Search Results (244)

Long-term water flooding development has exacerbated reservoir heterogeneity, and traditional polymer gels are unable to simultaneously meet the requirements of high injectability and strong plugging strength. If the viscosity of the polymer is high, its injectability will be poor; on the contrary the viscosity is low, the plugging strength will be poor, which severely restricts the oil recovery effect. This study synthesized an NBAP through free radical polymerization followed by a substitution reaction, and a plugging system (NBAP-B1) was subsequently formed by combining the polymer with a Cr³⁺ crosslinking agent. Rheological experiments demonstrated that the system exhibited significant shear thinning behavior, as well as excellent temperature and salt resistance. Gelation experiments indicated that the NBAP-B1 system featured controllable gelation time (20~150 h) and high gelation strength (J grade), along with excellent resistance to both high temperature and high salinity. Microscopic analysis revealed that the gel formed by NBAP-B1 possessed a dense and uniform three-dimensional network structure. Injection and plugging experiments demonstrated that NBAP-B1 exhibited optimal injectability and outstanding plugging performance. Additionally, profile control and displacement tests revealed a 18.37% enhancement in oil recovery efficiency by water flooding after the application of NBAP-B1 for conformance control. Collectively, these results demonstrate that the NBAP exhibits significantly superior performance compared to single component systems. It combines excellent injectability with high strength plugging capability, offering an effective approach for enhancing oil recovery in low permeability reservoirs. Full article

To address limitations such as cleaning difficulties or secondary contamination/damage of cultural relics caused by the uncontrollable diffusion of water/cleaning agent/dirty liquids during the cleaning process in traditional cleaning methods, this study, using cotton textiles as an example, systematically investigated the cleaning efficacy of four in situ methods (blank gel, cleaning gel, ultrasonic emulsification, and gel + ultrasonic emulsification synergistic cleaning) on eight types of stains, including sand, clay, rust, blood, ink, oil, and mixed solid/liquid stains. Building upon this, this study proposed an efficient, targeted, in situ, and controllable cleaning strategy tailored for fragile, stained textile relics. Results demonstrated that, regardless of the stain type, the synergistic cleaning method of G+U (gel poultice + ultrasonic emulsification) consistently outperformed the cleaning methods of blank gel poultice, cleaning gel poultice, and ultrasonic emulsification. Furthermore, the gel loaded with cleaning agents was always more effective than the blank gel (unloaded cleaning agents). The poultice methods of blank gel and cleaning gel were better suited for solid stains, while the ultrasonic emulsification cleaning method was more effective for liquid stains. Meanwhile, it was also found that the optimal cleaning method proposed in this study (the G+U synergistic cleaning method) was a cleaning method that restricted the cleaning agent within the gel network/emulsion system, and utilized the porous network physical structure of gel, the chemical action of emulsion’s wetting/dissolving dirt, and the cavitation synergistic effect of ultrasound to achieve the targeted removal of contaminants from relics’ surfaces. Crucially, the cleaning process of G+U also had the characteristics of controlling the cleaning area at the designated position and effectively regulating the diffusion rate of the cleaning solution within the treatment zone, as well as the reaction intensity. Therefore, the proposed optimal (the synergistic cleaning method of G+U) cleaning method conforms to the significant implementation of the “minimal intervention and maximal preservation” principle in modern cultural heritage conservation. Consequently, the synergistic cleaning method of G+U holds promise for practical application in artifact cleaning work. Full article

