Search Results (30,083)

Cancer remains a major global health challenge, emphasizing the need for new and effective therapies. This study investigates the anticancer potential of bioactive compounds from rosemary (Rosmarinus officinalis) using an integrative network pharmacology and computational approach. Twelve phytochemicals with favorable pharmacological profiles, optimal pharmacokinetics, and acceptable toxicological properties were evaluated, revealing 178 putative cancer-related targets. Protein–protein interaction (PPI) analysis highlighted ten key genes—EGFR, ESR1, HIF1A, HSP90AA1, MAPK1, BCL2, STAT3, TP53, CASP3, and SRC—implicated in the progression of various cancers, including breast, colorectal, liver, and lung tumors. Functional enrichment analysis demonstrated their involvement in multiple cancer-associated pathways. Among these, HSP90AA1 emerged as a critical target. Molecular docking revealed Rosmanol, Chlorogenic acid, and Carnosol as the most promising HSP90AA1 binders with strong predicted affinities. ADMET profiling confirmed their excellent drug-likeness and safety profiles, while molecular dynamics simulations validated the stability of the compound–protein complexes, further supporting their potential as HSP90 inhibitors. These findings suggest that rosemary-derived compounds may represent valuable candidates for anticancer drug development, though experimental validation is required to confirm their therapeutic efficacy. Full article

Background: Angiogenesis, the physiological process by which new blood vessels originate from pre-existing ones, can be triggered by tumor cells to promote the growth, survival, and progression of cancer. Malignant tumors require a constant blood supply to meet their needs for oxygen and nutrients, making angiogenesis a key process in tumor development. Its pathologic role is caused by the dysregulation of signaling pathways, particularly those involving VEGFR-2, a key mediator of angiogenesis, and the K-RAS G12C mutant, a promoter of VEGF expression. Given their critical involvement in tumor progression, these targets represent promising candidates for new cancer therapies. Methods and Results: In this study, we applied an in silico hybrid and hierarchical virtual screening approach to identify potential dual VEGFR-2/K-RAS G12C inhibitors with anticancer and antiangiogenic properties. To this end, we screened the National Cancer Institute (NCI) database through ADME filtering tools. The refined dataset was then submitted to the ligand-based Biotarget Predictor Tool (BPT) in a multitarget mode. Subsequently, structure-based analysis, including molecular docking studies on VEGFR and K-RAS G12C, was performed to investigate the interactions of the most promising small molecules with both targets. Conclusions: Finally, the molecular dynamics simulations suggested compound 737734 as a promising small molecule with high stability in complex with both VEGFR-2 and K-RAS G12C, highlighting its potential as a dual-target inhibitor for cancer therapy. Full article

The availability of phosphorus in the soil has a key role in plant physiological processes, particularly in the adaptive responses of invasive species. This study examined how contrasting soil phosphorus concentrations (low: 9 mg/kg and adequate: 27 mg/kg) influence biomass production, lignin and extractive content, P concentration in leaves, and root exudate composition in two invasive species, Ailanthus altissima and Fraxinus americana. Seedlings were grown in rhizoboxes filled with alkaline soils of two types. Adequate phosphorus concentration increased both aboveground and root biomass in the examined species, while low phosphorus significantly reduced biomass, especially in the aboveground parts, which were 3 to 4 times smaller compared to plants grown under adequate conditions. Low phosphorus concentration increased lignin and extractive content in the stem. Root exudate analysis revealed that low phosphorus availability enhanced the secretion of malate in both species. Ailanthus altissima exhibited higher malate concentrations in root exudates compared to Fraxinus americana under both phosphorus conditions. Ailanthus altissima is more competitive than Fraxinus americana on low-phosphorus alkaline soils. The results reveal how Ailanthus altissima and Fraxinus americana adapt to varying soil phosphorus levels, aiding the development of strategies to manage these invasive species and preserve ecosystem stability. Full article

