Search Results (514)

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R² = 0.86; Q²_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC₅₀ > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. Full article

Protein–polyelectrolyte nanostructures assembled via electrostatic interactions offer versatile applications in biomedicine, tissue engineering, and food science. However, several open questions remain regarding their intermolecular interactions and the influence of external conditions—such as temperature and pH—on their assembly, stability, and responsiveness. This study explores the formation and stability of networks between poly(acrylic acid) (PAA) and lysozyme (LYZ) at the nanoscale upon thermal treatment, using a combination of experimental and simulation measures. Experimental techniques of static and dynamic light scattering (SLS and DLS), Fourier transform infrared spectroscopy (FTIR), and circular dichroism (CD) are combined with all-atom molecular dynamics simulations. Model systems consisting of multiple PAA and LYZ molecules explore collective assembly and complexation in aqueous solution. Experimental results indicate that electrostatic complexation occurs between PAA and LYZ at pH values below LYZ’s isoelectric point. This leads to the formation of nanoparticles (NPs) with radii ranging from 100 to 200 nm, most pronounced at a PAA/LYZ mass ratio of 0.1. These complexes disassemble at pH 12, where both LYZ and PAA are negatively charged. However, when complexes are thermally treated (TT), they remain stable, which is consistent with earlier findings. Atomistic simulations demonstrate that thermal treatment induces partially reversible structural changes, revealing key microscopic features involved in the stabilization of the formed network. Although electrostatic interactions dominate under all pH and temperature conditions, thermally induced conformational changes reorganize the binding pattern, resulting in an increased number of contacts between LYZ and PAA upon thermal treatment. The altered hydration associated with conformational rearrangements emerges as a key contributor to the stability of the thermally treated complexes, particularly under conditions of strong electrostatic repulsion at pH 12. Moreover, enhanced polymer chain associations within the network are observed, which play a crucial role in complex stabilization. These insights contribute to the rational design of protein–polyelectrolyte materials, revealing the origins of association under thermally induced structural rearrangements. Full article

Sepsis is a fetal disease that requires a clear diagnostic biomarker for timely antibiotic treatment. Recent research has identified a pyroptosis-inducing epitope known as P5-5 in tetranectin (TN), a plasma protein produced by monocytes. Previously, we produced a 12F1 monoclonal antibody against the P5-5 and discovered that it could not only diagnose the presence but also monitor the progress of sepsis in the clinic. In the current study, we further investigated the structure site of the P5-5 and the recognition mechanism between the 12F1 mAb and the P5-5 epitope. To this end, 10 amino acids (NDALYEYLRQ) in the P5-5 were individually mutated to alanine, and their binding to the mAb was tested to confirm the most significant antigenic recognition sites. In the meanwhile, the spatial conformation of 12F1 mAb variable regions was modeled, and the molecular recognition mechanisms in detail of the mAb to the P5-5 epitope were further studied by molecular docking. Following epitope prediction and experimental verification, we demonstrated that the motif “DALYEYL” in the epitope sequence position 2−8 of TN-P5-5 is the major binding region for mAb recognition, in which two residues (4L and 8L) were essential for the interaction between the P5-5 epitope and the 12F1 mAb. Therefore, our study greatly narrowed down the previously reported motif from ten to seven amino acids and identified two Leu as critical contact residues. Finally, a single-chain variable fragment (scFv) from the 12F1 hybridoma was constructed, and it was confirmed that the identified motif and residues are prerequisites for the strong binding between P5-5 and 12F1. Altogether, the data of the present work could serve as a theoretic guide for the clinical design of biosynthetic drugs by artificial intelligence to treat sepsis. Full article

Sign language recognition plays a crucial role in enabling communication for deaf individuals, yet current methods face limitations such as sensitivity to lighting conditions, occlusions, and lack of adaptability in diverse environments. This study presents a wearable multi-channel tactile sensing system based on smart textiles, designed to capture subtle wrist and finger motions for static sign language recognition. The system leverages triboelectric yarns sewn into gloves and sleeves to construct a skin-conformal tactile sensor array, capable of detecting biomechanical interactions through contact and deformation. Unlike vision-based approaches, the proposed sensor platform operates independently of environmental lighting or occlusions, offering reliable performance in diverse conditions. Experimental validation on American Sign Language letter gestures demonstrates that the proposed system achieves high signal clarity after customized filtering, leading to a classification accuracy of 94.66%. Experimental results show effective recognition of complex gestures, highlighting the system’s potential for broader applications in human-computer interaction. Full article