The SETD6 protein lysine methyltransferase monomethylates specific lysine residues in a diverse set of substrates which contain the target lysine residue in a highly variable amino acid sequence context. To investigate the mechanism underlying this multispecificity, we analyzed SETD6 substrate recognition using AlphaFold 3 docking and peptide SPOT array methylation experiments. Structural modeling of the SETD6–E2F1 complex suggested that substrate binding alone is insufficient to restrict SETD6 activity to only one lysine residue, pointing to additional sequence readout at the target site. Methylation of mutational scanning peptide SPOT arrays derived from four different SETD6 substrates (E2F1 K117, H2A.Z K7, RELA K310, and H4 K12) revealed sequence preferences of SETD6 at positions −1, +2, and +3 relative to the target lysine. Notably, glycine or large aliphatic residues were favored at −1, isoleucine/valine at +2, and lysine at +3. These preferences, however, were sequence context dependent and variably exploited among different substrates, indicating conformational variability of the enzyme–substrate interface. Mutation of SETD6 residue L260, which forms a contact with the +2 site in the available SETD6-RELA structure, further demonstrated substrate-specific differences in recognition at the +2/+3 sites. Together, these findings reveal a versatile mode of peptide recognition in which the readout of each substrate position depends on the overall substrate peptide sequence. These findings can explain the multispecificity of SETD6 and similar mechanisms may underlie substrate selection in other protein methyltransferases. Full article

Traditional pneumatic soft grippers often suffer from a limited contact area and poor shape-matching performance, restricting their effectiveness in handling objects with complex or delicate surfaces. To address this problem, this study proposed an integrated soft gripper that combines pneumatic actuators with specially designed mechanical metamaterials, aiming to optimize deformation characteristics and enhance gripping surface conformity to target objects. The key contributions are as follows: (1) A novel integrated structure is designed, incorporating pneumatic actuators and mechanical metamaterials. (2) A highly efficient design framework based on deep learning is developed, incorporating forward and inverse neural networks to enable efficient performance prediction and inverse design. (3) The novel gripper is fabricated using stereolithography (SLA) and silicone casting, with experimental validation conducted via machine vision and multi-shape object tests. FEA simulations and experiments demonstrate significant improvements in shape matching: average deviations of gripping surfaces from targets are greatly reduced after optimization. This work validates that integrating mechanical metamaterials with data-driven design enhances the gripper’s adaptability, providing a feasible solution for high-performance soft gripping systems. Full article

In this study, the insufficient ability of tartary buckwheat protein (TBP) to stabilize Pickering emulsions was addressed by preparing TBP–sodium alginate (SA) composite particles via cross-linking and systematic optimization of the preparation parameters. The results showed that at a pH of 9.0 with 1.0% (w/v) TBP and 0.2% (w/v) SA, the zeta potential of the prepared TBP–SA composite particles was significantly more negative, and the particle size was significantly larger, than those of TBP, while emulsifying activity index and emulsifying stability index increased to 53.76 m²/g and 78.78%, respectively. Scanning electron microscopy confirmed the formation of a dense network structure; differential scanning calorimetry revealed a thermal denaturation temperature of 83 °C. Fourier transform infrared spectroscopy and surface hydrophobicity results indicated that the complex was formed primarily through hydrogen bonding and hydrophobic interactions between TBP and SA, which induced conformational changes in the protein. The Pickering emulsion prepared with 5% (w/v) TBP–SA composite particles and 60% (φ) oil phase was stable during 4-month storage, at a high temperature of 75 °C, high salt conditions of 600 mM, and pH of 3.0–9.0. The stabilization mechanisms may involve: (1) strong electrostatic repulsion provided by the highly negative zeta potential; (2) steric hindrance and mechanical strength imparted by the dense interfacial network; and (3) restriction of droplet mobility due to SA-induced gelation. Full article

Dihydroorotase (DHOase) catalyzes the reversible cyclization of N-carbamoyl-L-aspartate to dihydroorotate, a key step in de novo pyrimidine biosynthesis. A flexible active site loop in DHOase undergoes conformational switching between loop-in and loop-out states, influencing substrate binding, catalysis, and inhibitor recognition. In this study, we identified 5-fluoroorotate (5-FOA) and myricetin as inhibitors of Saccharomyces cerevisiae DHOase and systematically analyzed 97 crystal structures and AlphaFold 3.0 models of DHOases from 16 species representing types I, II, and III. Our results demonstrate that loop conformation is not universally ligand-dependent and varies markedly across DHOase types, with type II enzymes showing the greatest flexibility. Notably, S. cerevisiae DHOase consistently adopted the loop-in state, even with non-substrate ligands, restricting accessibility for docking-based inhibitor screening. Docking experiments with 5-FOA and myricetin confirmed that the loop-in conformation prevented productive active-site docking. These findings highlight the importance of selecting appropriate loop conformations for structure-based drug design and underscore the need to account for loop dynamics in inhibitor screening. Full article

