Search Results (87)

Endothelial hyperpermeability is a hallmark of diverse inflammatory and vascular pathologies, including sepsis, acute respiratory distress syndrome (ARDS), ischemia–reperfusion injury, and atherosclerosis. Traditionally considered a passive return to baseline following stimulus withdrawal, barrier recovery is now recognized as an active, endothelial-driven process. Earlier work identified individual components of this restorative phase, such as cyclic adenosine monophosphate (cAMP)/exchange protein directly activated by cAMP 1 (Epac1) signaling, Rap1/Rac1 activation, vasodilator-stimulated phosphoprotein (VASP) phosphorylation, and targeted cytoskeletal remodeling, as well as kinase pathways involving PKA, PKG, and Src. However, these were often regarded as discrete events lacking a unifying framework. Recent integrative analyses, combining mechanistic insights from multiple groups, reveal that nitric oxide (NO) generated early during hyperpermeability can initiate a delayed cAMP/Epac1 cascade. This axis coordinates Rap1/Rac1-mediated cortical actin polymerization, VASP-driven junctional anchoring, retro-translocation of endothelial nitric oxide synthase (eNOS) to caveolar domains, PP2A-dependent suppression of actomyosin tension, and Krüppel-like factor 2 (KLF2)-driven transcriptional programs that sustain endothelial quiescence. Together, these pathways form a temporally orchestrated, multi-tiered “inactivation” program capable of restoring barrier integrity even in the continued presence of inflammatory stimuli. This conceptual shift reframes NO from solely a barrier-disruptive mediator to the initiating trigger of a coordinated, pro-resolution mechanism. The unified framework integrates cytoskeletal dynamics, junctional reassembly, focal adhesion turnover, and redox/transcriptional control, providing multiple potential intervention points. Therapeutically, Epac1 activation, Rap1/Rac1 enhancement, RhoA/ROCK inhibition, PP2A activation, and KLF2 induction represent strategies to accelerate endothelial sealing in acute microvascular syndromes. Moreover, applying these mechanisms to arterial endothelium could limit low-density lipoprotein (LDL) entry and foam cell formation, offering a novel adjunctive approach for atherosclerosis prevention. In this review, we will discuss both the current understanding of endothelial hyperpermeability mechanisms and the emerging pathways of its active inactivation, integrating molecular, structural, and translational perspectives. Full article

The melting behavior of alkanes plays a critical role in a wide field of applications. While experimental studies have established the occurrence of premelting phenomena in both short- and long-chain alkanes, molecular-level insights remain limited. In this work, we employ coarse-grained molecular dynamics simulations to investigate the melting behavior of high-molecular-weight alkanes, with a particular focus on continuous premelting dynamics in the transition regime toward polymer-like systems. By simulating alkane chains of varying lengths and analyzing temperature-dependent structural changes, we identify a crossover from discrete phase transitions to a gradual premelting process beyond chain lengths of $N\approx 40$ coarse-grained beads. The extrapolation of melting temperatures to zero heating rate yields values that agree well with the experimental data for the longest simulated chains. Compared to previous simulation studies, the slower heating rates used here offer enhanced quantitative agreement. Overall, the results provide new molecular-level insights into the melting of long-chain alkanes and highlight the utility of coarse-grained models in capturing complex phase behavior. Full article

Water’s unique physicochemical properties arise from its dynamic hydrogen-bonding network, yet the precise molecular threshold at which these cooperative behaviors emerge remains a key question. This study employed nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) calculations to investigate the evolution of hydrogen bonding strength in small water clusters, ranging from dimers to pentamers. The observed exponential increase in NMR chemical shift up to the pentamer reflects growing hydrogen bond cooperativity, identifying the (H₂O)₅ cluster as a critical structural and energetic threshold. At this size, the network achieves sufficient connectivity to support key bulk-like phenomena such as proton transfer and dielectric relaxation. These conclusions were corroborated by complementary FT-IR and electrochemical impedance spectroscopy (EIS) measurements of bulk water. Our results position the water pentamer as the molecular onset of emergent solvent behavior, effectively bridging the divide between discrete clusters and the macroscopic properties of liquid water. Full article