Motivation. Analytic function theory on commutative complex extensions calls for an operator–theoretic calculus that simultaneously sees the algebra-induced coupling among components and supports boundary-to-interior mechanisms. Gap. While Dirac-type frameworks are classical in several complex variables and Clifford analysis, a coherent calculus aligning structural CR systems, a canonical first derivative, and a Cauchy-type boundary identity on the commutative model $\mathbb{C}\left(\mathbb{C}\right)\cong {\mathbb{C}}^4$ has not been systematically developed. Purpose and Aims. This paper develops such a calculus for $\mathcal{O}$-regular mappings on $\mathbb{C}\left(\mathbb{C}\right)$ and establishes three pillars of the theory. Main Results. (i) A fully coupled Cauchy–Riemann system characterizing $\mathcal{O}$-regularity; (ii) identification of a canonical first derivative $g^{\prime }\left(z\right)={\partial }_{x_0}g\left(z\right)$; and (iii) a Stokes-driven boundary annihilation law ${\int }_{\partial \mathrm{\Omega }}\tau g=0$ for a canonical 7-form $\tau$. On (pseudo)convex domains, $\overline{\partial }$-methods yield solvability under natural compatibility and regularity assumptions. Stability (under algebra-preserving maps), Liouville-type, and removability results are also obtained, and function spaces suited to this algebra are outlined. Significance. The results show that a large portion of the classical holomorphic toolkit survives, in algebra-aware form, on $\mathbb{C}\left(\mathbb{C}\right)$. Full article

Zinc oxide (ZnO) thin films have attracted increasing attention as promising materials for sensing applications due to their wide band gap, high exciton binding energy, and remarkable chemical stability. However, the inherent limitations of pure ZnO, such as moderate sensitivity, selectivity, and relatively high operating temperatures, limit its widespread use in advanced sensing technologies. Co-doping, or dual doping with two distinct elements, has emerged as an effective strategy to overcome these challenges by synergistically tailoring the structural, electronic, and surface properties of ZnO thin films. This review provides a comprehensive overview of recent advances in the development of co-doped ZnO thin films for sensing applications. The focus is on the role of different combinations of dopants, including transition metals, rare earth elements, and non-metals, in modulating the charge carrier concentration, oxygen vacancy density, and adsorption dynamics. These effects collectively enhance the sensing properties and long-term stability and reduce detection limits. The analysis highlights the correlations between synthesis methods, dopant incorporation mechanisms, and resulting sensor performance. Key challenges such as dopant clustering, reproducibility, and scalability are discussed, along with emerging opportunities in flexible room-temperature sensor platforms. Overall, it has been demonstrated that co-doped ZnO thin films represent a versatile and tunable class of sensing materials with strong potential for next-generation environmental and biomedical monitoring. Full article

This manuscript presents a robust formation and collision-free containment control system designed for a quadrotor fleet operating under turbulent wind conditions. Emphasizing collision avoidance, we introduce a two-layer strategy in which a virtual leader defines a trajectory, and leaders and followers maintain their positions while avoiding collisions among them. A graph convention is used to illustrate the roles of leaders and followers, as well as their interactions. Inter-agent collision avoidance is proposed by expanding the desired distance relative to all neighboring agents, thereby guaranteeing the convergence stage. Moreover, the approach employs a class of adaptive sliding mode strategies to ensure finite-time convergence, as well as non-overestimation of the control gain in the presence of uncertainties and perturbations. A stability analysis demonstrates the practical finite-time stability of the system using the Lyapunov methodology. Results from the simulation underscore the effectiveness of our proposal in adhering to the desired time-varying trajectories and ensuring sensor-less inter-agent collision avoidance for the followers, even in the presence of turbulent wind conditions. Full article

