The rising incidence of antimicrobial resistance necessitates the development of sustainable and eco-friendly nanomaterials. In this study, silver-iron oxide nanoparticles (Ag-FeO NPs) were phyto-synthesized using Traganum nudatum seed extract as a natural reducing and stabilizing agent, and their physicochemical properties and antimicrobial activity were systematically evaluated. UV-Vis spectroscopy showed a characteristic absorption peak at 359 nm, providing supportive evidence of nanoparticle formation. Fourier-transform infrared spectroscopy revealed functional groups at 1,645 and 3,315 cm-1, indicating the involvement of plant-derived phytochemicals in nanoparticle stabilization. Transmission electron microscopy analysis showed heterogeneous spherical and rod-like nanostructures with moderate aggregation, while scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy qualitatively indicated the presence of silver and iron, together with oxygen and carbon. Dynamic light scattering analysis showed an average hydrodynamic particle size of 7.3 nm and a broad particle size distribution (PDI = 0.60), with a zeta potential of −1.36 mV. GC-MS profiling identified bioactive metabolites, including 3-(octanoyloxy)propane-1,2-diyl bis(decanoate), n-hexadecanoic acid, hentriacontane, and lidocaine, potentially contributing to nanoparticle synthesis and bioactivity. Ag-FeO NPs exhibited significant antimicrobial activity against Escherichia coli, methicillin-resistant Staphylococcus aureus, and Candida albicans. SEM analysis of C. albicans revealed severe ultrastructural damage, including surface deformation and cell wall disruption. Ag-FeO NPs produced greater reductions in MCF-7 cell viability than in MCF-10A non-tumorigenic epithelial cells, although a clear concentration-dependent response was not observed within the tested range. Computational prediction analyses using PASS, SwissTargetPrediction, SwissADME, and ProTox-II indicated that several identified phytochemicals possess antimicrobial and antineoplastic potential together with favorable pharmacokinetic characteristics. Overall, the integration of green synthesis, experimental validation, and computational modeling highlights the potential of T. nudatum-mediated Ag-FeO NPs as effective and sustainable agents for biomedical applications.
Recent advances in the precise control of electromagnetic and transport properties, and the miniaturization of electronic devices, have introduced new prospects in the development of practical quantum computing. Double perovskites have gained particular attention in spintronic applications due to their structural stability, non-toxicity, and inherent spin polarization. In this study, we explore the effect of Ru 4d-electrons on the magnetic properties of Ba2XRuO6 (X = Y, Lu, Sc) using first-principles calculations within the WIEN2k framework. The calculated lattice constants for Ba2XRuO6 (X = Y, Lu, Sc) using PBEsol-GGA are comparable to reported experimental values. The calculated formation energies (ΔHf) of −2.88, −2.61, and −2.43 eV (for X = Y, Lu, and Sc, respectively) confirm thermodynamic stability. Band structure and density of states analyses reveal that all compounds are ferromagnetic semiconductors. All compounds exhibit ferromagnetic semiconducting behavior, and the bandgap increases with pressure up to 4 GPa. The observed magnetism arises from hybridization effects, crystal-field interactions, and exchange coupling. Optical analysis shows strong visible-light absorption, and transport parameters evaluated from 300 to 800 K highlight notable thermoelectric potential. These findings establish Ba2XRuO6 (X = Y, Lu, Sc) as promising candidates for spintronic and thermoelectric applications.
To ensure stable quality of colored cigarette paper dyed with natural dyes, real-time kinetic data of dye adsorption onto cellulosic fibers remains insufficient due to limitations of traditional offline sampling methods. In this work, brown natural dye was used as the adsorbate, and an online UV-Vis spectral monitoring system was developed to achieve continuous, non-destructive detection of the full adsorption process without intermittent sampling. The effects of initial dye concentration and fiber type on the adsorption behavior and mechanism were systematically investigated. All experiments were conducted at 20 °C with a pulp consistency of 0.2% (w/v), and the initial dye concentration ranged from 10 to 80 mg/L. Pseudo-first-order (PFO) was applied for data fitting. The adsorption process exhibits two successive stages: a water absorption-swelling induction period and a dye adsorption stage. A competitive adsorption mechanism between water molecules and dye macromolecules on fiber surfaces is proposed to explain the induction period. The induction time decreases exponentially with increasing initial dye concentration, following (y = 6,998*e−0·047ˣ) with (R2 = 0.987). Within 30–80 mg/L, the equilibrium adsorption capacity (qe) increases linearly with dye concentration. For hemp pulp fiber at 80 mg/L, (qe) reaches 1.1184 mg/g, the PFO rate constant (k1) is 0.0012 s-1 with (R2 = 0.9980). The PFO model shows better fitting performance for all systems, indicating a diffusion-controlled physisorption process. Hardwood pulp reaches equilibrium at ~1,500 s with the fastest initial rate, while softwood and hemp pulp require over 10000 s. This work provides fundamental kinetic data and theoretical support for formula design and process optimization of online dyeing for colored cigarette paper.