When a city decides to undertake a certain urban project, is it modifying just the physical environment or the social fabric that dwells within? This work investigates the relationship between the geometric configuration of urban space (geometry–city) and the topology of the networks of encounters of its inhabitants (network–city) that form through daily interactions. The research departs from the hypothesis that changes in geometry–city would not significantly alter the topology of the network–city, testing this proposition conceptually through abstract computational simulations developed specifically for this study. In this simulator, abstract maps with buildings distributed over different primary geometries are generated and have activities (use: home or work) and a population assigned. Encounters of the “inhabitants” are registered while daily commute routines, enough to achieve differentiation and stability, are run. The initial results revealed that the geometry description was not enough, and definitions regarding activity attribution were also necessary. Thus, we could not confirm nor reject the original hypothesis exactly, but it had to be complemented, including the idea of an activity–city dimension. We found that despite the geometry–city per se not determining the structure of the network–city, the spatial (geometric) distribution of activities directly impacts the resulting topology. Urban geometry influences networks–city only insofar as it conforms to activity–city, defining areas for activities or restricting routing between them. But it is the geometry of localization of the activities that has a direct impact on the topology of the network–city. This conceptual discovery can have significant implications for urban planning if corroborated in real-world situations. It could suggest that land use policies may be more effective for intervening in network-based characteristics, like social cohesion and resilience, than purely morphological interventions. Full article

Background/Objectives: Cancer progression is characterized by the suppression of apoptosis, activation of metastatic processes, and dysregulation of cell proliferation. The proper functioning of these mechanisms relies on critical signaling pathways, including Phosphoinositide 3-kinase/Protein kinase B/mammalian Target of Rapamycin (PI3K/Akt/mTOR), Mitogen-Activated Protein Kinase (MAPK), and Signal Transducer and Activator of Transcription 3 (STAT3). Although curcumin and resveratrol exhibit anticancer properties and affect these pathways, their pharmacokinetic limitations, including poor bioavailability and low solubility, restrict their clinical application. The aim of our study was to evaluate the synergistic anticancer potential of curcumin and resveratrol through hybrid molecules rationally designed from these compounds to mitigate their pharmacokinetic limitations. Furthermore, we analyzed the multi-target anticancer effects of these hybrids on the AKT serine/threonine kinase 1 (AKT1), MAPK, and STAT3 pathways using in silico molecular modeling approaches. Methods: Three hybrid molecules, including a long-chain (ELRC-LC) and a short-chain (ELRC-SC) hybrid, an ester-linked hybrid, and an ether-linked hybrid (EtLRC), were designed using the Avogadro software (v1.2.0), and their geometry optimization was carried out using Density Functional Theory (DFT). The electronic properties of the structures were characterized through Frontier Molecular Orbital (FMO), Molecular Electrostatic Potential (MEP), and Fourier Transform Infrared (FTIR) analyses. The binding energies of the hybrid molecules, curcumin, resveratrol, their analogs, and the reference inhibitor were calculated against the AKT1, MAPK, and STAT3 receptors using molecular docking. The stabilities of the best-fitting complexes were evaluated through 100 ns molecular dynamics (MD) simulations, and their binding free energies were estimated using the Molecular Mechanics/Poisson–Boltzmann Surface Area (MM/PBSA) method. Results: DFT analyses demonstrated stable electronic characteristics for the hybrids. Molecular docking analyses revealed that the hybrids exhibited stronger binding compared to curcumin and resveratrol. The binding energy of −11.4 kcal/mol obtained for the ELRC-LC hybrid against AKT1 was particularly remarkable. Analysis of 100 ns MD simulations confirmed the conformational stability of the hybrids. Conclusions: Hybrid molecules have been shown to exert multi-target mechanisms of action on the AKT1, MAPK, and STAT3 pathways, and to represent potential anticancer candidates capable of overcoming pharmacokinetic limitations. Our in silico-based study provides data that will guide future in vitro and in vivo studies. These rationally designed hybrid molecules, owing to their receptor affinity, may serve as de novo hybrid inhibitors. Full article

