Search Results (562)

Smart hydrogel systems with stimuli-responsive properties are increasingly being investigated in combination with advanced additive manufacturing techniques for targeted drug delivery and wound healing in regenerative medicine; however, their clinical translation remains limited by challenges related to material performance, design complexity, and manufacturing scalability. This review analyzes recent developments in smart hydrogel design and 4D-printed scaffolds, with emphasis on programmable and stimuli-responsive architectures. The literature is selectively evaluated based on relevance to (i) hydrogel structure–property relationships, (ii) 3D/4D printing strategies, and (iii) demonstrated performance in drug delivery and wound healing applications. The analysis highlights design approaches enabling spatiotemporal control of drug release and dynamic scaffold behavior, while also examining how fabrication methods influence functional outcomes. Major limitations are critically assessed, including issues of reproducibility, mechanical stability, long-term performance, and the gap between experimental studies and clinical application. Challenges in defining and implementing 4D printing in biomedical contexts are discussed as well. Overall, this review identifies current design trade-offs, outlines priorities for improving reliability and translational potential, and synthesizes emerging trends in 3D and 4D printed hydrogel scaffolds for precision drug delivery and regenerative wound therapy. Full article

This study aimed to investigate the wound-healing mechanisms of chitosan with a defined molecular weight (MW) and degree of deacetylation (DD), and to explore its potential in hydrogel formulations, optimized for enhanced antibacterial performance. An active molecular chitosan (AMC) was prepared via enzymatic treatment to target a specific MW range with excellent biological activity. The antibacterial, anti-inflammatory, and wound-healing effects of AMC-based hydrogels were evaluated. Given AMC’s antibacterial activity against vancomycin-resistant Staphylococcus aureus (VRSA), its anti-inflammatory effects were also evaluated in full-thickness wounds in BALB/c nude mice. Anti-inflammatory effects were assessed using ELISA and immunohistochemical staining to measure levels of IL-1β, IL-4, IL-6, IL-10, and TNF-α. AMC treatment significantly reduced wound size and suppressed inflammatory cytokine production. These results suggest that hydrogels containing AMC may enhance both antibacterial and anti-inflammatory properties, potentially promoting wound healing. Full article

Soft story irregularity poses a critical seismic risk to existing building stocks. While current seismic codes define stiffness irregularity factors to detect this vulnerability, they are typically evaluated based solely on initial elastic properties. This study investigates the evolution of these code-defined factors (ASCE/SEI-7, UBC, NBC, TBEC-2018, and BSL) within the post-elastic range to examine how structural damage affects soft story irregularity. The methodology comprises two phases: a low-strength RC plane frame (Case A) and a parametric study on a 3D RC building with incrementally increased ground story heights (Case B). Nonlinear pushover analyses were conducted to track the variation in irregularity factors at each pushover step and examined graphically. Results demonstrate that soft story behavior is not a static characteristic; irregularity factors deteriorate significantly as plastic hinges form. Crucially, several models that initially satisfied code limits in the elastic range eventually exceeded irregularity thresholds under inelastic behavior. This indicates that relying solely on initial stiffness may mask latent irregularities emerging during seismic actions. Consequently, to capture the true severity of soft story mechanisms, it is recommended that stiffness irregularity factors be evaluated at target displacement levels corresponding to the design earthquake. Full article

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease, with advanced stages potentially progressing to hepatocellular carcinoma. It is a multifactorial condition associated with metabolic syndrome, diabetes, and hormonal imbalance, leading to metabolic alterations that are intensified by inflammation. An important additional factor that amplifies these effects is oxidative stress, which interacts with inflammatory pathways and contributes to disease progression. This review evaluates evidence from in vitro, in vivo, and clinical studies on widely investigated natural compounds, including cinnamic acid, stilbene and quinone derivatives, coumarinoids, tannins, and miscellaneous phenol-containing compounds and alkaloids, focusing on their antioxidant, anti-inflammatory and multi-functional properties. These compounds have demonstrated beneficial effects such as reduction of lipid accumulation, improvement of insulin resistance, modulation of inflammatory cytokines (e.g., TNF-α, IL-6), and attenuation of oxidative stress markers, with several studies reporting improvements in liver enzymes and histological features of steatosis. The aim is to assess their potential to improve NAFLD beyond their established biological activities and to explore their repositioning potential as multi-targeted agents for complementary or second-line therapeutic strategies. Their plant-derived origin and broad therapeutic profiles suggest a favorable safety margin. However, further well-designed clinical studies are required to better define their efficacy, optimal dosing, pharmacokinetics and safety, as well as to clarify their mechanisms of action and their potential role in NAFLD management. Full article

