the dynamical response to applied stress depends jointly on cell-scale mechanics and cell-cell adhesion.

Interleukin-13 (IL-13) is an immunomodulatory cell signaling cytokine that has been implicated in neurodegenerative disease and chronic inflammation. IL-13 binds to its low and high affinity receptors, IL-13 receptor 1 (IL-13R1) and IL-13 receptor 2 (IL-13R2), respectively, with residence times that vary accordingly. As the binding kinetics of the cytokine-receptor complexes influence cellular responses, we employed the molecular dynamics (MD) simulation-based{tau} -random acceleration molecular dynamics method ({tau}RAMD) to compute relative residence times for wild-type (WT) IL-13 and 19 IL-13 mutants to the two receptors. Comparison with experimental kinetic data shows that the{tau} RAMD computations capture the trends in residence times. Analysis of simulated dissociation trajectories of the cytokine-receptor complexes reveals two distinct dissociation pathways of IL-13 from each of the receptors. This study thus pinpoints key determinants of the interaction of IL-13 with its receptors which could be targeted for therapeutic design. Statement of SignificanceCytokines are regulatory proteins that bind to cell surface receptors and thereby send signals to the cellular interior. Interleukin-13 (IL-13) is a cytokine that has a low and a high affinity receptor. It has important physiological roles, and its deregulation is involved in diseases such as atopic dermatitis and asthma. We employed a molecular dynamics simulation-based method to compute the effects of changes in the sequence of IL-13 on the lifetimes of complexes of IL-13 and its receptors. Comparison with experiments supports the validity of the computational approach and analysis of the simulations reveals two distinct ways in which IL-13 dissociates from each receptor. These results thus provide a map for targeting IL-13 - receptor interactions for the design of therapeutics.

Low-density lipoprotein (LDL) is a major atherogenic lipoprotein, yet its potential to directly modify the fibrin scaffold of blood clots is incompletely understood. Here, we investigated how LDL alters plasma fibrin network architecture and internal fibrinolysis across defined fibrinogen/thrombin conditions. Pooled normal human plasma was supplemented with LDL and clotted with controlled concentrations of fibrinogen and thrombin. Fibrin architecture was visualized by confocal microscopy and quantified by pore-size analysis; clot formation and lysis were monitored turbidimetrically in the presence of tissue plasminogen activator (tPA). Increasing LDL produced a pronounced reduction in fibrin-network pore size across the tested fibrinogen/thrombin conditions. The LDL dependence of pore diameter was well described by a power-law relationship, D_pore=(6.54 +/- 0.11)[LDL]^(-0.12 +/- 0.02) , (R^2 = 0.90), with a significant negative LDL exponent (p = 4 x 10^5). Increasing LDL also prolonged clot lysis time and altered turbidity kinetics. These findings extend epidemiologic and clinical associations between ApoB-containing lipoproteins and hypofibrinolytic clot phenotypes by demonstrating, in a controlled plasma system, that LDL itself can modify fibrin network architecture and fibrinolytic susceptibility. The results support a structure-function role for LDL within the fibrin biomaterial and motivate direct tests of LDL incorporation, protofibril packing, fibrinolytic-protein binding, and single-fiber mechanics.

Diffusion within the cytoplasm is fundamental to numerous biological processes. Fluorescence recovery after photobleaching (FRAP) is one of the most common method for quantifying molecular diffusivity in living cells using standard laser scanning confocal microscopy (LSCM). However, accurately measuring fast cytoplasmic diffusion (typically >10 m^2/s) is challenging due to rapid recovery kinetics, weak signal-to-noise ratios, post-bleach signal artifacts, and spatial restrictions affecting normalization. While individual challenges have been addressed in specific contexts, a simple and robust framework to quantify cytoplasmic diffusivity remains elusive. Here, we present a FRAP methodology specifically designed to overcome these obstacles. By utilizing the Gaussian function -- the impulse response (ImpRes) of the diffusion equation in an infinite medium -- our approach leverages the full spatiotemporal dataset through a single-equation three-parameter fitting procedure, thus releasing restrictions to small regions of interest and arbitrary initial time-points. The methodology was validated on three datasets of increasing complexity: in silico simulated recovery profiles, in vitro data from FITC-dextran in glycerol solution, and live-cell imaging of free cytoplasmic GFP. Systematic comparison with existing models demonstrates that the ImpRes approach significantly reduces sensitivity to noise and imperfect fluorescence normalization, while remaining robust against short-term biases, such as transient probe photo-activation. Given its robustness under realistic experimental conditions and its ease of implementation, the proposed FRAP methodology provides a reliable tool for quantitative cytoplasmic analysis.