Traditional pre-clinical drug evaluation methods, including animal experiments and static cell cultures using human-derived cells, face critical limitations such as interspecies differences, ethical concerns, and poor physiological relevance. More recently, microphysiological systems (MPSs) that use microfluidic devices to mimic in vivo conditions have emerged as promising platforms. By enabling perfusion cell culture and incorporating human-derived cells, MPSs can evaluate drug efficacy and toxicity in a more human-relevant manner. However, standard MPS protocols rely on discrete medium changes, causing abrupt changes in drug concentrations that do not reflect the continuous pharmacokinetics seen in vivo. To overcome this limitation, we developed a Dialysis Membrane-integrated Microfluidic Device (DMiMD) which maintains continuous drug concentrations through selective medium change via a dialysis membrane. The membrane’s molecular weight cut-off (MWCO) enables the retention of high-molecular-weight drugs while facilitating the passage of essential low-molecular-weight nutrients such as glucose. We validated the membrane’s molecular selectivity and confirmed effective nutrient supply using cells. Additionally, anticancer drug efficacy was evaluated under continuously changing drug concentrations, demonstrating that the DMiMD successfully mimics in vivo drug exposure dynamics. These results indicate that the DMiMD offers a robust in vitro platform for accurate assessment of drug efficacy and toxicity, bridging the gap between conventional static assays and the physiological complexities of the human body. Full article

The effects of proline co-solvent on helix folding are explored through the single discrete coordinate of the number of helical hydrogen bonds. The analysis is based on multi-microsecond length molecular dynamics simulations of alanine-based helix-forming peptides, (ALA)n, of length n = 4, 8, 15 and 21 residues, in an aqueous solution with 2 M concentration of proline. The effects of addition of proline on the free energy landscape for helix folding were analyzed using the graph-based Dijkstra algorithm, Optimal Dimensionality Reduction kinetic coarse graining, committor functions, as well as through the diffusion of the helix boundary. Viewed at a sufficiently long time-scale, helix folding in the coarse-grained hydrogen bond space follows a consecutive mechanism, with well-defined initiation and propagation phases, and an interesting set of intermediates. Proline addition slows down the folding relaxation of all four peptides, increases helix content and induces subtle mechanistic changes compared to pure water solvation. A general trend is for transition state shift towards earlier stages of folding in proline relative to water. For ALA5 and ALA8 direct folding is dominant. In ALA8 and ALA15 multiple pathways appear possible. For ALA21 a simple mechanism emerges, with a single path from helix to coil through a set of intermediates. Overall, this work provides new insights into effects of proline co-solvent on helix folding, complementary to more standard approaches based on three-dimensional molecular structures. Full article

Bacterial outer membrane vesicles (OMVs) are nanoscale extracellular structures produced by Gram-negative bacteria that are critical for microbial biology and host-pathogen interactions and have great potential in biotechnological applications. Despite the availability of fluorescent dyes for OMV studies, many are repurposed from eukaryotic extracellular vesicle research and are not explicitly optimized for OMVs, leading to challenges in achieving consistent labeling, minimizing background noise, and preserving vesicle integrity during analyses. This study evaluates B2, a benzimidazole-derived fluorophore, for OMV labeling in advanced techniques like flow cytometry and confocal microscopy. OMVs were isolated from Escherichia coli strains BL21 and O157, and their integrity was confirmed using transmission electron microscopy (TEM). B2 staining protocols were optimized for OMVs, and fluorescence analyses revealed specific interactions with the vesicle membranes, reducing aggregation and enhancing signal uniformity. Flow cytometry indicated near-complete labeling efficiency (98–100%) with minimal background interference. Confocal microscopy further validated B2’s effectiveness, showing evident OMV internalization into epithelial HT-29 cells and compatibility with other fluorophores. Density functional theory (DFT) calculations, including Fukui function analysis, identified key electrophilic and nucleophilic regions in B2 that facilitate specific hydrogen bonding and polar interactions with membrane components. Non-covalent interaction (NCI) analysis revealed pronounced intramolecular hydrogen bonding along with discrete regions of weak van der Waals interactions. Molecular dynamics simulations suggest that B2 exhibits an affinity for both the hydrophobic core of the lipid bilayer and the core oligosaccharide region of the LPS layer, which collectively ensures sustained retention of the dye. The findings presented in this study position B2 as a valuable fluorophore for OMV research. Full article