The development of tight heavy-oil reservoirs is severely hampered by the high viscosity and poor mobility of crude oil caused by strong intermolecular stacking interactions among asphaltenes, coupled with the substantial adsorption loss and inadequate deep transport capacity of conventional displacement agents. By targeted penetrant delivery, a novel nanoemulsion system with a well-defined “core–shell” architecture was synthesized to address these critical challenges. The physicochemical properties, stability and oil displacement performance were evaluated. The prepared nanoemulsion exhibited an ultrasmall and uniform particle size distribution between 10 nm and 20 nm. It also demonstrated exceptional dispersibility in aqueous media and remarkable thermal and salinity stability under reservoir conditions. Furthermore, an ultralow critical micelle concentration of approximately 0.01% could be achieved and the oil–water interfacial tension was reduced to 7.3 × 10⁻² mN/m, significantly outperforming the conventional surfactant AES. Core flooding tests revealed that the proposed nanoemulsion enhanced oil recovery by 37.1% and attained a displacement efficiency of 68.9% in oil-wet capillary models. Molecular dynamics simulations further elucidated the underlying synergistic mechanism. The hydrophilic shell minimized adsorption on rock surfaces, facilitating deep migration within nanoporous channels. The hydrophobic core, containing terpinene as a penetrant, effectively disrupted the π-π stacking of asphaltenes due to its nonplanar molecular configuration. This disruption transformed the asphaltene aggregates from a tightly packed state to a dispersed state, resulting in substantial viscosity reduction. This work elucidated the mechanism of asphaltene aggregate disruption by nanoemulsions at the molecular level, offering a promising and theoretically grounded strategy for the efficient exploitation of tight heavy-oil reservoirs. Full article

Background/Objectives: Due to the widespread problem of antimicrobial resistance (AMR), there is an urgent need to identify new antibacterial targets that act through mechanisms distinct from those of existing antibiotics. One of these targets is the essential cell division protein FtsQ, which is a central hub of the Gram-negative divisome, but the druggability of its extensive protein–protein interaction (PPI) interfaces remains poorly defined. Here, we present a comprehensive structure-based in silico characterization of Escherichia coli FtsQ aimed at identifying and prioritizing druggable regions for PPI modulation. Methods: We analyzed E. coli FtsQ in both apo and complexed states (FtsQB, FtsQL, and FtsQBL) using a combination of pocket-mapping tools (FTMap and SiteMap), evolutionary conservation analysis (ConSurf), and structure property assessment (BLAST, ProBiS) to map and evaluate potential binding pockets of FtsQ protein. Results: Eight potential binding sites were predicted across the β and POTRA domains of FtsQ. One previously unreported site within the POTRA domain was prioritized as a candidate site, characterized by favorable druggability scores, strong evolutionary conservation, and a putative role in the FtsQ–FtsW/FtsN/FtsI interaction network. In contrast, two highly conserved sites at the FtsQ–FtsB/FtsL interaction interface were structurally flat, indicating limited suitability for classical small-molecule binding and greater compatibility with alternative modalities such as macrocycles or peptidomimetics. Conclusions: Although FtsQ lacks deep canonical binding pockets, this study proposes several conserved and potentially tractable regions as candidate sites, supporting its potential as a non-classical but promising antibacterial target for disrupting bacterial cytokinesis. Full article

