Search Results (185)

Molybdenum (Mo) is a strategic raw material for high-end equipment manufacturing, aerospace technologies, and advanced alloys, and approximately 50% of global molybdenum resources are hosted in porphyry Cu–Mo deposits. To address the long-standing challenge of selectively separating chalcopyrite and molybdenite by flotation, this study screened five sulfur-containing organic depressants and investigated their effects on the flotation responses of the two minerals, motivated by the strong affinity of sulfur donor atoms for surface Cu sites on chalcopyrite. The results indicate that thiomalic acid, 4-hydroxythiobenzamide, and 6-methyl-2-thiouracil markedly depress chalcopyrite flotation, whereas 2-(methylthio)acetic acid and N-phenylthiourea exert only minor effects. In contrast, none of the five reagents significantly affects the floatability of molybdenite. Among these depressants, thiomalic acid exhibited the best selectivity. In practical Cu–Mo bulk concentrate flotation, it showed a clear dosage advantage at low addition levels and improved Cu–Mo separation performance; at a Mo recovery of 76.09% and a Mo grade of 5.45%, Cu recovery was reduced to 9.54%. The adsorption mechanism of thiomalic acid on chalcopyrite was further investigated using FT-IR spectroscopy, X-ray photoelectron spectroscopy, and self-consistent charge density-functional tight-binding (SCC-DFTB) calculations. The results suggest that thiomalic acid interacts strongly with surface Cu sites on chalcopyrite via its S- and O-containing functional groups, likely increasing surface hydrophilicity and inhibiting collector adsorption (and subsequent bubble attachment), thereby contributing to selective chalcopyrite depression. Full article

Glycosylation is a critical determinant of extracellular vesicle (EV) biology, shaping vesicle biogenesis, stability, biodistribution, cellular recognition, and uptake. Because EV glycans mirror disease-associated remodeling of parental cells, EV glycosylation is emerging as both a rich source of biomarkers and a functional regulator of regenerative signaling. This review highlights how altered EV glycosylation generates disease-specific signatures across major cancers, including lung, hepatocellular, colorectal, bladder, ovarian, pancreatic, and prostate cancer, and also discusses evidence in neurological, neuropsychiatric, metabolic, autoimmune, urinary, and musculoskeletal disorders. Beyond diagnostics, we examine the growing role of EV glycosylation in regenerative medicine, where glycan-dependent targeting and tissue interactions contribute to neural, cardiac, renal, skeletal, joint, and skin repair. We further provide an integrated overview of analytical strategies for EV glycosylation research, spanning mass spectrometry-based glycomics and glycoproteomics, affinity-based profiling, lectin microarrays, imaging, spectroscopic methods, advanced biosensing and nanotechnology-based approaches, and emerging artificial intelligence and bioinformatics tools. Current methodological challenges, biosafety issues, translational barriers, and future technologies are also critically discussed. Altogether, this review positions EV glycosylation as a promising interface between EV biology, precision diagnostics, and next-generation regenerative therapeutics. Full article

Quartz crystal microbalance (QCM) technology provides a powerful, label-free platform for monitoring molecular interactions in real time with nanogram sensitivity. Recent advances in compact instrumentation have enhanced analytical performance while reducing energy consumption, aligning with the principles of Green Analytical Chemistry. In parallel, the European Union has recommended the replacement of animal-derived antibodies with non-animal alternatives, creating an urgent need for sustainable affinity receptors. In this study, we present an innovative application of polynorepinephrine (PNE)-based molecularly imprinted polymers (MIPs) with a compact QCM sensing. PNE, a bioinspired polymer formed under mild aqueous conditions, offers strong adhesive properties and biocompatibility, enabling robust immobilization of imprinted receptors on gold-coated quartz disks. The resulting PNE-MIP/QCM platform combines the ultrasensitivity of quartz microbalances with the selectivity of molecular imprinting, delivering a reproducible and environmentally responsible affinity sensor. The sensor showed a limit of detection of 11.2 nM and enabled accurate IgG quantification in diluted human serum samples. As a proof of concept, the system was applied to Human Immunoglobulin G (IgG1) detection, demonstrating its potential for sustainable clinical diagnostics. Full article

