Plant virus causes severe yield losses in cash crops such as pepper and tomatoes, and efficient antiviral agents remain an urgent demand in agricultural pest control. Two series of pyrazoline acylhydrazone derivatives (A-1 ~ A-18 and morpholine-containing T-1 ~ T-27) were synthesized and evaluated for their anti-tobacco mosaic virus (TMV) activity. Promisingly, the introduction of a morpholine ring in the T-series increased curative activity by 10-78%, and protective activity by 6-72%. DFT calculations indicated that compound T-8, which contains a morpholine structure, exhibited significant spatial separation between its HOMO and LUMO distributions compared to morpholine-free compound A-13. This spatial separation favors the establishment of an intramolecular charge-transfer channel, thus enhancing electron transfer efficiency during target binding. T-19 demonstrated significantly curative and inactivation activities of 80.9 and 90.5%, respectively, which is superior or similar to that of commercialized Ningnanmycin (67.2 and 89.6%, respectively). The results of molecular docking, dynamic simulation, qRT-PCR, microscale thermophoresis and transmission electron microscope revealed that T-19 showed a strong affinity with TMV coat protein, resulting in a direct disruption of viral particles and inhibiting viral replication and systematic movement in host plant. T-series with morpholine ring led to a substantial enhancement in antiviral potency compared to A-series, and the discovery of T-19 provides an innovative design strategy for antiviral candidate. © 2026 Society of Chemical Industry.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that leads to gradual deterioration of cognitive functions. Cholinesterase enzymes play a critical role in regulating acetylcholine levels in the brain, and their dysfunction leads to impaired cholinergic neurotransmission, which is a primary hallmark of AD and contributes significantly to the cognitive decline and dementia. Here, a series of pyrazine-1,2,3-triazole molecular hybrids incorporating a trifluoromethyl (-CF3) group were synthesized (8a-o). Synthesized compounds were then evaluated in vitro for cytotoxicity and cholinesterase inhibitory activities. All synthesized compounds were found to be nontoxic toward BV-2 cells in the cytotoxicity screening. The in vitro inhibition assays revealed that these derivatives exhibited greater inhibitory potency against acetylcholinesterase (AChE) than butyrylcholinesterase (BuChE). Among them, compound 8h demonstrated the most potent AChE inhibition compared to BuChE (AChE, IC50 = 5.43 µM; BuChE, IC50 = 127.12 µM). The most active compound 8h was further subjected to molecular docking and dynamic simulation (100 ns) to investigate its binding affinity, thermodynamic behavior, and stability within the active site of cholinesterase enzymes. Overall, the findings suggested that the synthesized compounds represent promising drug candidates as selective acetylcholinesterase inhibitors for the treatment of AD.

Introduction Pediatric tumors can relapse despite low mutation burdens, suggesting hybrid evolutionary dynamics shaped by stochastic variability and stabilizing forces. We develop a hybrid Ornstein–Uhlenbeck (OU)–Branching framework that couples mean-reverting stochastic trait dynamics with demographic birth–death processes to model lineage diversification under effective stabilizing constraints. Methods Using Escherichia coli long-term evolution experiment (LTEE) lineages (WT, priA, recG), we parameterized the equilibrium mean (μ), mean-reversion strength (θ), and diffusion scale (σ) on the log10 mutation-frequency axis via replicate-grouped likelihood inference. We performed forward simulations for predictive envelopes, uncertainty quantification, phase-plane dynamics, and OU–Branching lineage networks. We also ran illustrative in silico therapy simulations under fixed OU parameters with exposure-modulated birth/death rates. Results The fitted model recapitulated lineage-specific mutation dynamics and branching architectures. priA exhibited elevated stochastic dispersion and drift-prone behavior consistent with a high-plasticity regime, whereas recG showed constrained diversification and increased lineage turnover consistent with a collapse-prone regime. Illustrative therapy simulations generated oscillatory trait trajectories, suppression–rebound population dynamics, clonal pruning, and extinction-versus-persistence regimes. Discussion Although Y is directly observed as log10 mutation frequency in LTEE, in tumors Y can represent a longitudinally measurable phenotypic state (e.g., drug-tolerance scores from single-cell data, MRD/VAF-derived burden proxies, or pathway activity states). The balance between stabilizing strength (θ) and stochastic variability (σ) provides a quantitative axis governing plasticity and persistence, motivating future calibration to clinical longitudinal data for evolution-aware, patient-specific modeling.