Synapsin-1 is a multidomain neuronal protein containing extensive intrinsically disordered regions and is a key component of synaptic-vesicle condensates. Direct residue-level simulation of the collective organization of thousands of synapsin molecules remains computationally demanding. Here, we develop a coarse-grained description that connects residue-level CALVADOS 3 simulations to a one-particle-per-protein model. A potential of mean force between two synapsin molecules is obtained by umbrella sampling and represented by an isotropic effective interaction containing a short-range attractive region and a weak outer repulsive contribution. We compare two treatments of this interaction that differ only in the retention of the outer tail. Langevin dynamics simulations of effective proteins show aggregation upon cooling and compression in both models, but with markedly different collective organization. The shorter-ranged model progressively coarsens toward a single dense domain, whereas retaining the outer repulsive contribution favors the persistence of multiple mesoscale aggregates. The two models also display distinct relationships between aggregate size and particle mobility at low temperature. These results show that weak features of an effective protein-protein interaction can have pronounced consequences for collective synapsin organization at mesoscopic scales. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/745062v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@854288org.highwire.dtl.DTLVardef@d2fc52org.highwire.dtl.DTLVardef@1b37d5aorg.highwire.dtl.DTLVardef@eac583_HPS_FORMAT_FIGEXP M_FIG C_FIG

During the influenza viral life cycle, the viral glycoprotein hemagglutinin (HA) mediates binding, entry, and fusion. Densely packed clusters of HA trimers at the plasma membrane are required to produce infectious virions; however, the mechanism of HA clustering is still unknown. We have shown previously that HA co-clusters with and modulates phosphatidylinositol 4,5-bisphosphate (PIP2) in host cell plasma membranes (PM). Here, we further characterize the relationship between HA and PIP2 using molecular dynamics simulations (MD) and fluorescence photoactivation localization microscopy (FPALM) to elucidate a mechanism of HA-PIP2 interaction. We found that the interaction occurs largely between the PIP2 head group and the cytoplasmic tail domain (CTD) of HA. Mutations of the CTD were made to alter charge (HARE, HARREQ), palmitoylation sites (HAMAY), or a combination thereof (HAREMAY, RREQMAY). MD showed that HARREQ and RREQMAY had the strongest effect on HA-PIP2 interactions through a depletion in the radial distribution function of PIP2 around HA at distances [≤]2.5 nm. FPALM revealed that HA cluster density at the PM was significantly reduced by CTD mutations, with the largest reduction occurring in mutants where the CTD charge and acylation were both altered (HAREMAY). HAREMAY clusters were also found to have larger circularities and perimeters, implying a structural change to the clusters. Mutations in the HA transmembrane domain also caused modest changes to the cluster properties of HA and its co-clustering with PIP2. FPALM showed PIP2 co-clustering with HA was also affected by HA mutations with more free PIP2 localized under HAREMAY clusters. A chemical model of simultaneous HA-PIP2 and PH-PIP2 binding enables interpretation of HA-PIP2 interactions and reveals quantitative differences between PIP2 binding by HA CTD mutants. We conclude that the mechanism of HA-PIP2 interaction consists of at least electrostatic and hydrophobic components. Our insights into the mechanism of HA-PIP2 interaction, and the prevalence of putative PIP2-interacting domains in a number of viral spike proteins suggest it may be fruitful to identify methods of disrupting interactions between phosphoinositides and viral proteins.