The excellent lubrication and load-bearing synergistic modulation of the meshing interface has been well recognized, as the microtextured tooth surface seems to be a punished area in deep-sea gear thermal elastohydrodynamic lubrication (TEHL). This is mainly because of the traditional perception of the anti-scuffing load-bearing capacity (ASLBC) and the similarity of the interfacial microelement configurations. Microtextured contact can be applied to the meshing interface to adjust the time-varying TEHL characteristics and enhance the meshing load-bearing performance. In this study, the analytical homogeneous equivalent micro-hydrodynamic contact multiscale parameters are determined, and the dispersed micro-flow real distribution area of the texturing interface is indicated, revealing the TEHL friction characteristics of the rolling–sliding line contact microelement, which is regarded as a bridge connecting the micro-dynamic pressure discrete contact friction behavior and the TEHL textured interface meshed-gear load-bearing. The contact model mentioned theoretically predicts the evolutionary time-varying characteristics of the micro-thermoelastic lubrication behavior of the textured contact interface under hydrodynamic conditions and demonstrates that the microtextured configuration parameters of the molecular scale meshing interface are the most influential structural parameters for the load-bearing problem of the homogeneous flow pressure film layer between the gear pair tooth surfaces, especially for deep-sea gear meshing load-bearing reliability under limited lubrication space. Full article

Understanding the behavior of fluid flow and solute transport in fractured rock is of great significance to geoscience and engineering. The discrete fracture network is the predominate channel for fluid flow through fractured rock as the permeability of fracture is several magnitudes higher than that of the rock matrix. As the basic components of the fracture network, investigating the fluid flow in crossed fractures is the prerequisite of understanding the fluid flow in fractured rock. First, a program based on the successive random addition algorithm was developed to generate rough fracture surfaces. Next, a series of fracture models considering shear effects and different surface roughness were constructed. Finally, fluid dynamic analyses were performed to understand the role of flowrate and surface roughness in the evolution of flow field, concentration field, solute breakthrough, and solute mixing inside the crossed fractures. Results indicated that the channeling flow at the fracture intersection became more pronounced with the increasing Péclet number (Pe) and Joint Roughness Coefficient (JRC), the evolution of the concentration field was influenced by Pe and the distribution of the concentration field was influenced by JRC. For Pe < 10, the solute transport process was dominated by molecular diffusion. For 100 > Pe > 10, the solute transport process was in the complete mixing mode. In addition, for Pe > 100, the solute transport process was in the streamline routing mode. The concentration distribution was affected by the local aperture at the fracture intersection corresponding to different surface roughness. Meanwhile, the solute mixing equation was improved based on this result. The research results are beneficial for further revealing the mechanism of fluid flow and solute transport phenomenon in fractured rock. Full article