Injection molding is widely used for mass-producing plastic components, demanding precise thermal control to optimize cycle times and part quality. Traditional CNC-machined molds limit design flexibility and restrict advanced cooling features like conformal cooling channels (CCCs). Integrating CCCs improves cooling performance, reduces cycle times, and offers more efficient, cost-effective designs. Additive manufacturing (AM), especially Metal-Fused Filament Fabrication (Metal-FFF), offers geometries unattainable by machining. While most mold research focuses on Laser Powder Bed Fusion (LPBF), the feasibility of Metal-FFF molds remains underexplored. This study presents the design, fabrication, and experimental evaluation of an injection mold produced via Metal-FFF with integrated CCCs. The process included computational design, resistance simulations, fabrication, debinding, sintering, and post-processing, followed by testing under injection molding conditions. Results show that Metal-FFF molds with CCCs boost cooling efficiency, cutting cycle times by about 30% compared to conventional molds, while offering greater design freedom and economic benefits. Nonetheless, issues such as porosity and shrinkage need further refinement to fully leverage this technology for industrial use. Full article

Background: Anaplastic lymphoma kinase (ALK) is a validated oncogenic driver in non-small cell lung cancer and other malignancies, making it a clinically relevant target for small-molecule inhibition. Methods: Here, we report a computational discovery pipeline integrating structure-based virtual screening, machine learning-guided prioritization, molecular dynamics simulations, and binding free energy analysis to identify potential ALK inhibitors from a natural product-derived subset of the ZINC20 database. We trained and benchmarked eleven machine learning models, including tree-based, kernel-based, linear, and neural architectures, on curated bioactivity datasets of ALK inhibitors to capture nuanced structure-activity relationships and prioritize candidates beyond conventional docking metrics. Results: Six compounds were shortlisted based on binding affinity, solubility, bioavailability, and synthetic accessibility. Molecular dynamics simulations over 100 ns revealed stable ligand engagement, with limited conformational fluctuations and consistent retention of the protein’s structural integrity. Key catalytic residues, including GLU105, MET107, and ASP178, displayed minimal fluctuation, while hydrogen bonding and residue interaction analyses confirmed persistent engagement across all ligand-bound complexes. Binding free energy estimates identified ZINC3870414 and ZINC8214398 as top-performing candidates, with ΔG_total values of –46.02 and –46.18 kcal/mol, respectively. Principal component and dynamic network analyses indicated that these compounds restrict conformational sampling and reorganize residue communication pathways, consistent with functional inhibition. Conclusions: These results highlight ZINC3870414 and ZINC8214398 as promising scaffolds for further optimization and support the utility of integrating machine learning with dynamic and network-based metrics in early-stage kinase inhibitor discovery. Full article

The current work establishes the geometrical bearing for hypersurfaces in a Golden Riemannian manifold with constant golden sectional curvature with respect to k-almost Newton-conformal Ricci solitons. Moreover, we extensively explore the immersed r-almost Newton-conformal Ricci soliton and determine the sufficient conditions for total geodesicity with adequate restrictions on some smooth functions using mathematical operators. Furthermore, we go over some natural conclusions in which the gradient k-almost Newton-conformal Ricci soliton on the hypersurface of the Golden Riemannian manifold becomes compact. Finally, we establish a Schur’s type inequality in terms of k-almost Newton-conformal Ricci solitons immersed in Golden Riemannian manifolds with constant golden sectional curvature. Full article