Vegetation, as a key component of land cover, plays a vital role in regulating energy exchange and water balance at different spatial and temporal scales. It is thus important to explore dynamic processes of changes in vegetation cover under changing environmental conditions in the context of global climate change. In this study, the Jialing River Basin (JRB) was selected as a case study, with the leaf area index (LAI) used as the primary indicator to represent JRB vegetation cover and growth status. The Biome-BGC model was employed to simulate the growth of various vegetation types within the basin. We calibrated the optimal range of multiple physiological and ecological parameters of vegetation and analyzed vegetation responses to climate change. The results showed that under four CMIP6 climate scenarios (SSP126, SSP245, SSP370, and SSP585), both temperature and precipitation in the basin are projected to increase. From 1976 to 2016, the vegetation coverage of the basin remained high, and on a monthly timescale, the grasslands are more responsive to climate-induced variability than woodlands. Under the influence of a warmer, more humid climate from 2023 to 2100, the LAI of vegetation in the basin is projected to show an increasing trend, and the vegetation coverage of woodland will still exceed that of grassland. These findings contribute to a more accurate simulation of vegetation dynamics under climate change and can inform the development of effective vegetation conservation and management strategies.

Despite the widespread significance of the Fe(III)-catalyzed oxidation of S(IV) for sulfur chemistry and atmospheric aerosols, its reaction mechanism and accelerated kinetics at the microdroplet surface remain poorly understood. Herein, integrating Born-Oppenheimer molecular dynamic (BOMD) simulations and electron paramagnetic resonance spectrometer (EPR) experiment, the results reveal that the rate-determining SO3·- radical generation exhibits orders of magnitude enhancement at the air-water interface compared to that established in solution-phase kinetics. This interfacial acceleration is progressively amplified under more acidic conditions, as corroborated by both lower calculated free energy changes and enhanced experimentally measured SO3·- signal intensities with decreasing pH. Challenging the traditional Fe(III) solubility-driven paradigm, we demonstrate that the elevated rate mainly stems from highly reactive Fe(III) speciation under low pH conditions, whose reduced molecular orbital energy level improves electron-accepting capacity and thereby accelerates the oxidation reaction as acidity increases. Critically, our simulations establish an unprecedented concerted proton-electron transfer (CPET) mechanism, supported by synchronous proton and electron transfer across all dynamic events. This work elucidates the origin of the high efficiency of Fe(III)-catalyzed S(IV) oxidation in microdroplets and provides fundamental insights into pH-dependent transition-metal ion speciation as a previously under-appreciated factor impacting atmospheric sulfate aerosol formation and sulfur cycling.

Abstract The determination of seismogenic fault geometry of historical earthquakes is hindered by temporal distance, degradation of seismic evidence, human activities, and natural weathering processes, and typically relies on trenching, a costly and time-intensive method. We used the dynamic rupture simulation method to investigate the seismogenic fault of the 1923 M 7.2 Renda earthquake on the northwestern Xianshuihe fault. First, we constructed two fault geometry models (models A and B), which are supposedly the candidates for the seismogenic fault of this event. Then, we constructed the regional medium model and complex stress fields model, and simulated the dynamic rupture process on these two fault models using the curved grid finite-difference method. Our rupture model was constrained by the field-observed fault surface dislocations and inferred intensity. The simulation results suggest that the seismogenic fault of the 1923 Renda earthquake corresponds to model A, in which the southeastern segment of the Daofu fault segment consists of a subsidiary fault located farther from the Qianning fault segment. Our simulation results also suggest that the 1923 Renda earthquake has a surface rupture length of approximately 71 km and a moment magnitude of 7.2, and the earthquake rupture propagates through the bending part at Goupu, where the fault strike changes dramatically. This study provides valuable insights for constraining the seismogenic fault geometry of historical earthquakes in other regions.

Proton-coupled electron transfer (PCET) reactions are core elementary steps in electrochemical energy conversion processes. Accurate quantification of their rate constants is crucial for understanding reaction mechanisms and designing electrocatalysts. However, developing appropriate methods to treat an exact grand canonical (GC) constant potential condition remains challenging and is still under debate. Here we compare two simulation strategies of introducing applied potentials: one incorporates microstates' electrochemical potential fluctuations to rigorously sample the GC ensemble distribution, while another fixes the potential by iteratively adjusting electron numbers for each microstate. Using the Volmer reaction at Pt(111) surface as a model system, and employing the Bennett-Chandler approach to calculate rate constants, we find that these two different approaches yield distinct thermal activations and dynamic recrossing behaviors, leading to non-negligible differences in predicted reaction rate constants. Our study highlights the criticality and necessity of capturing instantaneous potential fluctuations for rigorous and reliable dynamic simulations of electrochemical PCET steps.