Adult polyphenism is a prevalent form of adaptive evolution that enables insects to generate discrete phenotypes based on environmental factors. However, the morphology and molecular mechanisms underlying adult dimorphism in Callosobruchus maculatus (a global storage pest) remain elusive. Understanding these mechanisms is crucial for predicting the dispersal and population dynamics of C. maculatus. This knowledge can also provide a theoretical basis for biological control strategies. In this study, we compared the morphology of the hind wing and chest muscles, the transcriptional profiles, the energy metabolism substances, and the fecundity between the flight form and the normal form. The flight form displays a lighter overall appearance with small black spots, while the normal form lacks most flight muscles. Moreover, there are differences in the energy metabolism pathways between the two forms, including carbohydrate metabolism and oxidative phosphorylation. The flight form exhibits higher contents of carbohydrates, lipids, and mitochondrial energetic storage. The normal form exhibits better fertility but has lost its ability to fly. This is the first study to analyze the morphology and molecular characteristics of adult polyphenism in C. maculatus using morphological, physiological, and behavioral approaches, providing a foundational understanding of these aspects. Our study on C. maculatus also provides supporting evidence of a trade-off between dispersion and reproduction, where the flight form is capable of flying while the normal form has more reproductive benefits. Full article

Biochemical reaction systems in a cell exhibit stochastic behaviour, owing to the unpredictable nature of the molecular interactions. The fluctuations at the molecular level may lead to a different behaviour than that predicted by the deterministic model of the reaction rate equations, when some reacting species have low population numbers. As a result, stochastic models are vital to accurately describe system dynamics. Sensitivity analysis is an important method for studying the influence of the variations in various parameters on the output of a biochemical model. We propose a finite-difference strategy for approximating second-order parametric sensitivities for stochastic discrete models of biochemically reacting systems. This strategy utilizes adaptive tau-leaping schemes and coupling of the perturbed and nominal processes for an efficient sensitivity estimation. The advantages of the new technique are demonstrated through its application to several biochemical system models with practical significance. Full article

In previous work, we investigated thermodynamic processes in systems at the mesoscopic level where traditional thermodynamic descriptions (macroscopic or microscopic) may not be fully adequate. The key result is that entropy in such systems does not change continuously, as in macroscopic systems, but rather in discrete steps characterized by the quantization constant $\beta$. This quantization reflects the underlying discrete nature of the collision process in low-dimensional systems and the essential role played by thermodynamic fluctuations at this scale. Thermodynamic variables conjugate to the forces, along with Glansdorff–Prigogine’s dissipative variable can be discretized, enabling a mesoscopic-scale formulation of canonical commutation rules (CCRs). In this framework, measurements correspond to determining the eigenvalues of operators associated with key thermodynamic quantities. This work investigates the quantization parameter $\beta$ in the CCRs using a nano-gas model analyzed through classical statistical physics. Our findings suggest that $\beta$ is not an unknown fundamental constant. Instead, it emerges as the minimum achievable value derived from optimizing the uncertainty relation within the framework of our model. The expression for $\beta$ is determined in terms of the ratio $\chi$, which provides a dimensionless number that reflects the relative scales of volume and mass between entities at the Bohr (atomic level) and the molecular scales. This latter parameter quantifies the relative influence of quantum effects versus classical dynamics in a given scattering process. Full article

The presented work concerns computational investigations of the physical properties of composite materials based on polymer matrix and nonlinear optical (NLO) active chromophores. The structural, electronic, and optical properties of selected tetrathiafulvalene (TTF)-based chromophores have been calculated using quantum chemical methods. The polymer matrix changes the physical properties of the inserted chromophores influencing their optical parameters. To explain the mechanism of the NLO signal occurrence from the composites based on poly(methyl methacrylate) (PMMA) matrix and TTF chromophores, their structures are modeled using the classical molecular dynamics. In consequence, the structural properties of the composites are discussed according to the NLO requirements. By developing the theoretical model based on a discrete multipole local field approach, the impact of polymer matrix on the optical properties of chromophores is explained. Full article

In eukaryotic cells, gene transcription typically occurs in discrete periods of promoter activity, interspersed with intervals of inactivity. This pattern deviates from simple stochastic events and warrants a closer examination of the molecular interactions that activate the promoter. Recent studies have identified transcription factor (TF) clusters as key precursors to transcriptional bursting. Often, these TF clusters form at chromatin segments that are physically distant from the promoter, making changes in chromatin conformation crucial for promoter–TF cluster interactions. In this review, I explore the formation and constituents of TF clusters, examining how the dynamic interplay between chromatin architecture and TF clustering influences transcriptional bursting. Additionally, I discuss techniques for visualizing TF clusters and provide an outlook on understanding the remaining gaps in this field. Full article