Grasping objects with a high degree of anthropomorphism is a critical component in the field of highly anthropomorphic robotic grasping. However, the accuracy of contact maps and the irrationality of the grasping gesture become challenges for grasp generation. In this paper, we propose a reasonably improved generation scheme, called Diffangle-Grasp, consisting of two parts: contact map generation based on a conditional variational autoencoder (CVAE), sharing the potential space with the diffusion model, and optimized grasping generation, conforming to the physical laws and the natural pose. The experimental findings demonstrate that the proposed method effectively reduces the loss in contact map reconstruction by 9.59% in comparison with the base model. Additionally, it enhances the naturalness by 2.15%, elevates the success rate of grasping by 3.27%, reduces the penetration volume by 11.06%, and maintains the grasping simulation displacement. The comprehensive comparison and qualitative analysis with mainstream schemes also corroborate the rationality of the improvement. In this paper, we provide a comprehensive account of our contributions to enhancing the accuracy of contact maps and the naturalness of grasping gestures. We also offer a detailed technical feasibility analysis for robotic human grasping. Full article

Human Interleukin-6 (hIL-6) is a pro inflammatory cytokine that binds to its receptor, IL-6Rα followed by binding to gp130 and subsequent dimerization to form a hexamer signaling complex. As a critical inflammation mediator, hIL-6 is associated with a diverse range of diseases and monoclonal antibodies in clinical use that either target IL-6Rα or hIL-6 to inhibit signaling. Here, we perform high-throughput structure-based computational screening using ensemble docking for small-molecule antagonists for which the target conformations were taken from 600 ns long molecular dynamics simulations of the apo protein. Prior knowledge of the contact sites from binary complex studies and experimental work was incorporated into the docking studies. The top 20 scoring ligands from the in silico studies after post analysis were subjected to in vitro functional assays. Among these compounds, the ligand with the second-highest calculated binding affinity experimentally showed an ~84% inhibitory effect on IL6-induced STAT3 reporter activity at 10 μM concentration. This finding may pave the way for designing small-molecule inhibitors of hIL-6 of therapeutic significance. Full article

Prion diseases such as chronic wasting disease involve the conformational conversion of the cellular prion protein (PrP^C) into its misfolded, β-rich isoform (PrP^Sc). While chemical denaturants such as guanidine hydrochloride (GdnHCl) and urea are commonly used to study this process in vitro, their distinct molecular effects on native and misfolded PrP conformers remain incompletely understood. In this study, we employed 500 ns all-atom molecular dynamics simulations and essential collective dynamics analysis to investigate the differential effects of GdnHCl and urea on a composite PrP^C/PrP^Sc system, where white-tailed deer PrP^C interfaces with a corresponding PrP^Sc conformer. GdnHCl was found to preserve interfacial alignment and enhance β-sheet retention in PrP^Sc, while urea promoted partial β-strand dissolution and interfacial destabilization. Both denaturants formed transient contacts with PrP, but urea displaced water hydrogen bonds more extensively. Remarkably, we also observed long-range dynamical coupling across the PrP^C/PrP^Sc interface and between transiently bound solutes and distal protein regions. These findings highlight distinct, denaturant-specific mechanisms of protein destabilization and suggest that localized interactions may propagate non-locally via mechanical or steric pathways. Our results provide molecular-scale insights relevant to prion conversion mechanisms and inform experimental strategies using GdnHCl and urea to modulate misfolding processes in vitro. Full article

Aqueous solutions are not homogeneous and could be considered supramolecular systems. They can emit electromagnetic waves. Electromagnetic emission from one supramolecular system (“source”) can be received by another supramolecular system (“receiver”) without direct contact (distantly). This process represents a transfer of a “molecular signal” and causes changes in conformation and symmetry of the “receiver”. The aim of the current work is to theoretically describe such changes primarily using a solution of the chiral protein interferon-gamma (IFNγ) as an example. We provide theoretical evidence that supramolecular systems of highly diluted (HD) aqueous solutions formed by self-assembly after mechanical activation generate a stronger molecular signal compared to non-activated solutions, due to their higher energy-saturated state. Additionally, molecular signals cause supramolecular systems with complex (including chiral) structures to undergo easier changes in conformation and symmetry compared to simpler systems, enhancing their biological activity. Using statistical physics, we obtained the parameter Ic, characterizing the magnitude of conformational and symmetry changes in supramolecular (including chiral) systems caused by molecular signals. In quantum information science, there is an analogue of the parameter Ic, which characterizes the entanglement depth of quantum systems. This study contributes to the understanding of the physico-chemical basis of distant molecular interactions and opens up new possibilities for controlling the properties of complex biological and chemical systems. Full article