Diabetes mellitus is a major global health concern associated with severe metabolic and cardiovascular complications. This study evaluated the antidiabetic and antioxidant activities of Oxalis corniculata L. aerial parts, with a focus on α-glucosidase and α-amylase inhibition, using a combination of in vitro assays and in silico analyses. Among the tested fractions, the ethyl acetate fraction exhibited the strongest inhibitory activity against both enzymes, with IC50 values of 0.097 and 0.015 mg/mL for α-glucosidase and α-amylase, respectively, surpassing those of the reference drug, acarbose. This fraction also demonstrated potent antioxidant activity, with IC50 values of 0.025 and 0.020 mg/mL in DPPH and ABTS assays, respectively. To elucidate the underlying mechanisms beyond digestive enzyme inhibition, bioactive constituents were screened and evaluated using network pharmacology, molecular docking, molecular dynamics simulations, and density functional theory (DFT) calculations. Molecular docking and dynamic simulations confirmed stable and energetically favorable interactions with α-glucosidase and α-amylase. Network pharmacology analysis revealed that the antidiabetic effects of O. corniculata involve modulation of insulin resistance-related pathways, particularly PI3K/Akt signaling, GLUT4 translocation, and inflammation-associated targets, alongside regulation of oxidative stress through redox-related enzymes. Complementary DFT analysis provided molecular-level insights into the antioxidant mechanisms, highlighting favorable electronic properties that support efficient radical scavenging. Overall, this integrated experimental–computational study provided valuable evidence of O. corniculata aerial parts as a promising multi-target phytotherapeutic candidate for diabetes management, extending its therapeutic relevance beyond α-glucosidase and α-amylase inhibition.

High-platform timber structures represent a typical structural form in ancient Chinese architecture, where the platform and the upper timber structure constitute a mechanically coupled system with interacting mechanical properties and response behaviors. However, a systematic understanding of their global coupling mechanism and its impact on structural response remains unclear. This study investigates a representative high-platform timber structure, i.e., Xi’an Bell Tower, to analyze the static and dynamic response characteristics of the platform–superstructure system using in situ dynamic testing and finite element simulation. The results indicate that the simulated first two natural frequencies align well with in situ measurements, validating the model’s rationality. The global coupling effect alters the system’s mass and stiffness distribution, leading to an overall lengthening of the structural natural periods. Structural self-weight is identified as the dominant factor inducing vertical deformation under serviceability conditions, with significant deformation observed at the platform’s edges and corners. Under lateral loads, deformations concentrate in the second story of the timber superstructure, with seismic actions exerting a more pronounced influence than wind loads. Under rare earthquake conditions, the maximum inter-story drift ratio reaches 1/70. Local tensile stresses at the joints, architrave ends, and the Dou-Gong layer exceed the timber’s tensile strength parallel to the grain, identifying these components as the weak links in the structure’s seismic performance.

Abstract. The growing availability of glacier observations poses a challenge for models to integrate this heterogeneous information in a dynamically consistent way. At the same time, estimates of current glacier volume and area remain uncertain, as many global inventories and thickness datasets date back to the early 2000s. We present the Open Global Glacier Data Assimilation Framework, named AGILE, a time-dependent variational method inspired by 4D-Var data assimilation. AGILE is built on a reimplementation of the OGGM flowline glacier evolution model in PyTorch, enabling full differentiability through automatic differentiation (AD). We test AGILE v0.1 in a series of idealized experiments designed to reflect common initialization and calibration scenarios in global glacier modeling. The goal is to recover glacier bed topography and distributed ice volume in 2020 through transient calibration, based on dynamical simulations starting in 1980. In these experiments, we assume a perfectly known mass balance and fixed ice dynamics parameters. While this setup simplifies real-world complexity, it allows us to isolate and evaluate the core functionality of the approach. Our results show that AGILE efficiently optimizes multiple control variables by leveraging AD-derived gradients, requiring only a few iterations to substantially improve upon initial guesses. We also examine the potential to reconstruct earlier glacier states (e.g., in 1980) without direct observations and find that this is fundamentally limited because glacier dynamics are governed by a diffusion equation, which leads to a loss of information about past states over time, even in an idealized setting. Overall, our experiments demonstrate AGILE’s potential as a flexible and efficient data assimilation framework. Its ability to integrate diverse datasets in a dynamically consistent manner makes it a promising tool for future real-world glacier modeling applications.