Lymphocyte activation gene-3 (LAG-3) is a pivotal immune checkpoint receptor that exerts a negative regulatory effect on T-cell function. Although LAG-3-blocking antibodies have shown promising clinical potential, the inherent limitations of conventional monoclonal antibodies necessitate the development of novel antibody formats with enhanced biological and pharmacological properties. In this study, a panel of single-domain antibodies (sdAbs) targeting human LAG-3 was generated via phage display technology. Among these candidates, 2H-G7 was identified as a high-affinity sdAb that binds to LAG-3 with an equilibrium dissociation constant (K_D) in the nanomolar range. Notably, 2H-G7 potently blocks the interactions of LAG-3 with both of its key ligands, fibrinogen-like protein 1 (FGL1) and major histocompatibility complex class II (MHC-II). Its capacity to restore impaired T-cell function was validated by quantifying interleukin-2 (IL-2) secretion and CD69 expression in stimulated primary human peripheral blood mononuclear cells (PBMCs). Epitope mapping studies localized the binding site of 2H-G7 to the D1D2 extracellular domains of LAG-3, distinct from relatlimab, a clinically approved LAG-3-blocking antibody serving as the benchmark. In a xenogeneic mouse model of non-small-cell lung cancer (NSCLC), 2H-G7-Fc exhibited superior tumor growth inhibition efficacy compared with relatlimab. These findings demonstrate that 2H-G7 is a promising lead candidate for the development of next-generation LAG-3-targeted tumor immunotherapies. Full article

Water is one of the most valuable resources on the planet; without it, life as we know it could not exist. Consequently, its increasing scarcity and pollution, which are mainly due to industrialization and changing consumption patterns, intensify the stress on water resources. At the same time, industrial activities contribute to water contamination with pollutants such as heavy metals, further reducing water availability. Due to their risks to human health and ecosystems, effective removal strategies are essential. Among the emerging approaches, polymer-based additive manufacturing (AM), commonly known as 3D printing (3DP), has gained attention for water treatment due to its versatility, precise control over structure and porosity, and ease of processing, while remaining at a low cost. Additionally, the polymers used have interesting adsorbent properties and allow for the incorporation of functional additives, further enhancing their performance. This review analyses the recent advances in 3D-printed polymeric materials for the removal of heavy metals and dyes, focusing on material composition, manufacturing technologies, geometry, removal mechanisms, performance, and regeneration. It was concluded that metal ions and cationic dyes are primarily removed through adsorption, due to interactions with negatively charged surfaces that are often enhanced by high-affinity additives. Anionic dyes are generally less effectively removed by adsorption and often rely on degradation mechanisms. However, adsorption of anionic dyes can occur, for instance when the adsorbent surface is modified to introduce positively charged functional groups. The ability of 3DP to create hierarchical porous structures combining micro-, meso-, and macropores improves fluid flow and contact area, thereby enhancing the removal efficiency. Full article

Surface plasmon resonance (SPR) is a label-free, real-time biosensing technology with high sensitivity for the detection of biomolecular interactions. This review highlights recent advances in SPR biosensors for the detection of SARS-CoV-2. First, we outline design strategies, especially advanced plasmonic nanostructures and precise surface functionalization, that improve the specificity and binding affinity to viral targets. Next, we cover signal amplification methods, such as nanoparticle conjugation and plasmonic photothermal effects, which enhance the sensitivity for low-abundance viral components. Subsequently, we conducted a comparative analysis of SPR biosensors alongside traditional and emerging detection approaches for SARS-CoV-2, elucidating their individual merits and drawbacks. We also discuss how machine learning improves data interpretation and diagnostic accuracy. Finally, we discuss the current challenges and future development directions, particularly for clinical diagnostics, epidemic monitoring, and public health security. These advances support faster, more reliable, and accessible diagnostics for current and future viral outbreaks. Full article

