Search Results (160)

Type 1 diabetes (T1D) is driven by autoreactive CD4⁺ T-cell responses to pancreatic beta cell antigens presented by disease-associated human leucocyte antigen (HLA) class II molecules. However, the molecular mechanisms by which subtle antigenic modifications promote pathogenic immunity remain incompletely defined. Recent immunopeptidomic studies have identified a cysteine-to-serine substitution at position 19 of the insulin B chain, referred to as InsC19S, as a microenvironment-driven neoepitope that can be presented by HLA class II molecules, including HLA-DQ8, and is recognized by diabetogenic CD4⁺ T cells. In this study we explore potential structural and thermodynamic mechanisms that may contribute to the enhanced immunogenicity associated with this single-amino-acid modification. Using molecular dynamics simulations combined with coarse-grained free-energy-perturbation analyses, we compared HLA DQ8 complexes bound to wild-type (WT) insulin and InsC19S peptides. The InsC19S variant is predicted in simulations to exhibit enhanced binding stability, characterized by increased hydrogen bond occupancy, reduced peptide conformational mobility, and a more favorable binding free energy. In addition, the modified peptide is predicted to induce peptide-dependent conformational adjustments within the HLA-DQ8 peptide-binding groove, resulting in expansion of the conformational landscape and stabilization of distinct low-energy states that are not accessed by the WT complex. Principal component analysis and free-energy landscape mapping suggest that this mutation may promote altered collective motions within HLA DQ8 that are consistent with enhanced peptide major histocompatibility complex (MHC) persistence and optimized antigen presentation geometry. Together, these computational observations suggest a structural framework that may help explain the preferential presentation and pathogenic recognition of InsC19S reported in experimental studies. These findings provide a molecular-level framework that may help link microenvironment-driven insulin neoepitope formation to altered peptide–MHC stability and conformational dynamics in HLA-DQ8. Full article

Traditional sliding mode control (SMC) lacks an active mechanism for redistributing energy among state channels during transient convergence, resulting in a rigid trade-off between response speed, overshoot suppression, and energy efficiency. This paper proposes a virtual state coupled SMC method that introduces a dynamic virtual state with bilinear product coupling $x_1{x}_2$ into the sliding surface. Unlike conventional virtual states that serve as static linear combinations or observer-based estimates, the proposed virtual state evolves dynamically and establishes an active energy exchange channel between the real and virtual state dynamics. Linearization and Lyapunov-based analyses prove local asymptotic stability of the closed-loop system. The coupling strength $\gamma$ is shown to be decoupled from the linearized local eigenvalues and thus governs the energy–performance trade-off independently, while the condition $c>\gamma /4$ guarantees a non-vanishing domain of attraction. Simulations demonstrate that the proposed method achieves up to 53.2% control energy reduction under disturbance-free conditions compared with conventional SMC. Under persistent high-frequency disturbances, increasing $\gamma$ reduces oscillations by 54.2% at a controllable energy cost of 45.7%. Systematic parameter selection guidelines are provided, and Monte Carlo simulations (500 trials, $\pm 30\%$ parameter perturbations) confirm 100% convergence. The proposed method offers an independently adjustable energy–performance trade-off mechanism suitable for sensor-based motion systems with stringent transient and energy requirements. Full article

Coronavirus disease 2019 continues to pose global health challenges, with the pandemic significantly burdening several economies, healthcare systems, and the social lives of individuals. Furthermore, new cases continue to be reported, underscoring the need for therapeutic strategies targeting conserved regions and host–virus interactions. Building on earlier virtual screening for small molecules, all-atom molecular dynamics simulations and binding-free-energy calculations were performed to elucidate how the two previously identified small molecules (NSC36398 and NSC281245) may affect the dynamic behaviour of the interaction between heat shock 70 kDa protein 8 (HSPA8) and the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein. Post-MD analyses refined prior docking predictions, where NSC281245 was found to bind tightly to the complex with limited perturbations at the HSPA8-spike protein interaction surface, whereas NSC36398 appeared to induce allosteric-like domain-level destabilisation effects while maintaining stable polar contacts with the protein. Our findings demonstrate the potential of NSC36398 as a promising modulator for disrupting the HSPA8-spike protein complex, which may serve as a structural lead for designing next-generation inhibitors of host–virus interactions. Full article