The utilization of immunomodulatory nanomaterials, i.e., leveraging their unique properties to enhance immune responses, represents a transformative approach for the treatment of various diseases. Recent advancements in nanotechnology have enabled the design of nanomaterials capable of delivering immunomodulatory agents in a targeted manner, such as cytokines, antibodies, and nucleic acids, to specific cells or tissues involved in immune regulation. These nanomaterials, including nanoparticles, liposomes, nanogels, nanoemulsions, dendrimers, MXenes and extracellular vesicles, have been increasingly tailored to modulate immune responses with precision and efficacy. This targeted approach not only enhances therapeutic outcomes but also reduces off-target effects, minimizing systemic toxicity. In this review, an overview of immunomodulatory nanomaterials and their biomedical applications are highlighted. Herein, we have discussed different types of nanomaterials and their design strategies, interactions with different immune system components (macrophages, dendritic cells (DCs), neutrophils, T lymphocytes (CD4⁺ helper T-cells, CD8⁺ cytotoxic T-cells, regulatory T-cells/Tregs, and memory T-cells), and B lymphocytes), and immunomodulation mechanisms. Furthermore, nanomaterial-based immunomodulation strategies to enhance cancer immunotherapy, wound healing, and bone regeneration and the treatment of infectious diseases, autoimmune diseases, and allergy and are discussed in detail. In addition to therapeutic applications, selected nanomaterial platforms demonstrate significant potential in pharmaceutical formulations by improving drug stability, controlled release, and bioavailability, as well as in cosmetology through skin-targeted delivery, anti-inflammatory activity, immune protection, and enhanced tissue regeneration. Finally, clinical trial updates, challenges and future prospects are outlined. Key findings indicate that lipid-based, polymeric, inorganic nanoparticles and dendrimers provide complementary advantages for immunomodulation, including efficient delivery, controlled release, multifunctionality, and precise immune targeting. Despite safety, regulatory, and scalability challenges, these systems show strong potential for advancing precision and personalized medicine. Taken together, these innovations hold great promise for personalized medicine approaches, wherein nanomaterials can be tailored to individual patient profiles for more effective and precise disease treatment and prevention strategies. This review focuses primarily on the mechanistic interactions between immunomodulatory nanomaterials and immune cells, including macrophages, dendritic cells, neutrophils, T lymphocytes, and B lymphocytes, rather than providing an exhaustive treatment of physicochemical optimization parameters such as particle size or surface modification chemistry, which fall outside the defined scope of this work. Full article

Background/Objectives: The growing prevalence of obesity necessitates innovative gut-targeted material strategies to modulate diet-associated metabolic dysfunction. This study investigates a spray-dried konjac glucomannan–montmorillonite (KGM-MMT) hybrid designed to integrate fermentable polysaccharide properties with luminal lipid-adsorptive clay functions within a single micro-engineered formulation. Methods: In HFD-fed mice treated for 42 days with 2% w/w KGM-MMT, cumulative body weight gain was attenuated by 7.6%, with an AUC of 5094 ± 52.95, compared to 5513 ± 81.35 in HFD controls (p < 0.0001). Results: Serum IL-6 concentrations were reduced by 97% (p = 0.0002), while blood glucose decreased by 46% (p < 0.0001); these effects were greater than those observed with MMT (24%, p = 0.0271) and KGM (16%, ns). Gut microbiota profiling demonstrated a significant 6.2-log₂-fold increase in Lactobacillaceae (p = 0.023) and a 2.4-log₂-fold increase in Enterococcaceae (p = 0.015) following KGM-MMT treatment. Functional shifts inferred from 16S rRNA gene-based prediction indicated a 1.9-fold increase in short-chain fatty acid-related pathways and a 5.4-fold increase in bile acid deconjugation pathways. Conclusions: Although the KGM-MMT hybrid did not consistently outperform its individual components across all endpoints, it consolidated complementary KGM- and MMT-associated effects within a single dosage form. These findings support spray-dried KGM-MMT as a gut-targeted biomaterial strategy that integrates multiple luminal and microbiota-associated functions within a single formulation. Future studies should define dose–response relationships, validate microbiota-derived functional predictions using higher-resolution approaches, and assess durability and safety under longer-term exposure. Full article