This study evaluated the sustainability of removing phenolic compounds from olive mill effluents using a nanobiochar synthesized from olive pomace. Catechol, tyrosol, hydroxytyrosol, and homovanillic alcohol were chosen as model pollutants due to their presence in agro-industrial wastewater. The surface morphology, elemental composition, crystallographic structure, functional groups, porosity, and thermal stability of the nanobiochar were investigated by SEM, EDX, XRD, FTIR, BET analysis, and TGA/DTA. The developed nanobiochar exhibited a predominantly amorphous carbon structure, enriched in carbon (85.6%), with localized graphitic domains. Its mesoporous architecture (S_BET = 15.478 m² g⁻¹; Dp = 2.14 nm) promotes accessibility to active sites, while its thermal stability confirmed its suitability for adsorption applications. In this batch adsorption study, the technological aspect considered is the influence of operating parameters on adsorption efficiency, using kinetic and equilibrium models. Pseudo-first-order and pseudo-second-order kinetic models, as well as Freundlich and Langmuir isotherms, were used to analyze the experimental data. The pseudo-second-order model proved to be the most suitable for describing adsorption, suggesting that the process is primarily dominated by chemisorption. Similarly, the Langmuir model gave the least satisfactory results regarding equilibrium data, indicating monolayer adsorption on homogeneous active sites. The adsorption capacity of phenolic compounds was variable. The highest adsorption capacities were observed for catechol (250 mg g⁻¹), tyrosol (19.23 mg g⁻¹), homovanillic alcohol (15.38 mg g⁻¹), and hydroxytyrosol (13.16 mg g⁻¹). The results of this research indicate that adsorption affinity depends on molecular structure and electronic properties. Furthermore, computer modeling based on molecular simulations and electronic descriptors was performed to explain the adsorption mechanism. Linear regression, principal component analysis, and elastic regression revealed strong correlations between adsorption parameters and molecular descriptors. These results demonstrate that olive pomace-based nanobiochar is an environmentally friendly adsorbent for the treatment of phenolic effluents, with adsorption primarily controlled by surface interactions. Full article

Background: Myocardial fibrosis (MF) results from excessive collagen deposition in the cardiac interstitium, causing structural and functional cardiac impairments that underlie multiple cardiovascular diseases. Grape seed oil (GSO), rich in various bioactive fatty acids, demonstrates established cardiovascular benefits, yet its potential mechanisms against MF remain incompletely elucidated. This study was designed to investigate the inhibitory effects of bioactive components from GSO on TGF-β1-induced fibrosis in cardiac fibroblasts (CFs) and to elucidate the underlying molecular mechanisms. Methods: GSO was obtained using supercritical CO₂ extraction technology. Initially, the anti-fibrotic activity of GSO was evaluated in vitro: a fibrosis model was established by inducing cardiac fibroblasts with TGF-β1 (10 ng/mL for 48 h), followed by treatment with 20% (v/v) GSO. Subsequently, the bioactive constituents of GSO were identified by Gas Chromatography-Mass Spectrometry (GC-MS). Network pharmacology approaches were employed to predict its potential therapeutic targets and associated signaling pathways. Molecular docking simulations were then performed to validate the binding interactions between the key bioactive components and the core targets obtained from enrichment analysis. Finally, the predicted core pathway was experimentally verified by Western blot analysis. Results: In vitro experiments demonstrated that 20% GSO treatment significantly downregulated TGF-β1-induced fibrotic markers at both transcriptional (MMP9, MMP2, Col1a1) and protein (TGF, Col I/III, α-SMA) levels (p < 0.01). GC-MS analysis identified nine fatty acids in GSO, including palmitic acid and linolenic acid. Network pharmacology revealed interactions between these compounds and 357 myocardial fibrosis-related targets. Molecular docking confirmed strong binding affinities (below −5.0 kcal/mol) of key components (heptadecanoic acid, palmitic acid) to core targets (MMP-9, PTGS2, MAPK3). Western blot analysis further verified that GSO significantly inhibited the expression of PI3K-AKT pathway-related proteins (p < 0.01). Conclusions: The fatty acids in GSO (linolenic acid, palmitic acid) attenuate myocardial fibrosis by inhibiting the PI3K/AKT signaling pathway and downregulating key fibrotic markers. These findings establish a novel theoretical foundation for the treatment of myocardial fibrosis and highlight the potential value of grape industry byproducts in cardiovascular therapeutics. Full article