The subject of this study is almost contact complex Riemannian manifolds, also known as almost contact B-metric manifolds. The considerations are restricted to a special class of these manifolds, namely those of the Sasaki-like type, because of their geometric construction and the explicit expression of their classification tensor by the pair of B-metrics. Here, each of the two B-metrics is considered as an $\eta$-Ricci–Bourguignon almost soliton, where $\eta$ is the contact form. The soliton potential is chosen to be a conformal Killing vector field (in particular, concircular or concurrent) and then a generalization of the notion of conformality using contact conformal transformations of B-metrics. The resulting manifolds, equipped with the introduced almost solitons, are geometrically characterized. In the five-dimensional case, an explicit example on a Lie group depending on two real parameters is constructed, and the properties obtained in the theoretical part are confirmed. Full article

The development of functional biosensors is rapidly advancing in response to the growing demand for personalized and continuous healthcare monitoring. Two-dimensional (2D) nanostructured materials have attracted significant attention for next-generation biosensors due to their exceptional physicochemical properties, including a high surface-to-volume ratio, excellent electrical conductivity, and mechanical flexibility. The integration of 2D materials with biological recognition elements offers synergistic improvements in sensitivity, stability, and overall sensor performance. These unique properties make 2D materials particularly well-suited for constructing wearable and implantable biosensors, which require conformal contact with soft tissues, mechanical adaptability to body movement, and reliable operation under physiological conditions. This review highlights recent advances in functionalized and composite 2D materials for wearable and implantable biosensing applications. We focus on key strategies in surface modification and hybrid nanostructure engineering aimed at optimizing performance in dynamic, body-integrated environments. Finally, we discuss current challenges and future directions for clinical translation, emphasizing the potential of 2D-material-based biosensors to drive progress in personalized and precision medicine. Full article

Organic dyes are pollutants that threaten aquatic life and human health. These dyes are used in various industries; therefore, recent research focuses on the problem of their removal from wastewater. The aim of this study is to examine the clay/gum arabic nanocomposite (CG/NC) as an adsorbent to adsorb methylene blue (MB) and crystal violet (CV) dyes from synthetic wastewater. The CG/NC was characterized using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunaure–Emmett–Teller (BET). The effect of parameters that may influence the efficiency of removing MB and CV dyes was studied (dosage of CG/NC, contact time, pH values, initial concentration, and temperature), and the optimal conditions for removal were determined. Furthermore, an artificial neural network (ANN) model was adopted in this study. The results indicated that the adsorption behavior adhered to the Langmuir model and conformed to pseudo-second-order kinetics. The results also indicated that the removal efficiency reached 99%, and q_max reached 66.7 mg/g and 52.9 mg/g for MB and CV, respectively. Results also proved that CG/NC can be reused up to four times with high efficiency. The ANN models proved effective in predicting the process of the removal, with low mean squared errors (MSE = 1.824 and 1.001) and high correlation coefficients (R² = 0.945 and 0.952) for the MB and CV dyes, respectively. Full article

Friction hysteresis, ingaphenomenon observed when a sliding contact is subjected to an oscillatory motion has significant implications in fields such as tribology and robotics. Understanding and quantifying friction hysteresis is essential for improving the performance and efficiency of many sliding contacts. In this paper, we introduce six non-dimensional groups to characterize and study friction hysteresis behaviour for rough conformal sliding contacts. The proposed non-dimensional groups are specifically designed to capture the essential features of friction hysteresis loops encountered based upon previous work of present authors. The non-dimensional groups are derived from a mixed friction model composed of the transient Reynolds equation, a statistical mixed friction contact model, and the load balance. The non-dimensional groups capture physical parameters that influence friction behaviour, including normal load, sliding speed, viscosity, density, and surface roughness. By expressing these parameters in non-dimensional form, the proposed groups provide a concise and generalizable framework for analysing friction hysteresis across different systems and scales. To demonstrate the effectiveness of the non-dimensional groups, we establish a comprehensive relationship between the proposed groups and typical friction hysteresis loops encountered. Through numerical simulations, we find relationships that govern the transition between different hysteresis loop shapes and sizes. This knowledge can inform the design and optimization of systems where friction hysteresis plays a crucial role. Full article