The integration of rooted plant flour into traditional noodle matrices, such as rice noodles and qingke noodles, represents a novel approach to enhancing the nutritional and sensory profiles of staple foods. This study investigates the volatile flavor components and functional compounds derived from rooted plant flours, including Gongmi “tribute rice”, qingke “highland barley” flour, kudzu vine flour, Gastrodia elata blume flour, dried ginger flour, and fishwort root flour, when incorporated into rice and qingke noodles. The novelty of this research lies in its comprehensive analysis of how these flours influence not only the nutritional and textural properties but also the volatile organic compounds (VOCs) that define sensory acceptance and health benefits. Using advanced gas chromatography mass spectrometry (GC-MS), we identified key VOCs, such as esters, aldehydes, and terpenes, which contribute to unique flavor profiles like umami, sweetness, and earthy notes in fortified noodles. Additionally, the study highlights the best functional compounds for health, including polyphenols, resistant starch, and polysaccharides, which demonstrate significant antioxidants, anti-inflammatory, and cholesterol-lowering properties. For instance, highland barley enriched flour exhibited high levels of phenolic compounds and carotenoids, which correlated with improved antioxidant activity and a reduced glycemic index. Similarly, Gongmi flour contributed elevated levels of γ-aminobutyric acid (GABA) and rutin, enhancing the rice noodles’ potential to manage metabolic diseases and support cardiovascular health. Molecular docking analyses predicted strong interactions between key volatile compounds (e.g., 3-dihydro-1, 3-trimethyl-33-phenyl-1H-indene) and metabolic targets like ACE and SGLT1, suggesting mechanisms for their cardioprotective and anti-diabetic effects. This research provides a groundbreaking framework for developing next generation functional foods by leveraging rooted plant flours to bridge the gap between sensory appeal and health efficacy, offering strategic insights for personalized nutrition and sustainable food production. Full article

Geometric problem-solving has always been a great challenge in the field of deductive reasoning and artificial intelligence. Symmetry is a defining characteristic of geometric shapes and properties. Consequently, the application of symmetry principles to geometric reasoning arises as a natural choice. To address the efficiency degradation and limited generalization, we propose FGeo-ISRL, a neural-symbolic inverse search framework whose core is the synergistic integration of a task-fine-tuned large language model and Monte Carlo Tree Search. Under the formal framework of FormalGeo, geometric theorems are iteratively applied starting from the given conditions and the target conclusion, in order to infer the necessary supporting premises. The large language model simultaneously serves as a policy network and a value network, guiding theorem application decisions and evaluating intermediate proof states, whereas the Monte Carlo Tree Search performs structured exploration over the state space, both training for policy refinement and inference for online search. The reinforcement learning agent is trained with a hybrid reward scheme, combining immediate feedback from the value difference and a sparse success reward. Experiments demonstrate the effectiveness and correctness of FGeo-ISRL. It not only achieves a Single-Step Theorem Accuracy of 90.2% and a Geometric Problem-Solving Accuracy of 83.14%, but also ensures that every step of the proof process remains readable, verifiable, and traceable. Full article

Alpha-mangostin (AM), a xanthone from Garcinia mangostana, has shown promising nephroprotective properties, but its mechanisms in acute kidney injury (AKI) remain incompletely defined. In this study, we applied an integrative network pharmacology pipeline combined with molecular docking to clarify AM’s multi-target mechanisms in AKI. We identified 128 predicted AM targets and intersected them with AKI-related genes, yielding 122 shared targets. Protein–protein interaction analysis identified ten hub genes—TNF, AKT1, IL6, SRC, CTNNB1, HSP90AA1, NFKB1, HIF1A, PPARG, and PTGS2—implicating inflammatory, hypoxia, and cell-survival pathways. KEGG enrichment highlighted HIF-1 signaling, PI3K–Akt signaling, chemokine signaling, AGE–RAGE signaling, and pathways related to cellular senescence and oxidative stress, while GO terms emphasized responses to chemical/oxygen-containing compounds, kinase activity, signal transduction, and apoptosis. Molecular docking against the ten hub proteins showed favorable binding energies across multiple targets. The strongest predicted affinities were observed for PTGS2 (−11.13 kcal/mol), TNF (−9.74 kcal/mol), and AKT1 (−9.48 kcal/mol). Docking positioned AM within the COX-2 catalytic pocket, engaging key catalytic and hydrophobic residues similar to known inhibitors. MD simulation interaction analysis confirmed that AM maintained stable contacts with key human PTGS2 residues, characterized by dominant hydrogen bonds and water-bridge interactions with SER353, TYR355, ARG513, and SER530, along with consistent hydrophobic contacts, and persistent interactions sustained throughout the 200 ns trajectory. Collectively, these results suggest that AM modulates interconnected inflammatory, hypoxic, and survival pathways relevant to AKI, acting as a multi-target ligand with notable interaction involving COX-2, TNF, and AKT1. Further experimental validation and formulation strategies to improve bioavailability are recommended for the advancement of AM toward therapeutic evaluation in AKI. Full article