Sports have progressively incorporated technological advances, yet while the impact on performance and broadcasting is remarkable, the application of Artificial Intelligence (AI) in sports refereeing appears residual. A closer examination of prior research suggests that this limited development reflects deeper conceptual patterns within the field. While existing research on AI in sports officiating has predominantly conceptualized the field under an accuracy-optimization paradigm (focusing on decision precision, visual attention patterns, referee fatigue, and performance enhancement), there is a systematic lack of theoretical and empirical work that frames officiating as a broader socio-technical ecosystem. In particular, the literature does not provide conceptual models addressing (i) AI-assisted risk prevention and athlete safety as a core officiating function, (ii) human–AI task redistribution in cognitively overloaded and hybrid evaluative environments (e.g., disciplines such as artistic gymnastics or bodybuilding, where technical execution and aesthetic judgment are simultaneously assessed), and (iii) the redefinition of the referee’s role when AI operates as an anticipatory or real-time alert system rather than merely as a post hoc verification tool. Thus, the gap is not only one of application but of knowledge production: the dominant paradigm optimizes decision accuracy, yet it leaves the question of how AI can transform refereeing responsibilities, cognitive load distribution, and safety governance within competitive ecosystems under-theorized. This exploratory study adopts a Human–Computer Interaction (HCI) perspective to contrast existing initiatives with the practical expectations of professional referees. The methodology comprises two pillars: a systematic literature review following PRISMA guidelines and qualitative experimentation involving professional referees using focus groups and affinity diagrams techniques. From an initial total of 1251 records retrieved across five academic databases (2019–2025), 1122 articles were analyzed after applying strict inclusion/exclusion criteria. The findings provide preliminary support for our hypothesis of a significant underutilization gap, showing that research is concentrated on accuracy systems, while high-potential areas identified as critical by experts, such as athlete safety, represent only 0.6% of the analyzed literature. The study contributes a conceptual framework based on five categories established by experts, according to the identified use cases, providing guidance for future AI integration and interdisciplinary research in the sports officiating ecosystem. Based on the results, we point to future applications and lines of research aimed at integrating AI as a tool for sports refereeing. Full article

This study demonstrates that compressive strength in cement-stabilized rammed earth is governed by conditional, threshold-controlled interactions rather than by intrinsic mineralogical effects. A B + K (beidellite + kaolinite) content exceeding 15% defines a low-strength regime (median ≈ 44.6 kN), whereas B + K ≤ 5% allows medians above 90 kN under 7% forming moisture. Quartz-rich fractions show a global correlation of r = 0.71. The Kruskal–Wallis test confirms strong clay grouping influence (H = 72.78, p < 0.001). Analysis of the experimental dataset shows that most strength distributions deviate from normality, invalidating pooled parametric inference and justifying the use of distribution-free methods. At the global level, bulk density and quartz-rich fractions are the dominant positive contributors to strength. Meanwhile, forming moisture and high combined beidellite–kaolinite content (>15%) exerts a negative influence under elevated forming moisture (8%), whereas the effect of 1:1 and 2:1 clay minerals differs depending on their hydro-affinity and moisture regime. However, subgroup analyses reveal frequent reversals in both magnitude and sign of correlations, proving that mineral effects depend critically on cement dosage and moisture regime, revealing discrete strength regimes defined by hierarchical interactions between moisture, cement content, and mineralogical thresholds. The combined beidellite–kaolinite content was classified into ≤5%, 5–15%, and >15% groups. Specimens with B + K > 15% consistently formed a low-strength regime, with a median destructive load of approximately 44.6 kN (≈1.1–1.3 MPa depending on cross-sectional area). In contrast, mixtures with B + K ≤ 5% achieved median loads above 90 kN (≈2.5–3.0 MPa). Quartz-rich fractions showed a strong global positive correlation with strength (r = 0.71), while the grouped clay fraction exhibited a highly significant effect (Kruskal–Wallis H = 72.78, p < 0.001). A regime shift was observed between 7% and 8% forming moisture, where quartz correlation changed from strongly positive (r ≈ 0.70) to negative (r ≈ −0.69). Increasing cement content from 6% to 9% significantly improved strength (H = 12.30, p = 0.0005), although this effect diminished when B + K exceeded 15% or forming moisture reached 8%. Association rules further confirm that high or low strength emerges only from specific multivariate combinations. The results show that mineralogy influences CSRE strength primarily through interaction with technological parameters, providing a robust basis for regime-based interpretation and rational mixture design. Full article