While movement variability is a natural element of human expression, in sign languages it may affect mutual understanding, learning, and potential overuse injury. Sign language variability is not well-understood in part because quantitative analytical methods are yet to be clearly defined. Hence the aim of this study was to assess intra-subject reliability across repeated sessions for three signers, to identify features sensitive to experience-related differences in motor control consistency, and to establish movement consistency metrics for treating sign language kinematic differences as linguistically meaningful. Three signers were assigned to three different proficiency levels of sign language: Deaf (D), proficient (P), and student (S). Sign production variables were evaluated using intraclass correlation coefficients (ICCs) and coefficients of variation(CVs).Most kinematic features showed good to excellent ICCs such as duration, path length, signing space volume, and average and peak velocity. Some EMG features such as mean forearm amplitudes and co-contraction also showed good to excellent ICCs. These data can be used to improve the scientific investigation of sign languages, improve educational resources, and establish baseline thresholds to inform ergonomic or scheduling guidelines for interpreters.

Cellular systems must act robustly to maintain organismal health, including maintaining biophysical properties that allow for appropriate cellular function, and adapting these properties through changes such as those that occur during cell division. However, we still lack tools to measure many of these physical properties with precision in the living cell. For example, the mechanical properties of the nucleoplasm, the fluid-like substance that fills the nucleus, have not been fully characterized. To investigate these properties, we have turned to the fission yeast Schizosaccharomyces pombe (S. pombe), a well-established, genetically tractable model organism that has been used extensively for studying a variety of cell biophysical processes and structures, including the cytoskeleton and cell division. It is an apt system for studying how the nucleus adapts over the course of the cell cycle, since it undergoes closed mitosis, where the nuclear envelope remains intact during cell division. Studying nucleoplasm properties over the course of closed mitosis may help reveal how nuclear volume, shape, surface area expansion, and chromosome segregation are linked and coordinated. To measure nucleoplasm material properties in S. pombe, we have paired Fluorescence Correlation Spectroscopy (FCS) with a photoswitchable fluorophore, enabling fine control over fluorescent intensity inside live cells. We infer material properties from FCS measurements, while the photoswitchable probe enables confocal imaging in conjunction with these measurements, yielding corresponding information about cellular state and dynamics. Interestingly, we find that nucleoplasm material properties do not vary significantly over the cell cycle. Future studies will use this tool to examine how diverse molecular and genetic perturbations alter nucleoplasmic properties, providing insight into how these properties maintain nuclear function and protect genomic integrity over the cell cycle and during development.

Fingertip friction plays a central role in tactile exploration and object manipulation. During sliding, tangential force depends jointly on the real contact area and the interfacial shear stress, both of which can be influenced by sliding conditions. However, changes in fingertip friction are often interpreted primarily through changes in real contact area, whereas the accompanying changes in interfacial shear stress remain less well characterized. This gap is especially relevant for electrostatic surface haptic displays, which modulate fingertip friction by applying a voltage between the finger and the touch surface. Here, we experimentally quantify the mean interfacial shear stress of a sliding fingertip on an electrostatically actuated touchscreen using simultaneous measurements of tangential force and optically resolved real contact area. Ten participants performed sliding trials across three speeds and three normal forces with and without electrostatic actuation. Interfacial shear stress increased with speed and decreased with normal force; in both cases, these trends arose because real contact area varied more strongly than tangential force. Electrostatic actuation further reduced interfacial shear stress, as increasing voltage produced a larger increase in real contact area than in tangential force. These findings show that interfacial shear stress varies systematically with sliding conditions and electrostatic actuation, clarifying how changes in real contact area and interfacial shear stress combine to shape fingertip-surface friction.