This study focused on elucidating the effects of chitosan (Ch), hyaluronic acid (HA), and titanium dioxide nanoparticles (nano-TiO₂) on the physicochemical characteristics of a model bacterial membrane (layer) composed of the phospholipid DPPG (1,2-dipalmitoyl-sn-glycero-3-phospho-rac-(1-glycerol) sodium salt). The membrane was prepared on mica using the Langmuir–Blodgett (LB) technique from an aqueous subphase containing Ch, HA and/or TiO₂. Its surface properties were subsequently characterized by optical profilometry and surface free energy estimation. The nanoscale topography of the DPPG layer provided a biomimetic platform that reflects the organization of bacterial membranes, enabling a precise evaluation of how external agents, such as Ch, HA, and nano-TiO₂, modify the surface’s structural and energetic properties. The results showed that the LB films exhibit mildly heterogeneous topography, which can be attributed to lipid domains with distinct molecular packing densities. Depending on the type of biopolymer employed with TiO₂, distinct topographic architectures of the DPPG monolayers were obtained. Furthermore, the presence of nano-TiO₂ was clearly manifested as a topographic irregularity, while the analysis of hydrophilic–hydrophobic properties revealed a structurally perturbed lipid film. The results provide detailed insight into how these specific molecules (Ch, HA, nano-TiO₂) interact at the molecular level with model bacterial membranes, offering a comprehensive picture of cell–microenvironment interactions. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells when the spike receptor-binding domain (RBD) engages angiotensin-converting enzyme 2 (ACE2). Cannabinoid scaffolds have recently been reported to bind S1/RBD, block spike-mediated membrane fusion, and modulate host inflammatory pathways, making them attractive candidates for entry inhibition. Here, we applied an integrated computational pipeline to prioritize cannabis-derived compounds as interfacial blockers of the RBD–ACE2 complex across variants. Eleven phytocannabinoids were docked into the wild-type (WT) RBD–ACE2 interface, identifying three cavities, with ligands preferentially occupying pocket 1. Complexes were subjected to triplicate 200 ns all-atom molecular dynamics (MD) simulations for WT, Delta, and Omicron BA.1 RBD–ACE2. Binding energetics were quantified using molecular mechanics/generalized Born surface area (MM/GBSA) and solvated interaction energy (SIE), and per-residue contributions were analyzed together with solvent-accessible surface area (SASA) and residue interaction networks. Among all compounds, cannabidiol (CBD) and cannabinol (CBN) were the only ligands that remained stably bound in pocket 1 for all variants. CBN showed the most favorable ligand–complex binding in WT, whereas CBD preserved favorable binding in Omicron BA.1 despite reduced interface burial, indicating that van der Waals/electrostatic complementarity and solvation, rather than surface coverage alone, govern affinity. Both ligands weakened modeled RBD–ACE2 binding by perturbing hot-spot residues centered on Y505 or N501Y in RBD and E37, A387, and R393 in ACE2. Overall, our results highlight CBD and CBN as tractable, variant-spanning interface disruptors and illustrate how MD-based free-energy calculations can support computational drug discovery against evolving viral protein–protein interfaces. Full article

Differential operators often admit multiple algebraically equivalent symbolic formulations, yet those formulations can differ in the organization of their internal structure prior to solution analysis. A reproducible symbolic framework is introduced to compare such formulations at the level of operator expressions. Within a declared symbolic specification consisting of a fixed grammar, an admissible weight class, canonical compression rules, and an admissible family of reformulations, we define four encoding-relative structural descriptors: structural strain $\tau$, structural curvature $\kappa$, compressibility $\sigma$, and the balance ratio $\Gamma =\kappa /\tau$. Structural strain compares an encoding to a designated reference representation, while compressibility measures reduction under canonical symbolic compression. These quantities are deterministic descriptors within the declared encoding class rather than coordinate-free invariants of the underlying operator. The structural length functional underlying these descriptors is developed, canonical compression is formalized, and finite symbolic comparison is distinguished from pathwise symbolic deformation. A robustness theorem shows that, away from the threshold surface $\Gamma =\sigma$, sufficiently small admissible perturbations preserve the induced diagnostic label. A supporting weight-robustness result further shows that qualitative labels persist across a local admissible family of weight choices under corresponding nondegeneracy conditions. The framework serves as a reproducible diagnostic for operator representations alongside Lyapunov, spectral, pseudospectral, and energy-based stability theories. Examples of representative ordinary and partial differential operators illustrate how the descriptors are computed and how they behave under admissible re-expression, while the appendices provide the technical backbone of the paper: formal definitions, reproducibility protocol, extended perturbation arguments, and explicit failure-mode analysis. Additional sensitivity checks regarding encoding, weights, and threshold variation clarify the method’s scope, and explicit failure modes delineate the boundary cases in which the descriptors cease to apply. The main contribution of this study is a formally delimited and reproducible symbolic framework for comparing differential operators under a fixed, declared specification, together with robustness results and worked examples that clarify the method’s scope. Full article