Lightweight, efficient, and reversible hydrogen storage materials are critical for the advancement of hydrogen-based energy technologies. In this work, we present a comprehensive density functional theory (DFT) investigation of hydrogen storage in pristine and metal-decorated C₈ carbon quantum dots (CQDs), representing ultrasmall, highly curved nanomaterials at the molecular–nanoscale interface. Lithium, magnesium, and titanium were investigated as representative decorating metals to tailor hydrogen adsorption strength and reversibility. The pristine C₈ quantum dot is structurally stable but exhibits negligible hydrogen affinity (−0.062 eV per H₂), rendering it unsuitable for practical storage applications. In contrast, metal decoration significantly enhances hydrogen adsorption while preserving molecular H₂ physisorption, yielding optimal single-molecule adsorption energies of −0.172, −0.304, and −0.451 eV for Li-, Mg-, and Ti-CQDs, respectively. Sequential adsorption analysis indicates exceptionally high hydrogen uptakes of up to 18 H₂ molecules for Li-CQD and 20 H₂ molecules for both Mg- and Ti-CQDs, corresponding to very high theoretical gravimetric capacities. Energy decomposition and interaction region analyses demonstrate that hydrogen uptake proceeds via a cooperative physisorption mechanism driven by dispersion, electrostatic, and polarization interactions, strongly enhanced by quantum confinement and extreme curvature effects inherent to the CQD. Grand canonical thermodynamic modeling confirms fully reversible hydrogen storage under practical temperature and pressure conditions. Among the systems studied, Mg-CQD exhibits the most favorable balance between adsorption strength and desorption accessibility, delivering a remarkable reversible gravimetric hydrogen storage capacity of 21.7 wt%, significantly surpassing most metal-decorated graphene-, fullerene-, and carbon nanotube-based materials reported to date. These results establish metal-decorated C₈ quantum dots as a new class of high-performance nanomaterials for reversible hydrogen storage and demonstrate the potential of ultrasmall carbon quantum dots to overcome the long-standing trade-off between hydrogen uptake and reversibility in nanostructured storage media. Full article

Canine distemper virus (CDV) remains a highly contagious and lethal pathogen, posing a severe global threat to domestic dogs and wild carnivores. To address the urgent need for effective interventions, we utilized a proprietary Vero-SLAM cell platform to isolate a wild-type CDV strain and generate neutralizing polyclonal antibodies. Subsequently, phage display technology was employed to screen for single-chain variable fragments (scFvs) targeting the CDV hemagglutinin protein (CDV-H). This approach led to the identification of a specific scFv with virus-binding affinity comparable to commercial antibodies, which effectively blocks CDV infection in Vero-SLAM cells. Molecular docking and molecular dynamics simulations were conducted to elucidate the interaction mechanism, suggesting that this scFv binds to a novel and unique epitope on the CDV-H. These findings not only expand our understanding of the antigenic properties of the CDV H protein but also provide a theoretical foundation and a promising candidate molecule for the development of future CDV diagnostics and antiviral strategies. Full article