Recent experiments show that protein condensates sitting on opposite surfaces of a flat lipid membrane move together and prefer to overlap, even though they cannot touch each other. This points to an indirect, membrane-mediated interaction. Two mechanisms could be responsible: a curvature-induced interaction, which is energetic in origin, and a fluctuation-induced interaction, which is entropic. Here we study both with coarse-grained molecular dynamics simulations, using Cookes implicit-solvent lipid model together with a generic bead-spring polymer model for the condensate. We compute the potential of mean force between two condensates across the membrane. For condensates of the same size, full overlap is unfavorable, and the pair instead settles into a partially overlapping state that bends the membrane into an S-like shape. When the two condensates differ strongly in size, full overlap becomes favorable. We explain this with a simple geometric picture. The condensate wets the membrane as a thin film and imposes curvature only along its rim, while membrane tension flattens the membrane under its interior. The resulting ring of curvature can trap a smaller condensate on the opposite side. We also compare the bending undulations and the effective bending modulus of a bare membrane, a membrane with one condensate, and a membrane with condensates on both sides. A wetting condensate suppresses the undulation modes and stiffens the membrane, but whether this makes overlap entropically favorable remains inconclusive. Our results indicate that the coupling is driven mainly by curvature, and that it depends on the wetting mechanism and on the membrane tension.

Monitoring pH and extracellular acidification rate (ECA) in biological samples containing live mammalian cells can provide valuable information on the glycolytic activity and bioenergetic status of cells. Compared to pH electrodes, optochemical pH sensors look more advantageous, since they allow rapid, non-invasive parallel analysis of multiple samples with stable readout of pH. We have developed new fluorescent pH sensors based on hydrophobic protonable metal-free porphyrins,OEP and OEPK, embedded in a plasticized PVC matrix containing a proton transfer agent. These pH sensors provide internally-referenced calibration-free operation, both in ratiometric intensity and lifetime-based detection modes. Sensor development included optimization of the indicator dye and its photophysical characteristics, screening of different proton transfer agents to minimize sensor toxicity, tuning of the protonation range and pKa, long-term storage stability and response time studies. Optimised pH sensor coatings were then deposited on plastic substrates (96-well microplates) and used for real-time monitoring of Extracellular Acidification Rate (ECAR) for cultured cancer cells and 3D spheroid structures on standard laboratory equipment (multi-label plate reader and confocal FLIM microscope). The advanced pH sensors tailored for use with biological samples have high potential for cell analysis and related applications.

Nanodiscs and bicelles are widely used as membrane mimetics for structural studies of membrane-associated systems. Studies have reported that their magnetic alignment behavior and phase stability are highly sensitive to composition and temperature. In this study, we systematically investigate the effects of cholesterol on bicelle formation and magnetic alignment in DMPC + 0.2 glycyrrhizic acid (GA) systems using a combined 31P and 14N solid-state NMR experimental and simulation-based approach. Temperature dependent 31P NMR spectra reveal a clear transition from vesicle dominant to aligned bicelles/nanodsics phase, while 1N quadrupolar splitting and lineshape analysis provides quantitative insights into heterogeneous lipid bilayer populations, distinguishing large aligned nanodiscs (B(L)), small nanodiscs (B(S)), and isotropic/random components (B(R)). A strong correlation is observed between the 31P derived bicelle fraction and the 14N B(L) population, confirming that macroscopic alignment in the presence of an external magnetic field directly reflects the growth of large, well-ordered nanodiscs. Cholesterol is found to play a critical dual role by modulating membrane order and curvature. At low cholesterol concentration (0 to 5 mole percent), nanodiscs alignment occurs gradually with increasing temperature, while at higher cholesterol concentration (15 to 25 mole percent), the alignment is delayed and accompanied by broader spectral features, indicating structural heterogeneity. Notably, 10 mole percent cholesterol consistently provides the optimal balance, enabling efficient temperature dependent conversion to aligned bicelles while maintaining high B(L) populations (about 70-80 percentage) and minimal isotropic fractions. In contrast, higher cholesterol maintains significant B(S) and B(R) populations, even at elevated temperature. The 14N quadrupolar coupling (Cq is approximately 8.5 to 9.2 kHz for aligned nanodiscs) remains nearly invariant across compositions, showing that cholesterol does not change local headgroup dynamics but instead redistributes lipid populations. These findings establish a combined 31P and 14N solid -state NMR approach provides a valuable platform for quantitatively correlating membrane structure, dynamics, and alignment, offering practical guidelines for optimizing bicelle systems for high resolution solid-state NMR studies of membrane associated biomolecules.