Ambulance not only plays the role of transporting patients, but also provides a comfortable environment for patients. However, bumpy roads increase human vibration and reduce the comfort of patients. Therefore, it is necessary to analyze the vibration of human body and put forward the measures to reduce the vibration. Firstly, the vibration test of human body is carried out, the acceleration and comfort of human body are analyzed, and the corresponding relationship between subjective data and objective data is established, so as to determine the control target of acceleration of different parts of human body. The test results show that the vibration of different parts of the human body is different, and the back and shoulder are the most sensitive to vibration, and most of the symptoms are dizziness and palpitation. In order to reduce the vibration of the back and shoulder, the saddle-shaped back pillow (SBP) and C-shaped auxiliary head pillow (CSH) with variable stiffness are designed. The ideal damping effect of SBP and CSH is verified by the coupling dynamic simulation model of human-vehicle-road. The comparative test results show that SBP and CSH can reduce human vibration by up to 20%, which can help enhance patients' comfort.

Identification of mitochondrial dysfunction-related biomarkers and immune infiltration in liver ischemia-reperfusion injury via integrated bioinformatics and machine learning.

Mathematical modelling of tumor-immune interactions in breast cancer.

This study develops and evaluates a high-renewable hybrid microgrid for rural Bangladesh. The objective is to design a reliable, affordable, and grid-compliant system that supports residential, institutional, and irrigation loads. The work integrates techno-economic optimization, sensitivity analysis, and voltage-frequency stability assessment within a single framework. HOMER Pro is used to analyze multiple hybrid configurations, while MATLAB evaluates dynamic stability. The proposed contribution lies in modeling realistic field-based load profiles, incorporating converter constraints, and assessing stability across different operating conditions. A PV-wind-biogas-battery microgrid emerges as the optimal option. It achieves 88.2% renewable penetration with a net present cost of USD 206,841 and a levelized cost of energy of USD 0.0207/kWh. Solar PV and wind provide most of the annual energy, while grid support remains limited. Sensitivity analysis shows that solar and converter costs strongly influence project economics. Dynamic simulations confirm secure voltage-frequency performance and compliance with Bangladesh Grid Code limits. The results demonstrate that the proposed system offers a practical pathway for low-cost, reliable, and sustainable electrification in rural communities. The framework can also be adapted to other locations with similar resource and load characteristics.

Abstract Current accident statistics show that the highest rate of fatal traffic accidents in Germany occurs on rural roads, particularly as a result of vehicles leaving the road. Advanced driver assistance systems (ADAS) and highly automated driving functions therefore have high potential to improve safety in this domain. A key challenge is lateral vehicle control, especially the selection of an appropriate trajectory when cornering in automated driving mode (SAE Level 3+). The aim of this work is to derive characteristic driving variants from real-world measurement data, which serve as a basis for the design of automated lateral vehicle control and contribute to achieving high customer acceptance at the same time. For this purpose, extensive data from real world field tests was collected, standardized, and segmented at defined nodes (curve entry, apex, curve exit). A subsequent cluster analysis identified typical driving styles. Based on this, various trajectory variants were systematically generated using graph theory methods. These variants differ in terms of vehicle class, curve radius, and preference for corner-cutting. In addition, environmental influences such as the presence of oncoming traffic were considered. The outcome is a catalog of reality-based trajectories that serves as the basis for future driving functions. This enables further investigations in which the influence of the variants on driving comfort and safety will be evaluated, both in the Dynamic Vehicle Road Simulator (DVRS) and in real-world driving tests with test vehicles.

Abstract Climate change has become a critical driver of energy policy and building performance assessment worldwide. In response to rising greenhouse gas emissions and increasing energy demand, the European Union introduced the Energy Performance Certificate (EPC) system in 2002 to standardize and promote energy efficiency in buildings. However, conventional EPC assessments are still based on static weather inputs such as Typical Meteorological Year (TMY) data, which overlook the growing influence of climate variability and long-term warming trends. This study proposes a dynamic simulation framework that incorporates both global warming and interannual climate fluctuations into building energy evaluations. Using 45 years of ERA5 reanalysis data (1979–2023) and EnergyPlus simulations of a standardized residential building in Korea, we quantify how external climate dynamics affect heating and cooling demand. Results reveal that short-term variability often exceeds the energy impacts of four decades of warming, with spatial differences influenced by topography and ENSO phase. These findings highlight the limitations of current EPC methodologies and underscore the need to integrate both gradual and dynamic climate influences into future EPC frameworks to ensure more resilient energy planning.