Background/Objectives: Nature has evolved millions of venom-derived peptides with diverse biological functions, a substantial fraction of which target complex membrane proteins such as G-protein-coupled receptors and ion channels. Many of these peptides are stabilized by multiple disulfide bonds, endowing them with exceptional structural stability and favorable pharmacological properties. Methods: Leveraging this natural diversity, we developed a robust venom peptide therapeutics discovery system built on phage display technology and constructed a library using approximately 482 venom-derived scaffolds. The library design was guided by a machine learning (ML) model capable of predicting mutation-tolerant residues that preserve peptide foldability, maximizing structural integrity and sequence diversity. Results: The resulting VCX library was evaluated through screening against four diverse targets (CD47, DLL3, IL33, and P2X7R), yielding strong binders for all four, a success rate of 100%. Furthermore, by integrating high-throughput recombinant expression of thioredoxin–venom fusion proteins along with ML-assisted affinity maturation, we rapidly identified potential leads for DLL3 binders. Conclusions: This venom-based discovery platform offers significant advantages in both functionality and developability compared with conventional peptide discovery approaches. By combining natural structural diversity, ML-guided design, and recombinant expression, it enables efficient identification of “antibody-like” binders with molecular weights much smaller than those of antibodies. Consequently, it provides a powerful strategy for developing next-generation peptide therapeutics targeting challenging protein–protein interactions and complex membrane proteins. Full article

Background: Non-small cell lung carcinoma (NSCLC) is the most prevalent form of lung cancer, and its progression is closely associated with constitutive activation of signal transducer and activator of transcription 3 (STAT3). This study used surface plasmon resonance (SPR) technology to develop a STAT3-targeting recognition system and identify natural STAT3-targeting compounds from the traditional Chinese medicine Psoralea corylifolia and to evaluate their anti-NSCLC activities, with particular attention to reactive oxygen species (ROS) regulation. Methods: The SPR biosensor immobilized with STAT3 was used to screen and enrich STAT3-binding constituents of Psoralea corylifolia, and to determine ligand-STAT3 affinities. Molecular docking was performed to characterize interactions within the STAT3 SH2 domain. Functional effects were assessed in A549 cells using proliferation and scratch migration assays. Antioxidant capacity was evaluated via hydroxyl radical and superoxide anion scavenging assays, and intracellular ROS levels were measured in hydrogen peroxide (H₂O₂)-induced oxidative stress models in human umbilical vein endothelial cells (HUVECs) and A549 cells. Results: SPR analysis showed that psoralen and isopsoralen bind to STAT3, with equilibrium dissociation constants (KD) of 80.92 µM and 28.11 µM, respectively. Molecular docking further confirmed their interaction with the STAT3 SH2 domain. Both compounds inhibited A549 proliferation and reduced migration. Beyond direct STAT3 inhibition, both compounds demonstrated notable free radical scavenging activity. In a H₂O₂-induced oxidative stress model, pretreatment with psoralen or isopsoralen significantly reduced ROS levels in HUVECs, while increasing ROS accumulation in A549 lung cancer cells. Conclusions: This work identifies psoralen and isopsoralen as novel dual-function STAT3 inhibitors that exert anti-NSCLC effects through combined STAT3 suppression and context-dependent ROS modulation, and demonstrates the utility of SPR for screening bioactive natural products. Full article

Polyphenols are a structurally diverse group of plant secondary metabolites widely recognized for their antioxidant, anti-inflammatory, antimicrobial, and chemoprotective properties, which have stimulated their extensive use in food, pharmaceutical, nutraceutical, and cosmetic products. However, their chemical heterogeneity, wide polarity range, and strong interactions with plant matrices pose major challenges for efficient extraction, separation, and reliable analytical characterization. This review provides a critical overview of contemporary strategies for the extraction, separation, and identification of polyphenols from plant-derived matrices. Conventional extraction methods, including maceration, Soxhlet extraction, and percolation, are discussed alongside modern green technologies such as ultrasound-assisted extraction, microwave-assisted extraction, pressurized liquid extraction, and supercritical fluid extraction. Particular emphasis is placed on environmentally friendly solvents, including ethanol, natural deep eutectic solvents, and ionic liquids, as sustainable alternatives that improve extraction efficiency while reducing environmental impact. The review further highlights chromatographic separation approaches—partition, adsorption, ion-exchange, size-exclusion, and affinity chromatography—and underlines the importance of hyphenated analytical platforms (LC–MS, LC–MS/MS, and LC–NMR) for comprehensive polyphenol profiling. Key analytical challenges, including matrix effects, compound instability, and limited availability of reference standards, are addressed, together with perspectives on industrial implementation, quality control, and standardization. Full article