Peptide binders, serving as a critical drug modality bridging small-molecule compounds and protein macromolecules, can effectively mimic the secondary structural elements of natural proteins. Peptides exhibit unique physicochemical advantages when targeting protein protein interaction (PPI) interfaces, which are typically characterized by flat surfaces and extensive contact areas. Recently, diffusion models represented by RFdiffusion have established a new computational paradigm for protein backbone generation by defining a denoising process over the rigid-body transformation group. However, in the de novo design of binders targeting “undruggable” PPI targets, this general paradigm encounters significant adaptability bottlenecks. First, its underlying rigid-body assumption struggles to accurately describe the dynamic induced-fit process of peptides at the binding interface. Second, it lacks sufficient robustness to the experimental resolution heterogeneity inherent in training data. Furthermore, the decoupled two-stage generation of sequence and structure severs the synergy of physicochemical properties, leading to backbones with idealized, singular secondary structures that lack authentic spatial binding capacity and reasonable side-chain physicochemical features. To address these challenges, this study proposes PPI-Diff, a novel generative framework. While preserving the generative capability of diffusion models, PPI-Diff introduces three core mechanisms: (1) a resolution-aware constraint mechanism that maps the measurement precision of experimental data into explicit contextual constraints to dynamically suppress geometric noise from low-resolution samples; (2) an internal-coordinate-driven manifold diffusion model that performs conformational evolution on a Riemannian manifold constructed by dihedral angles, balancing local stereochemical validity with the precise capture of flexible peptide conformations; and (3) a geometry-semantic synergistic modeling mechanism that leverages the evolutionary embeddings of a pre-trained protein language model (ESM-2) as latent variables to align structure generation with biophysical functions. Systematic benchmarking demonstrates that, on a strictly non-homologous test set, the binders generated by PPI-Diff significantly outperform existing baseline models in terms of interface contact density, stereochemical validity, and sequence novelty. Full article

Background/Objectives: Natural killer (NK) cells are key innate lymphoid cells that restrict tumour progression by secreting proinflammatory cytokines and directly lysing malignant cells, with their activity tightly regulated by a balance of activating and inhibitory surface receptors. The natural cytotoxicity receptor NKp44 is induced on NK cells following stimulation with IL-2 or IL-15 and recognizes platelet-derived growth factor D (PDGF-DD) as a ligand. Mechanistic interpretation of NKp44 signalling upon PDGF-DD engagement is confounded by the existence of three distinct NKp44 isoforms (NKp44-1, -2, and -3), each capable of initiating divergent intracellular signalling cascades. Unlike NKp44-2 and -3, NKp44-1 encodes a cytoplasmic tyrosine residue (Y238) that conforms to a putative immunoreceptor tyrosine-based inhibition motif (ITIM) and has been reported to suppress NK cell effector functions in some contexts. However, it remains unclear whether the NKp44 isoforms are translated and expressed in NK cells, and formal evidence defining NKp44-1 signalling in response to engagement by PDGF-DD is lacking. Methods: In this study, we used C-terminal targeting monoclonal antibodies (mAbs) and a NFAT-GFP reporter system to define the expression and signalling properties of NKp44 isoforms in response to PDGF-DD. Results: We demonstrate protein expression of NKp44-1 and NKp44-2-/3 receptors in IL-2 expanded NK cells. We further show that NKp44-1 transduces activating rather than inhibitory signals when engaged by PDGF-DD ligand, albeit weaker than NKp44-3. Intriguingly, we find that Y238 is dispensable for NKp44-1 activating signalling and instead functions as a YXXΦ internalisation motif. Conclusions: Collectively, these findings provide the first evidence that the NKp44-1 and NKp44-2/3 isoforms are expressed in NK cells and establish that PDGF-DD activates signalling through NKp44-1 independently of Y238. This work lays the foundations for future studies investigating how PDGF-DD sensing by the different NKp44 isoforms shapes immune functions in different physiological and pathological contexts. Full article