Fibroblast activation protein (FAP) is a highly specific biomarker overexpressed in cancer-associated fibroblasts, making it a promising diagnostic target. Developing novel high-affinity molecular probes for FAP-targeted diagnostics remains an active area of research. In this study, an integrated computational pipeline combining generative artificial intelligence, molecular docking, molecular dynamics (MD) simulation, binding energy estimation, and pharmacokinetic predictions was used to design and evaluate novel linagliptin-based compounds as potential FAP-binding analogs. From a preliminary library of 1,016 analogs generated using DeepLigBuilder, eight unique candidates with nine binding models were obtained based on binding affinity predicted using DeepLigBuilder and binding energy based on molecular docking, and four candidates were identified based on dynamic stability assessments and binding energy estimation. Two novel linagliptin-based candidates, Ligand90 and Ligand150, were identified as putative FAP-binding analogs based on ADMET profiling and Lipinski’s Rule of Five compliance. This integrated computational strategy provides a valuable framework to rationally design computationally prioritized candidates for targeting FAP.
Recognition of amyloid-β (Aβ) by structurally defined inorganic scaffolds offers a route to dissecting how framework geometry and surface chemistry govern peptide–material interactions. We report transferrin (Tf)/KLVFF-PCN-222, a bioinorganic recognition platform built by covalently co-grafting the Aβ-homologous pentapeptide KLVFF and transferrin (Tf) onto the csq-topology porphyrinic zirconium MOF PCN-222 via EDC/NHS chemistry. The one-dimensional hexagonal mesopore channels (∼3.7 nm) and the dense meso-tetrakis (4-carboxyphenyl)porphyrin (TCPP) sites of the csq framework provide geometric access for Aβ1–42 monomer diffusion and an array of peptide–porphyrin recognition contacts. Fluorescence quenching and isothermal titration calorimetry returned an apparent dissociation constant (Kd,app) of 33.5 ± 4.2 nM for the Aβ1–42 monomer (apparent fluorescence-mode limit of detection (LOD) = 1.8 nM), and circular dichroism showed that the probe suppressed Aβ β-sheet conversion (14% vs. 41% β-sheet content at 24 h). A panel of structural controls—scrambled FFKLV, the narrow-pore fcu MOF UiO-66-NH2, and the TCPP-based ftw MOF-525—together with a selectivity screen against BSA, IgG, Tau, α-synuclein, and lysozyme (selectivity ratio >12 for Aβ1–42) indicates that KLVFF sequence specificity and csq mesopore geometry act cooperatively to drive recognition. The framework retains an intrinsic NIR photothermal property (photothermal conversion efficiency, η = 47.3 ± 1.8% at 808 nm); the photoacoustic measurement reported here is a probe concentration calibration only, and no Aβ-responsive photoacoustic signal was established. In an hCMEC/D3 in vitro monolayer, the apparent permeability coefficient (Papp) reached 1.78 × 10−5 cm s−1 with ∼48% of the flux being TfR1-competition-sensitive, and SH-SY5Y viability was partially preserved in a tandem BBB–neuron Transwell model. All validations are in vitro. This work provides a topology-controlled, structure–function proof of concept for csq Zr-TCPP frameworks as bioinorganic platforms for Aβ recognition and conformational modulation.