As AI-driven educational systems increasingly rely on deep neural networks, their vulnerability to adversarial perturbations raises concerns about assessment integrity, fairness, and reliability. Adversarial example purification is attractive for such deployments because it removes input perturbations without modifying the already deployed models. However, most existing purification methods are inherently goal-free: denoising-based approaches apply blind heuristic operators, while reconstruction-based methods rely on stochastic sampling guided by natural image priors. These methods typically suppress perturbations at the cost of weakening semantic details or inducing structural distortions. To address this limitation, we propose a novel goal-directed purification framework, termed adversarial energy field optimization for adversarial example purification (AEFOP). AEFOP formulates purification as a constrained optimization problem by defining a learnable adversarial energy which quantifies how far an input deviates from the benign region. This allows adversarial examples to be explicitly pushed from high-energy regions toward low-energy benign regions along an interpretable descent trajectory. Specifically, we build an adversarial energy network and optimize the energy field via a two-stage strategy: adversarial energy field shaping, which enforces distance-like energy behavior and correct gradient directions, and task-driven energy field calibration, which unrolls the descent process to calibrate the field with classification-consistency and semantic-preservation objectives. Extensive experiments across multiple attack scenarios demonstrate that AEFOP achieves superior purification accuracy and high visual quality while requiring only a few gradient steps during inference, offering a practical and efficient robustness layer for vision-based AI services in education. Full article

Dragonflies exhibit remarkable flight stability in unsteady environments, largely due to aerodynamic interaction between their forewings and hindwings. This study investigates gust response in dragonfly-inspired micro-aerial vehicles (MAVs) from a system dynamics perspective, with emphasis on the aerodynamic role of tandem-wing interaction rather than control compensation. A six-degree-of-freedom (6DOF) rigid-body framework is developed and coupled with a quasi-steady aerodynamic model that includes explicit phase-dependent interaction between forewing and hindwing forces. Gusts are introduced as time-varying inflow perturbations, allowing physically consistent analysis of how disturbances propagate through aerodynamic loading into vehicle motion. Simulations are performed for representative flight conditions, including gliding, hovering, and gust-perturbed ascent. The results show bounded trajectory, velocity, and attitude responses under sustained gust excitation, even with conservative baseline control. Force and energy analyses indicate that wing–wake interaction redistributes aerodynamic loads in time and reduces peak force and moment fluctuations before they reach the rigid-body dynamics. This behavior is interpreted as passive aerodynamic filtering of gust disturbances inherent to the tandem-wing configuration. Comparative simulations using backstepping control and Active Disturbance Rejection Control (ADRC) further show that the dominant gust attenuation arises from aerodynamic configuration rather than from control action. Although the aerodynamic model is quasi-steady, the framework reproduces key trends reported in biological and CFD-based studies and provides a numerical foundation for future wind-tunnel and free-flight experiments on configuration-level gust attenuation. Full article