Sugarcane yield plays a crucial role in food safety and biofuel production, and it is strongly influenced by climatic variations. In this context, this study applies canonical correlation analysis (CCA) to identify the climatic predictors, such as sea surface temperature, atmospheric pressure, and wind speed, that affect sugarcane yield from 1990 to 2019. Hierarchical cluster analysis applied to the performance of 58 municipalities in the eastern region of Pernambuco identified three distinct and homogeneous groups. An analysis of the CCA for the three sugarcane yield groups and climatic variables revealed that the first canonical function was significant with R = 0.82 and precision of 0.67 (p ≤ 0.05 at 95% confidence level), and that the sugarcane yield groups and climatic variables were different (Wilks’ lambda = 0.14), but they were associated. Climatic variables affected the three sugarcane productivity groups, with redundancy indices of 29.7%, 52.2%, and 59.9%. Climatic variables with positive canonical weights enhance performance, while those with negative weights decrease yields. The structural canonical loads and cross-loadings reveal that sea surface temperature plays a crucial role in determining sugarcane yield, potentially influencing precipitation and temperature patterns in the region. The sensitivity analysis confirms the stability of the canonical loads and the robustness of the results, demonstrating that this research can support yield forecasting, regional agricultural policy, and drought management. Identifying climate predictors, such as sea surface temperature, wind speed, and atmospheric pressure, enables the creation of accurate models to predict sugarcane productivity, assisting farmers in planning input management, irrigation during dry periods, and harvesting. Furthermore, climate data can inform policies that encourage sustainable agricultural practices and adaptation to climate conditions, strengthening food security and guiding the selection of more resilient sugarcane varieties, increasing production resilience. Full article

Caffeine is a natural alkaloid consumed primarily for its stimulant and metabolic effects. Some everyday products, such as coffee, tea, soft drinks, sports supplements, and even pain relievers, contain caffeine. However, excessive caffeine consumption, greater than 400 mg per day, can cause adverse effects. Therefore, this work presents an electrochemical sensor based on a molecularly imprinted polymer (MIP) electropolymerized on gold nanoparticles functionalized with p-aminothiophenol (AuNPs-pATP) for caffeine quantification. AuNPs-pATP synthesized show a spherical morphology with an average diameter of 2.54 nm. Stages of MIP formation were monitored by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) using a potassium ferrocyanide redox probe, where the following were observed: (i) an increase in conductivity upon modification of the GCE with AuNPs-pATP, (ii) the blocking of active sites during the electropolymerization step, and (iii) the release of specific cavities upon template removal, revealing consistent differences between the MIP and the control polymer (NIP). SEM images revealed three-dimensional spherical cavities on MIP surface, while the NIP showed a more compact rough surface. Caffeine quantification was performed using square wave voltammetry (SWV) with LOD of 0.195 µmol L⁻¹ and LOQ of 0.592 µmol L⁻¹. Interference studies indicated high selectivity and a high density of caffeine-specific binding sites in the MIP. Additionally, MIP sensor demonstrated reusability, good reproducibility, and stability, as well as promising results for analysis in soft drink and sports supplement samples. Full article

This paper presents an output-feedback sliding-mode control strategy for a two-DOF lower-limb exoskeleton system aimed at rehabilitation assistance for disabled individuals. The core of the approach is a cascade super-twisting observer, beginning with a super-twisting differentiator (STD) that estimates unmeasured angular velocities from measured joint angles. These velocity estimates feed into a second-stage adaptive super-twisting sliding-mode observer (ASTSMO), which accurately reconstructs external load torque disturbances affecting the system. Using these estimates, a sliding-mode controller robustly tracks the exoskeleton’s desired trajectories despite external disturbances. The stability of the proposed control scheme is rigorously established through Lyapunov-based analysis within a sliding-mode framework. Numerical simulations conducted in Matlab R2022/Simulink demonstrate the method’s effectiveness in accurately estimating unmeasured states and unknown disturbances, as well as achieving robust tracking performance in the presence of system uncertainties. Full article