IntroductionAromatic amines released from azo dyes are regulated in textile products under the European REACH framework due to their potential health risks. Their determination remains analytically challenging because of their structural similarity, moderate polarity, and the complexity of textile matrices, which can cause significant matrix effects.MethodsA green Capillary Electrophoresis method coupled with Diode Array Detection (CE–DAD) was developed for the simultaneous determination of eleven regulated aromatic amines in textile extracts. A Design of Experiments (DoE) approach was employed to systematically optimize the separation conditions, with the aim of maximizing resolution, selectivity, and robustness while minimizing analysis time. The environmental sustainability of the analytical procedure was assessed using the BAGI and Agree metric.ResultsThe optimized CE–DAD method showed satisfactory analytical performance when validated using spiked textile extracts, providing adequate recovery, precision, and robustness. The method also demonstrated good applicability to complex textile matrices. The green assessment confirmed the low environmental impact of the proposed analytical procedure.ConclusionsThe developed CE–DAD method represents a sustainable, reliable, and cost-effective analytical strategy for the simultaneous determination and monitoring of regulated aromatic amines in textile products. The integration of DoE-based optimization and green analytical assessment highlights its potential as an environmentally responsible alternative for analysis of complex textile matrices.
IntroductionMolecular hybridization is an effective approach employed to synthesize molecules that possess the ability to function as dual inhibitors, thereby addressing the issue of growing resistance. Resistance by the malaria parasite is one such example. Therefore, the study aims to develop hybrid compounds consisting of 4-aminoquinoline and 4-thiazolidinone, utilizing molecular docking for sorting, followed by synthesis and evaluation of their anti-malarial potential.MethodsThe molecules were selected on the basis of affinity from the computational study. To strengthen the in silico docking, a 200ns molecular dynamics simulation study was also performed. The title compounds, 7-18, were synthesized in a three-step reaction, involving non-polar solvent addition reaction resulting in heterocyclization. The synthesis was followed by characterization of all the synthesized compounds, and they were further subjected to biological screening through in-vitro, and the selected actives to in-vivo evaluation. An acute toxicity study was also conducted.ResultsThe compounds exhibited promising action, with five compounds, 8, 9, 14, 15, and 18, demonstrating efficacy comparable to the reference drug in the Pf-DHFR enzyme inhibition assay. Four of the active compounds selected for the Plasmodium berghei murine model displayed excellent activity, with percentage parasitaemia inhibition to the extent of 84%, and mean survival time up to 27 days. The MD simulation study showed the stability of the ligand-protein complex up to 200 ns. The in silico ADMET prediction, along with acute toxicity testing of the most active compound, showed no major toxicity.DiscussionThe study concludes the hybrid compounds to be promising antimalarial agents, and the scaffold may be a good lead for the development of next-generation antimalarials.
Lead halide perovskite light-emitting diodes (PeLEDs) have emerged as highly promising candidates for next-generation displays and solid-state lighting, achieving record-high external quantum efficiencies (EQEs) exceeding 30%. The perovskites possess outstanding optoelectronic properties, such as high photoluminescence quantum yields (PLQY), narrow full-width at half maximum (FWHM), and efficient radiative recombination, driven fundamentally by the unique Pb2+ orbital configuration that imparts direct bandgaps and intrinsic defect tolerance. However, commercializing PeLEDs in next-generation displays and lighting is bottlenecked by dual-challenges in material and device: intrinsically, the soft lattice stemming from ionic soft lattice is prone to phase degradation, ion migration, and environment-induced dissociation, triggering severe non-radiative recombination, luminescence failure and environmental toxicity; extrinsically, unbalanced carrier injection, interfacial energy-level mismatch, and Joule heating effect jointly inflict low luminescence efficiency and rapid device decay. This review offers a systematic overview of multi-dimensional strategies developed to resolve this key contradiction. From a synthetic chemistry perspective, we summarize intrinsic lattice stabilization via compositional engineering, surficial ligand passivation and core-shell heterostructures, as well as solvent-free mechano-synthesis pathways. From a device engineering standpoint, we highlight charge-transport layer optimization, self-assembled monolayer (SAM) functionalization for interfacial-defect passivation and balanced carrier injection, alongside photonic waveguiding management. Finally, we discuss future perspectives on atomic-level mechanism characterization, ligand-mediated surface reconstruction, and closed-loop lifecycle management, offering a comprehensive roadmap toward the high-performance, long-term stability and scalable commercialization of next-generation PeLEDs for display and lighting technologies.