Global Positioning System (GPS)-derived ionospheric electron concentration measurements provide a powerful observational framework for seismo-electromagnetic studies, enabling quantitative investigation of lithosphere–atmosphere–ionosphere coupling processes through statistically detectable perturbations in ionospheric electron concentration. We analyze GPS-derived Vertical Total Electron Content (VTEC) variations associated with the 14 August 2021 Haiti earthquake ($M_w$ 7.2) and the 11 January 2022 Cyprus earthquake ($M_w$ 6.6) using data from nearby International GNSS (Global Navigation Satellite System) Service (IGS) stations located within their respective earthquake preparation zones. VTEC time series spanning 45 days before and 7 days after each event are processed to remove the diurnal component, yielding residuals that isolate short-term ionospheric variability. Anomaly detection is performed using three statistical frameworks: a Gaussian mean, standard deviation model, a robust median/median absolute deviation (MAD) model, and a distribution-free quantile-based model. Daily “occurrence” and “energy” indices are constructed to quantify the frequency and cumulative strength of detected anomalies, respectively. While the indices exhibit similar temporal patterns across all methods, they indicate frequent anomaly detection, limiting statistical selectivity. To address this, both indices are normalized by their median values and filtered using a 95% quantile threshold, retaining only extreme deviations. This procedure substantially reduces background fluctuations and isolates a small number of statistically significant anomaly peaks. For both earthquakes, enhanced anomaly activity is identified in the weeks preceding the events, whereas post-event peaks coincide with periods of elevated meteorological and geomagnetic activity. The results demonstrate that normalization combined with robust statistical methods is essential for discriminating significant ionospheric TEC anomalies from background variability. Full article

The two most severe cosmological tensions in the Hubble constant $H_0$ and the matter clustering amplitude $S_8$ have the same relative discrepancy of 8.3%, which suggests that they may have a common origin. Modifications of gravity and exotic dark fields with numerous free parameters introduced in the Einstein field equations often struggle to simultaneously alleviate both tensions; thus, we need to look for a common cause within the standard $\Lambda$CDM framework. At the same time, linear perturbation analyses of matter in the expanding $\Lambda$CDM universe have always neglected the impact of comoving peculiar velocities $\mathbf{v}$ (generally thought to be a second-order effect), the same velocities that, in physical space, cannot be fully accounted for in the observed late-time universe when the cosmic distance ladder is used to determine the local value of $H_0$. We have reworked the linear density perturbation equations in the conformal Newtonian gauge (sub-horizon limit) by introducing an additional drag force per unit mass $-\Gamma \left(t\right)\mathbf{v}$ in the Euler equation with $\Gamma \equiv \gamma \left(2H\right)$, where $\gamma \ll 1$ is a positive dimensionless constant and $2H\left(t\right)$ is the time-dependent Hubble friction. We find that a damping parameter of $\gamma =0.083$ is sufficient to resolve the $S_8$ tension by suppressing the growth of structure at low redshifts, starting at $z_{★}\simeq 3.5–6.5$ to achieve $S_8\simeq 0.78–0.76$, respectively. Furthermore, we argue that the physical source causing this additional friction (a tidal field generated by nonlinear structures in the late-time universe) is also responsible for a systematic error in the local determinations of $H_0$—the inability to subtract peculiar tidal velocities along the lines of sight when determining the Hubble flow via the cosmic distance ladder. Finally, the dual action of the tidal field on the expanding background—reducing both the matter and the dark energy sources of the squared Hubble rate $H^2$, thereby holding back the cosmic acceleration $\ddot{a}$—is of fundamental importance in resolving cosmological tensions and can also substantially alleviate the density coincidence problem. Full article

Background: The extracellular-signal-regulated kinase (ERK) cascade regulates cell proliferation, differentiation, and survival, and ERK2 mediates substrate phosphorylation, influencing gene expression and cellular functions. Methods: In the current study, a pool of new molecules was generated using the DeLA-Drug, a machine learning (ML)-assisted de novo design tool. The chemical space was reduced through a similarity search against active ERK2 inhibitors and molecular docking with AutoDock vina, followed by pharmacokinetic assessment in DeepPK. Poses of the final selected molecules were refined in DiffDock, and dynamicity was assessed through molecular dynamics (MD) simulation. Finally, the free-energy perturbation (FEP)-based binding affinity was explored in Gromacs2023.4. Results: From the above approaches, four molecules (Ek1, Ek2, Ek3, and Ek4) were identified as promising candidates with favorable binding interactions. Molecular docking revealed that the selected molecules exhibited higher binding affinity for ERK2, ranging from −9.50 to −10.50 kcal/mol. The dynamics assessment via MD simulation clearly revealed their strong association with ERK2, corroborated by the lower deviation of the ERK2 backbone in dynamic states. All four screened molecules have satisfactory pharmacokinetic properties, medicinal chemistry properties, and good synthetic accessibility scores, indicating their potential as drug-like compounds under Lipinski’s rule of five to inhibit or modulate ERK2 activity. The FEP energy of Ek1 was found to be −26.85 kJ/mol, which is higher than the standard molecule (−22.77 kJ/mol) and indicates its strong affinity toward ERK2. Conclusions: These results suggest that all proposed ERK2 modulators are potential avenues for future drug discovery targeting ERK2, subject to experimental validation. Full article