In the resettlement process of water conservancy and hydropower projects, the effective development of resettlers’ livelihoods constitutes a vital component for safeguarding the rights of land-expropriated farmers and maintaining social stability. The sustainability of resettlers’ livelihoods depends on both resource endowments and their behavioral intentions. However, the traditional Sustainable Livelihoods Approach (SLA) has largely neglected behavioral driving mechanisms, thereby limiting the precision of related research. Drawing on the SLA and the Theory of Planned Behavior (TPB), this study incorporates willingness to develop as a perceived behavioral control variable into the analysis of resettlers’ livelihood capital and constructs a research model that outlines sustainable development pathways under the influence of livelihood status and perceived control. Based on this model, the sustainable livelihood capacity of 195 resettler households in Guangdong Province was comprehensively evaluated, after which the obstacle degree model was used to identify key obstacle factors across various livelihood strategies. The results demonstrate that sustainable livelihood capacity is influenced by livelihood capital, the livelihood environment, and willingness to develop, with the latter and financial capital emerging as the most significant obstacles. This framework can support the sustainable livelihood development of resettlers under evolving conditions and offer policy-makers sustainability-oriented recommendations. Full article

Viologens are promising candidates for next-generation electrochromic devices due to their reversible color changes, low operating voltages, and structural tunability. However, their practical performance is often constrained by limited color range, stability issues, and poor charge delocalization. In this study, we present a detailed density functional theory (DFT) and time-dependent DFT (TD-DFT) investigation of asymmetric viologens based on the Benzyl-4,4′-dipyridyl-R (BnV-R) framework. A series of electron-donating and electron-withdrawing substituents (CN, COOH, PO₃H₂, CH₃, OH, NH₂) were introduced via either benzyl or phenyl linkers. Geometry optimizations for neutral, radical cationic, and dicationic states were performed at the CAM-B3LYP/6-31+G(d,p) level with C-PCM solvent modeling. Electronic structure, frontier orbital distributions, and redox potentials were correlated with substituent type and linkage mode. Natural Bond Orbital analysis showed that electron-withdrawing groups stabilize reduced states, while electron-donating groups enhance intramolecular charge transfer and switching kinetics. TD-DFT calculations revealed significant bathochromic and hyperchromic shifts dependent on substitution patterns, with phenyl linkers promoting extended conjugation and benzyl spacers minimizing aggregation. Radical cation stability, quantified via ΔE_red and comproportionation constants, highlighted cyano- and amine-substituted systems as particularly promising. These insights provide predictive design guidelines for tuning optical contrast, coloration efficiency, and electrochemical durability in advanced electrochromic applications. Full article

Rheumatoid arthritis (RA) is a systemic autoimmune disorder marked by chronic inflammation of small synovial joints, with frequent extra-articular involvement of the skin and eyes. Prolonged methotrexate therapy for RA is often accompanied by serious side effects. Therefore, new drugs with less toxicity and greater effectiveness need to be developed. The ginsenoside 20(R)-25-methoxyl-dammarane-3β,12β,20-triol (AD-1), purified from Panax ginseng berry, exhibits potent anti-inflammatory and anti-cancer activities. However, the pharmacological mechanism of AD-1 in RA remains unclear. This study explored the potential anti-RA effects of AD-1 using an integrative strategy that combined network pharmacology, molecular docking, molecular dynamics simulation, and in vitro pharmacological validation. Enrichment analyses of KEGG and GO terms based on network pharmacology pointed to the PI3K/Akt signaling axis as a key regulatory pathway modulated by AD-1. Molecular docking and dynamics simulations revealed that AD-1 may have a close interaction with PIK3R1 and AKT1, demonstrating a stabilizing effect. Then, after experimental verification using human rheumatoid arthritis fibroblasts (MH7A), it was found that AD-1 suppressed cell proliferation, migration, and invasion and promoted apoptosis. Subsequent analysis of the RABC databases revealed that PIK3R1 and AKT1 were upregulated in RA, while AD-1 reduces phosphorylation of PI3K and Akt. In conclusion, these findings indicate that AD-1 exerts its anti-RA action, at least in part, through modulation of the PI3K/Akt signaling pathway and induction of apoptosis in synovial cells. This study provides a basis and new strategies for the role of ginsenosides in the treatment of RA. Full article