Premature ovarian insufficiency (POI) is characterized by gonadotropin elevation, estrogen deficiency, and follicular loss. Resveratrol (RSV), a natural polyphenol with antioxidant and anti-aging properties, shows therapeutic promise for POI, but its molecular targets and mechanisms remain unclear. Network pharmacology analysis was used to identify overlapping targets of RSV and POI, followed by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, protein-protein interaction (PPI) network construction, and hub gene screening. Molecular docking and dynamics simulations were performed to characterize the affinity and binding stability. In vivo, a cyclophosphamide-induced POI rat model was established to evaluate the protective effects of RSV on ovarian morphology and hormone levels. In vitro, a 4-hydroperoxycyclophosphamide-induced granulosa cell model was used to assess DNA damage and homologous recombination (HR) activity through TUNEL staining, Western blotting, and nuclear foci analysis, with RAD51 inhibition applied to verify pathway dependence. About 609 overlapping genes between RSV- and POI-related targets were identified. GO and KEGG enrichment analyses revealed significant involvement in reproductive system development, DNA repair complex, and cellular senescence. PPI and topological analysis identified three core genes - ATM, BRCA1, and RAD51 - significantly enriched in the HR pathway. Molecular docking and dynamic simulations indicate that RSV has a strong affinity and stable binding mode with these three targets. In vivo, RSV ameliorated cyclophosphamide-induced ovarian injury, increasing serum anti-Müllerian hormone levels and secondary follicle counts. Mechanistically, in the POI cell model, RSV upregulated RAD51 and downregulated γH2AX expression, thereby promoting HR pathway activation and DNA double-strand break repair. The protective effect of RSV was abolished by the RAD51 inhibitor RI-1. Immunofluorescence foci analysis further verified that RSV enhanced the recruitment of RAD51 to DNA damage sites and reduced nuclear γH2AX accumulation. This study provides structural and experimental evidence for the target selection, structural optimization, and molecular mechanism of RSV in the treatment of POI.

Abstract By using the 1 m telescope of Yunnan Observatories and the 0.5 m telescope of Ho Koon Nature Education cum Astronomical Centre, China, we had obtained eight transit light curves for the exoplanetary system WASP-36 and three for the exoplanetary system XO-3 between 2010 and 2021. By means of the Markov Chain Monte Carlo technique, we have jointly analyzed these light curves and the relative Transiting Exoplanet Survey Satellite light curves to refine the physical parameters of both systems. Through combining the new mid-transit times with the published ones and the ones from the Exoplanet Transit Database website, we have derived transit timing variation (TTV) patterns of the two systems. By analyzing the TTV signals, we find that WASP-36’s TTV favors the apsidal precession model while XO-3’s TTV agrees to the orbital decay model. However, detailed physical analyses demonstrate that the two mechanisms are not the origin of the observed TTVs. Considering that the observed TTVs are induced by perturbers in the systems, based on dynamic simulations, we have constrained the mass of hypothetical perturbers by combining the rms values of both TTVs and radial velocity curve residuals. When the hypothetical perturbing planets are near mean-motion resonance with the transiting planets, the systems could potentially harbor Earth-mass perturbing planets capable of reproducing the observed TTV signals.

Long-term protection of an inactivated enterovirus type 71 vaccine against hand, foot, and mouth diseases in children: a modelling study.

Terahertz resonances embedded in crystalline heterostructures could close a spectral gap between conventional electronics and photonics while opening new windows on phenomena in non-equilibrium lattice dynamics. We show that femtosecond optical screening of the depolarization field in epitaxial PbTiO3/SrTiO3 superlattices launches a collective polar mode that oscillates near 1 THz and coherently spans the entire mini-Brillouin zone. Wave-vector-resolved pump-probe X-ray diffraction resolves a nearly dispersion-less oscillation at 0.87 and 0.94 THz at the zone boundary and zone center, respectively, persisting for ∼2.5ps, corresponding to a weakly damped resonance. Dynamical phase-field simulations reveal the origin of the mode to mesoscopic rotation of closure-domain textures during the photoexcited transition from an unscreened to a screened electrostatic state. Varying the PbTiO3 and SrTiO3 ratio tunes the mode frequency continuously from 0.9 to 1.4 THz, providing a quantitative design rule for frequency-selectable THz oscillators in ferroelectric heterostructures. By coupling nanoscale polarization reconfiguration to long-wavelength coherent dynamics, this work establishes depolarization-field engineering to topology-driven THz functionality and expanding the landscape of collective lattice dynamics.