Objectives: Multidrug-resistant (MDR) Pseudomonas aeruginosa represents a major clinical challenge, driven in part by resistance–nodulation–division (RND) efflux pumps that reduce intracellular antibiotic concentrations and limit the efficacy of many antibacterial agents, including fluoroquinolones. The aim of this study was to identify and characterize TXA11114 as a small-molecule efflux pump inhibitor (EPI) capable of restoring the activity of the fluoroquinolone levofloxacin against MDR P. aeruginosa. Methods: The antibacterial activity of the TXA11114–levofloxacin combination was evaluated using minimum inhibitory concentration (MIC) assays against panels of clinical isolates. Mechanistic studies included levofloxacin accumulation assays, ethidium bromide accumulation assays, outer-membrane permeability measurements, and whole-genome sequencing of mutants with altered potentiation phenotypes. In vivo efficacy was evaluated in murine thigh and lung infection models, while preliminary safety and drug-like properties were assessed using cytotoxicity assays and in vitro ADME profiling. Results: The TXA11114–levofloxacin combination produced > 1 log₁₀ CFU reductions in bacterial burden in murine thigh and lung infection models, exceeding the activity of levofloxacin monotherapy. TXA11114 markedly potentiated levofloxacin activity, producing substantial reductions in levofloxacin MIC values across multiple MDR clinical isolates, and also enhanced the activity of several additional efflux pump substrates, including β-lactams, tetracyclines, chloramphenicol, and trimethoprim–sulfamethoxazole. Mechanistic experiments demonstrated increased intracellular accumulation of efflux substrates without evidence of nonspecific membrane disruption, and mutations in ompH were associated with altered potentiation phenotypes. Conclusions: The TXA11114–levofloxacin combination produced significantly greater bacterial reductions than levofloxacin monotherapy in murine infection models. Levofloxacin was selected because fluoroquinolone resistance in P. aeruginosa is frequently driven by efflux-mediated mechanisms. While this study focused on levofloxacin potentiation, future work will evaluate additional efflux pump substrates and further define the molecular target of TXA11114. Full article

Welded joints in API 5L X70 pipeline steel represent critical locations for pipelines intended for hydrogen service because welding can create microstructural inhomogeneity, stress concentrations, and uneven mechanical properties that can promote hydrogen-assisted degradation. In hydrogen-containing environments, these effects may manifest as reduced ductility, loss of fracture resistance, and increased cracking susceptibility, particularly in the weld metal and heat-affected zone. Therefore, welding procedures for X70 intended for hydrogen applications must be evaluated using systematic mechanical testing and microstructural characterization under defined hydrogen exposure conditions. The study investigates the detrimental effects of hydrogen on the mechanical integrity of pipeline materials, focusing on welded joints of the API 5L X70 steel, a candidate material for use in hydrogen-containing environments. The weldability and structural performance of the X70 pipeline steel joints in hydrogen environments, produced using automated multi-pass metal active gas (MAG) welding, was experimentally studied. Welding was performed on a DN800 pipe with precise control over welding parameters. Comprehensive analyses were conducted on the welded joints, including microstructure examinations, hardness measurements, slow strain rate testing in high-pressure gaseous H₂ with a N₂ baseline and fracture toughness testing. In high-pressure hydrogen SSRT showed a moderate reduction in ductility relative to nitrogen, with reduction of area decreasing from 81.2% (N₂) to 69.1 and 71.5% (H₂), while time-to-failure remained comparable (475 min in N₂ vs. 497 and 496 min in H₂) Ultimate tensile strength was not reduced (579 MPa in N₂ vs. 609 and 597 MPa in H₂). Secondary surface cracks were observed only on specimens tested in hydrogen. Fracture mechanics testing after hydrogen exposure yielded K_IH values of 58–59 MPa√m in the weld metal and 57–61 MPa√m in the HAZ, exceeding the 55 MPa√m acceptance threshold applied in this study. The results highlight the necessity of optimized welding techniques and targeted material analyses to ensure the safety and durability of pipelines in hydrogen-rich environments, thereby contributing to the development of reliable infrastructure for sustainable energy systems. Full article