This paper proposes a local sliding mode control (SMC) strategy for frequency regulation and active power sharing in islanded microgrids (MGs). Unlike advanced strategies, either droop-based or droop-free, that rely on inter-inverter communication, the proposed method operates in a fully decentralized manner, using only measurements available at each inverter. In addition, it adopts a minimalist structure that avoids adaptive laws and consensus mechanisms, which simplifies implementation. A discontinuous control law is derived to enforce sliding dynamics on a frequency-based surface, ensuring robust behavior in the face of disturbances, such as clock drifts, sudden load variations, and topological reconfigurations. A formal Lyapunov-based analysis is conducted to establish the stability of the closed-loop system under the proposed control law. The method guarantees that steady-state frequency deviations remain bounded and predictable as a function of the controller parameters. Simulation results demonstrate that the proposed controller achieves rapid frequency convergence, equitable active power sharing, and sustained stability. Owing to its communication-free design, the proposed strategy is particularly well-suited for MGs operating in rural, isolated, or resource-constrained environments. A comparative evaluation against both conventional droop and communication-based droop-free SMC approaches further highlights the method’s strengths in terms of resilience, implementation simplicity, and practical deployability. Full article

Human granulocyte colony-stimulating factor (hG-CSF) is primarily used to treat neutropenia induced by cancer chemotherapy and bone marrow transplantation. The current identification test for hG-CSF relies on Western blot (WB), a labor-intensive and technically demanding method. This study aimed to screen and prepare an anti-hG-CSF nanobody to identify and quantify hG-CSF, with the ultimate goal of developing colloidal gold-labeled nanobody test strips for rapid identification. An alpaca was immunized with hG-CSF, and the VHH gene sequence encoding the anti-hG-CSF nanobody was obtained through sequencing following phage display library construction and multiple rounds of biopanning. The nanobody C68, obtained from screening, was expressed by E. coli, and its physicochemical properties such as molecular weight, isoelectric point, and affinity were characterized after purification. WB analysis demonstrated excellent performance of the nanobody in identification tests in terms of specificity, limit of detection (LOD), applicability with products from various manufacturers, and thermal stability. Additionally, we established an ELISA method for hG-CSF quantification utilizing the nanobody C68 and conducted methodological validation. Finally, colloidal gold-based test strips were constructed using the nanobody C68, with a LOD of 30 μg/mL, achieving rapid identification for hG-CSF. This study represents a novel application of nanobodies in pharmaceutical testing and offers valuable insights for developing identification tests for other recombinant protein drugs. Full article

Background: G-quadruplexes (G4s) are non-canonical higher-order nucleic acid structures that form at guanine-rich motifs, with features spanning both secondary and tertiary structural levels. These dynamic structures play pivotal roles in diverse cellular processes. Endogenous G4s (eG4s) function through their dynamically formed structures, prompting the hypothesis that their thermostability, as a key structural property, may critically influence their functionality. This study investigates the relationship between G4 stability and other functional genomic signals within eG4 regions and examines its broader impact on chromatin organization and transcriptional regulation. Methods: We developed a mapping strategy to associate in vitro-derived thermostability metrics and multi-omics functional signals with eG4 regions. A stability-centric analytical framework combining correlation analysis and causal inference using the Bayesian networks was applied to decipher causal relationships between G4 stability and the other related signals. We further analyzed the association between the stability of transcription start site (TSS)-proximal eG4s and the biological functions of their downstream genes. Results: Our analyses demonstrate that G4 thermostability exerts causal effects on epigenetic states and transcription factor binding, thereby influencing chromatin and transcription regulation. We further show distinct network architectures for G4-binding versus non-binding transcription factors. Additionally, we find that TSS-proximal eG4s are enriched in genes involved in core proliferation and stress-response pathways, suggesting that eG4s may serve as regulatory elements facilitating rapid stress responses through genome-wide coordination. Conclusions: These findings establish thermostability—though measured in vitro—as an intrinsic property that shapes eG4 functionality. Our study not only provides novel insights into the functional relevance of G4 thermostability but also introduces a generalizable framework for high-throughput G4 data interpretation, significantly advancing the functional decoding of eG4s across biological contexts. Full article