Metaheuristic algorithms have become essential tools for solving complex, high-dimensional, and constrained optimization problems. This paper introduces an adaptive R implementation of the parameter-free Jaya algorithm, enhanced with methodological innovations for both single-objective and multi-objective settings. The proposed framework integrates adaptive population management, dynamic constraint-handling, diversity-preserving perturbations, and Pareto-based archiving, while retaining Jaya’s parameter-free simplicity. These extensions are further supported by parallel computation and visualization tools, enabling scalable and reproducible applications. Benchmark evaluations on standard test functions demonstrate improved convergence accuracy, solution diversity, and robustness compared to the classical Jaya and other baseline algorithms. To highlight real-world applicability, the method is applied to a renewable energy planning problem, where trade-offs among cost, emissions, and reliability are explored. The results confirm that the adaptive Jaya approach can generate well-distributed Pareto fronts and provide practical decision support for energy system design. The main contributions of this work are threefold: (i) the development of an adaptive multi-objective extension of the Jaya algorithm that preserves its parameter-free philosophy while incorporating diversity preservation, dynamic constraint handling, and Pareto-based selection; (ii) a unified and openly available R implementation that integrates methodological advances with parallel computation and visualization, addressing the lack of transparent and reusable MO-Jaya tools in the existing literature; and (iii) a systematic evaluation on benchmark test functions and a renewable energy planning case study, demonstrating competitive convergence, robust Pareto diversity, and practical decision-making insights compared to established methods. By openly releasing the software in R (≥3.5.0), this work contributes both a methodological advance in multi-objective metaheuristics and a transparent tool for applied optimization in engineering and environmental domains. Full article

This paper investigates the different relaxation channels of a single symmetric top NH₃ and a spherical top CH₄ molecule trapped at low temperature in a clathrate hydrate nano-cage in the infrared absorption domain of their vibrational degrees of freedom. The approach utilizes the Born–Oppenheimer approximation and the extended site inclusion model applied to CO₂ in a previous work, which was based on pairwise atom–atom effective interaction potentials. The calculations show that trapping the methane or ammonia molecule is energetically more favorable in a type sI clathrate structure than in an sII one, and entropic considerations show that methane can be released much more easily than ammonia from clathrate hydrate nano-cages. In the small (s) and large (l) nano-cages with the sI structure, the CH₄ molecule exhibits a more or less perturbed rotational motion, while the NH₃ molecule shows a strongly hindered orientational motion that tends to a three-dimension librational motion (oscillation motion) around its orientational equilibrium configuration. The calculated orientational energy level schemes are quite different from those of the molecular free rotation. In the static field inside the cage, degenerate ${\nu }_3$ and ${\nu }_4$ vibrational modes of methane and ammonia molecules are shifted and split. Moreover, for ammonia molecules, the ${\nu }_1$ and ${\nu }_2$ modes are shifted, and the inversion motion is no longer allowed. The non-radiative and radiative relaxation channels of CH₄, NH₃ and CO₂ in clathrate nano-cages are discussed with reference to the matrix isolation spectroscopic results. Upon laser excitation, then, from the energy levels calculated for the different degrees of freedom, NH₃ and CO₂ are expected to fluoresce, while for CH₄, non-radiative relaxation should lead to evaporation at the surface of clathrates. Experimental setups are suggested to localize and study these species underneath ice surfaces on distant planets or planetesimals from mobile detectors such as drones or CubeSats equipped with appropriate laser sources and telescopes with 2D imaging detectors. Full article