Our study aims to address the methodological challenges frequently encountered in RNA-Seq data analysis within cancer studies. Specifically, it enhances the identification of key genes involved in axillary lymph node metastasis (ALNM) in breast cancer. We employ Generalized Linear Models with Quasi-Likelihood (GLMQLs) to manage the inherently discrete and overdispersed nature of RNA-Seq data, marking a significant improvement over conventional methods such as the t-test, which assumes a normal distribution and equal variances across samples. We utilize the Trimmed Mean of M-values (TMMs) method for normalization to address library-specific compositional differences effectively. Our study focuses on a distinct cohort of 104 untreated patients from the TCGA Breast Invasive Carcinoma (BRCA) dataset to maintain an untainted genetic profile, thereby providing more accurate insights into the genetic underpinnings of lymph node metastasis. This strategic selection paves the way for developing early intervention strategies and targeted therapies. Our analysis is exclusively dedicated to protein-coding genes, enriched by the Magnitude Altitude Scoring (MAS) system, which rigorously identifies key genes that could serve as predictors in developing an ALNM predictive model. Our novel approach has pinpointed several genes significantly linked to ALNM in breast cancer, offering vital insights into the molecular dynamics of cancer development and metastasis. These genes, including ERBB2, CCNA1, FOXC2, LEFTY2, VTN, ACKR3, and PTGS2, are involved in key processes like apoptosis, epithelial–mesenchymal transition, angiogenesis, response to hypoxia, and KRAS signaling pathways, which are crucial for tumor virulence and the spread of metastases. Moreover, the approach has also emphasized the importance of the small proline-rich protein family (SPRR), including SPRR2B, SPRR2E, and SPRR2D, recognized for their significant involvement in cancer-related pathways and their potential as therapeutic targets. Important transcripts such as H3C10, H1-2, PADI4, and others have been highlighted as critical in modulating the chromatin structure and gene expression, fundamental for the progression and spread of cancer. Full article

Alzheimer’s disease (AD) is a neurological disorder associated with amyloid $\beta$-protein (A$\beta$) assembly into toxic oligomers. In addition to the two predominant alloforms, A${\beta }_{1-40}$ and A${\beta }_{1-42}$, other C-terminally truncated A$\beta$ peptides, including A${\beta }_{1-38}$ and A${\beta }_{1-43}$, are produced in the brain. Here, we use discrete molecular dynamics (DMD) and a four-bead protein model with amino acid-specific hydropathic interactions, DMD4B-HYDRA, to examine oligomer formation of A${\beta }_{1-38}$, A${\beta }_{1-40}$, A${\beta }_{1-42}$, and A${\beta }_{1-43}$. Self-assembly of 32 unstructured monomer peptides into oligomers is examined using 32 replica DMD trajectories for each of the four peptides. In a quasi-steady state, A${\beta }_{1-38}$ and A${\beta }_{1-40}$ adopt similar unimodal oligomer size distributions with a maximum at trimers, whereas A${\beta }_{1-42}$ and A${\beta }_{1-43}$ oligomer size distributions are multimodal with the dominant maximum at trimers or tetramers, and additional maxima at hexamers and unidecamers (for A${\beta }_{1-42}$) or octamers and pentadecamers (for A${\beta }_{1-43}$). The free energy landscapes reveal isoform- and oligomer-order specific structural and morphological features of oligomer ensembles. Our results show that oligomers of each of the four isoforms have unique features, with A${\beta }_{1-42}$ alone resulting in oligomers with disordered and solvent-exposed N-termini. Our findings help unravel the structure–function paradigm governing oligomers formed by various A$\beta$ isoforms. Full article