In the field of enhanced oil recovery (EOR), particularly for water control in high-temperature reservoirs, there is a critical need for effective in-depth water shutoff and conformance control technologies. Polymer-based in situ-cross-linked gels are extensively employed for enhanced oil recovery (EOR), yet their short gelation time under high-temperature reservoir conditions (e.g., >120 °C) limits effective in-depth water shutoff and conformance control. To address this, we developed a hydrogel system via the in situ cross-linking of polyacrylamide (PAM) with phenolic resin (PR), reinforced by silica sol (SS) nanoparticles. We employed a variety of research methods, including bottle tests, viscosity and rheology measurements, scanning electron microscopy (SEM) scanning, density functional theory (DFT) calculations, differential scanning calorimetry (DSC) measurements, quartz crystal microbalance with dissipation (QCM-D) measurement, contact angle (CA) measurement, injectivity and temporary plugging performance evaluations, etc. The composite gel exhibits an exceptional gelation period of 72 h at 130 °C, surpassing conventional systems by more than 4.5 times in terms of duration. The gelation rate remains almost unchanged with the introduction of SS, due to the highly pre-dispersed silica nanoparticles that provide exceptional colloidal stability and the system’s pH changing slightly throughout the gelation process. DFT and SEM results reveal that synergistic interactions between organic (PAM-PR networks) and inorganic (SS) components create a stacked hybrid network, enhancing both mechanical strength and thermal stability. A core flooding experiment demonstrates that the gel system achieves 92.4% plugging efficiency. The tailored nanocomposite allows for the precise management of gelation kinetics and microstructure formation, effectively addressing water control and enhancing the plugging effect in high-temperature reservoirs. These findings advance the mechanistic understanding of organic–inorganic hybrid gel systems and provide a framework for developing next-generation EOR technologies under extreme reservoir conditions. Full article

Surface texturing is designed to improve the functional properties of machine elements by generating dimples on the surface contacted. Friction and wear resistance can also be improved by creating diamond-like carbon (DLC) coatings. These two techniques were combined to extend the lifetime of the elements and minimise friction in reciprocating conformal sliding contact. This work is functionally important for assemblies operating under high normal loads. Experiments were carried out in initially lubricated reciprocating sliding contact using an Optimol SRV 5 tribotester in the flat-on-flat configuration. The disc samples were untextured, laser textured, and DLC-coated untextured and textured. The combination of DLC coating and surface texturing caused an enhancement of the tribological performance of the sliding pair compared to that of untextured discs with and without DLC coating and textured discs without DLC coating. The DLC coating of the untextured disc caused a growth in the lifetime of a friction pair by a factor of 2.4. Seizure resistance also increased due to surface texturing of the steel disc for pit area ratios of 9 and 13%. Combining surface texturing with pit area ratios of 3 and 9% and DLC coating led to a decrease in the coefficients of friction of sliding pairs compared to only textured and coated discs. The DLC coating caused a decrease in the wear of the disc sample and reduction in wear levels of the counter samples in comparison to those of textured discs without DLC coatings. Full article

Recent advancements in wearable electronics have significantly enhanced human–device interaction, enabling applications such as continuous health monitoring, advanced diagnostics, and augmented reality. While progress in material science has improved the flexibility, softness, and elasticity of these devices for better skin conformity, their optical properties, particularly transparency, remain relatively unexplored. Transparent wearable electronics offer distinct advantages: they allow for non-invasive health monitoring by enabling a clear view of biological systems and improve aesthetics by minimizing the visual presence of electronics on the skin, thereby increasing user acceptance. Hydrogels have emerged as a key material for transparent wearable electronics due to their high water content, excellent biocompatibility, and tunable mechanical and optical properties. Their inherent softness and stretchability allow intimate, stable contact with dynamic biological surfaces. Furthermore, their ability to support ion-based conductivity is advantageous for bioelectronic interfaces and physiological sensors. Current research is focused on advancing hydrogel design to improve transparency, mechanical resilience, conductivity, and adhesion. The core components of transparent wearable systems include physiological sensors, energy storage devices, actuators, and real-time displays. These must collectively balance efficiency, functionality, and long-term durability. Practical applications span continuous health tracking and medical imaging to next-generation interactive displays. Despite progress, challenges such as material durability, scalable manufacturing, and prolonged usability remain. Addressing these limitations will be crucial for the future development of transparent, functional, and user-friendly wearable electronics. Full article