Amyloids are protein aggregates having a cross-β structure, and they reveal some unusual properties, like interactions with specific dyes and resistance to actions of detergents and proteases, as well as the capability to force some proteins to change their conformation from a soluble form to aggregates. The occurrence of amyloids is not restricted to humans and animals, as they also exist in microbial cells. However, contrary to animals, where amyloids are usually pathological molecules, bacterial amyloids are often functional, participating in various physiological processes. In this review, we focus on a specific property of bacterial amyloids, namely their ability to interact with nucleic acids and resultant regulatory mechanisms. Moreover, some of these interactions might play indirect roles in the pathomechanisms of human neurodegenerative and inflammatory diseases; these aspects are also summarized and discussed in this review. 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

Cyclohexane-containing semi-aromatic polyamides (c-SaPA) exhibit excellent comprehensive properties. Existing studies predominantly focus on synthesis and modification, while fundamental investigations into pyrolysis mechanisms remain limited, which restricts the development of advanced materials for high-performance applications such as automotive and energy systems. This study employs Reactive Force Field Molecular Dynamics (ReaxFF-MD) simulations to establish a pyrolysis model for poly(terephthaloyl-hexahydro-m-xylylenediamine) (PHXDT), systematically probing its pyrolysis kinetics and evolutionary pathways under elevated temperatures. The simulation results reveal an activation energy of 107.55 kJ/mol and a pre-exponential factor of 9.64 × 10¹³ s⁻¹ for the pyrolysis process. The primary decomposition pathway involves three distinct stages. The first is initial backbone scission generating macromolecular fragments, followed by secondary fragmentation that preferentially occurs at short-chain hydrocarbon formation sites alongside radical recombination. Ultimately, the process progresses to deep dehydrogenation, carbonization, and heteroatom elimination through sequential reaction steps. Mechanistic analysis identifies multi-pathway pyrolysis involving carboxyl/amide bond cleavage and radical-mediated transformations (N-C-O, C-C-O, OH· and H·), yielding primary products including H₂, CO, H₂O, CH₃N, C₂H₂, and C₂H₄. Crucially, the cyclohexane structure demonstrates preferential participation in dehydrogenation and hydrogen transfer reactions due to its conformational dynamic instability and low bond dissociation energy, significantly accelerating the rapid generation of small molecules like H₂. Full article

KRAS is a pivotal oncoprotein that regulates cell proliferation and survival through interactions with downstream effectors such as RAF1. Despite significant advances in understanding KRAS biology, the structural and dynamic mechanisms of KRAS allostery remain poorly understood. In this study, we employ microsecond molecular dynamics simulations, mutational scanning, and binding free energy calculations together with dynamic network modeling to dissect how engineered DARPin proteins K27, K55, K13, and K19 engage KRAS through diverse molecular mechanisms ranging from effector mimicry to conformational restriction and allosteric modulation. Mutational scanning across all four DARPin systems identifies a core set of evolutionarily constrained residues that function as universal hotspots in KRAS recognition. KRAS residues I36, Y40, M67, and H95 consistently emerge as critical contributors to binding stability. Binding free energy computations show that, despite similar binding modes, K27 relies heavily on electrostatic contributions from major binding hotspots while K55 exploits a dense hydrophobic cluster enhancing its effector-mimetic signature. The allosteric binders K13 and K19, by contrast, stabilize a KRAS-specific pocket in the α3–loop–α4 motif, introducing new hinges and bottlenecks that rewire the communication architecture of KRAS without full immobilization. Network-based analysis reveals a strikingly consistent theme: despite their distinct mechanisms of recognition, all systems engage a unifying allosteric architecture that spans multiple functional motifs. This architecture is not only preserved across complexes but also mirrors the intrinsic communication framework of KRAS itself, where specific residues function as central hubs transmitting conformational changes across the protein. By integrating dynamic profiling, energetic mapping, and network modeling, our study provides a multi-scale mechanistic roadmap for targeting KRAS, revealing how engineered proteins can exploit both conserved motifs and isoform-specific features to enable precision modulation of KRAS signaling in oncogenic contexts. Full article