In this contribution, we propose and study long-time behaviors of a new class of N-dimensional delayed Kirchhoff–Carrier-type problems with variable transfer coefficients involving a logarithmic nonlinearity. We take into account the dependence of diffusion and damping coefficients on the position and direction, as well as the presence of different types of delays. This class of nonlocal anisotropic and nonlinear wave-type equations with multiple time-varying mixed delays and dampings, of a fairly general form, containing several arbitrary functions and free parameters, is of the following form: ${\displaystyle \frac{{\partial }^{2}u}{\partial t^2}-{div(\mathcal{K}(\Vert \sigma \nabla u\Vert }_{L^2(\Omega )}^2)A_{\sigma }{(\mathbf{x})\nabla u)+\mathcal{M}(\Vert u\Vert }_{L^2(\Omega )}^2)u-div(\zeta (t)A_{\sigma }(\mathbf{x})\nabla \frac{\partial u}{\partial t})+d_0(t)\frac{\partial u}{\partial t}+{\mathbb{D}}_r(\mathbf{x},t;\frac{\partial u}{\partial t})=\mathbb{G}(u),}$ where $u(\mathbf{x},t)$ is the state function, $\mathcal{M}$ and $\mathcal{K}$ are the nonlocal Kirchhoff operators and the nonlinear operator $\mathbb{G}(u)$ corresponds to a logarithmic source term. The symmetric tensor $A_{\sigma }$ describes the anisotropic behavior and processes of the system, and the operator ${\mathbb{D}}_r$ represents the multiple time-varying mixed delays related to velocity ${\displaystyle \frac{\partial u}{\partial t}}$. Our problem, which encompasses numerous equations already studied in the literature, is relevant to a wide range of practical and concrete applications. It not only considers anisotropy in diffusion, but it also assumes that the strong damping can be totally anisotropic (a phenomenon that has received very little mathematical attention in the literature). We begin with the reformulation of the problem into a nonlinear system coupling a nonlocal wave-type equation with ordinary differential equations, with the help of auxiliary functions. Afterward, we study the local existence and some necessary regularity results of the solutions by using the Faedo–Galerkin approximation, combining some energy estimates and the logarithmic Sobolev inequality. Next, by virtue of the potential well method combined with the Nehari manifold, conditions for global in-time existence are given. Finally, subject to certain conditions, the exponential decay of global solutions is established by applying a perturbed energy method. Many of the obtained results can be extended to the case of other nonlinear source terms. Full article

Plasma membrane Ca²⁺-ATPases (PMCA) are activated by calmodulin (CaM) via a C-terminal calmodulin-binding domain, CaMBD. Although specific mutations in this domain have been linked to disease, the broader impact of alternative substitutions across the interface remains unexplored. We applied an integrative in silico workflow to test six substitutions within CaMBD positions 1–18, L5R, N6I, I8T, V14E/D, and F18S, across PMCA isoforms 1–4. CaMBD sequences were aligned across isoforms, and candidates for substitutions were selected by conservation and nucleotide feasibility, prioritizing conserved or co-evolutionarily relevant sites, with substitutions possible by single-nucleotide change. PolyPhen-2 screened the impact of the substitutions on the protein functionality, the DisGeNET database was used to contextualize ATP2B genes with clinical phenotypes, and structural models plus binding free energy changes were estimated with AlphaFold3, FoldX, and MutaBind2. Effects were isoform and subregion dependent, with the strongest weakening toward the CaMBD C-terminus. V14E/D and F18S showed the largest and consistent predicted destabilization, consistent with disruption of conserved hydrophobic anchors. I8T and L5R had mixed outcomes depending on isoform, while N6I presented various scenarios with no clear effect. PolyPhen-2 classified most tested substitutions as damaging. Gene-disease evidence linked ATP2B to neurological, endocrine, and oncologic phenotypes, consistent with roles in Ca²⁺ homeostasis. Overall, CaMBD appears highly sensitive to perturbation, with distal positions 14–18 particularly vulnerable to substitutions that can destabilize CaM binding and potentially impair PMCA-mediated Ca²⁺ clearance in susceptible tissues. Full article