Real-time quantitative analysis of complex matrices (e.g., moisture and multiple components) is a critical bottleneck in modern Process Analytical Chemistry (PAC). While online near- and mid-infrared spectroscopy are widely deployed, achieving high-fidelity measurements in dynamic industrial environments remains highly challenging. Severe matrix effects coupled with industrial multi-stress interferences, including continuous detector window pollution and light source drive voltage fluctuations, often cause significant baseline drift and non-linear spectral distortion, challenging both physical optical limits and traditional linear calibration models. To address these challenges, this review systematically evaluates the optical architectures and analytical boundaries of four mainstream online infrared spectrometers: filter-based, grating dispersion, Fourier Transform Infrared (FTIR), and Acousto-Optic Tunable Filters (AOTF). Crucially, we comprehensively review the evolution of chemometric compensation strategies designed to overcome these complex spectral interferences. By comparing traditional multivariate linear models, such as Partial Least Squares (PLS), with cutting-edge deep learning frameworks, notably 1D Convolutional Neural Networks (1D-CNN), we discuss the potential of AI-driven soft-calibration for robust feature extraction and precise quantitative prediction under extreme operational stresses. We emphasize that the advantages of such approaches are contingent upon data availability, the degree of spectral nonlinearity, and the specific process environment; they are not a universal replacement for conventional models, which remain effective under stable and linear conditions. Furthermore, the synergistic evolution of miniaturized solid-state hardware is discussed. Ultimately, this review provides a robust theoretical framework for selecting analytical instruments and developing advanced, data-driven chemometric methodologies in dynamic environments, while acknowledging the practical constraints and trade-offs involved in real-world deployment.
IntroductionBiomonitoring of commercial endocrine-disrupting chemicals (EDCs) increasingly underpins exposure assessment and risk evaluation, yet most large-scale studies still rely on indirect, enzymatic hydrolysis–based methods whose quantitative performance has not been systematically verified. Here, we describe the development and rigorous validation of a direct liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay using validated standards to simultaneously quantify bisphenol S (BPS), propylparaben (PrP), monobutyl phthalate (MBP), and their major urinary glucuronide and sulfate conjugates in human urine.MethodsA direct LC–MS/MS assay was developed for the simultaneous quantification of BPS, PrP, MBP and their major urinary metabolites. The method was validated in accordance with U.S. Food and Drug Administration bioanalytical guidelines, including assessments of linearity, accuracy, precision, selectivity, specificity, matrix effects, recovery, and carryover. The validated assay was then used to evaluate the accuracy of a conventional β‐glucuronidase–based hydrolysis workflow across a wide concentration range in spiked synthetic urine by comparing indirect measurements with direct totals for each analyte. Method utility in human biomonitoring was demonstrated by analysis of urine samples from 30 pregnant women in their second trimester.ResultsUsing isotope-dilution calibration, solid-phase extraction, and negative-ion electrospray multiple reaction monitoring, the method achieved sub‐ng/mL limits of detection for all analytes, linear response over 3-4 orders of magnitude, and intra‐ and inter‐day precision and accuracy within contemporary bioanalytical criteria, confirming fitness for trace-level biomonitoring. Indirect, hydrolysis-based measurements closely tracked direct totals for BPS and PrP, but systematically underestimated MBP, with a concentration-dependent negative bias that increased at higher levels, demonstrating that hydrolysis efficiency is analyte-specific and cannot be inferred from surrogate substrates alone. Application of the direct method to archived urine samples from 30 pregnant individuals enabled the first simultaneous resolution of the free and conjugated forms of these three EDCs in a maternal cohort and revealed that glucuronides accounted for the majority of the total urinary burden, with total concentrations exceeding contemporary NHANES estimates.DiscussionCollectively, these findings show that indirect methods can introduce substantial, analyte-dependent underestimation of internal dose, with implications for exposure misclassification, attenuation of epidemiologic effect estimates, and underestimation of population risk. The data support the position that direct LC–MS/MS quantification of parent and conjugated species, coupled with analyte-resolved assessment of hydrolysis efficiency, should become standard practice in method validation and national biomonitoring programs to ensure accurate exposure assessment for non‐persistent EDCs.
The persistence of resistance, recurrence, and limited selectivity in cancer therapy necessitates the development of structurally advanced antitumor agents capable of modulating multiple intracellular pathways. This review provides a systematic analysis of nitrogen- and oxygen-containing heterocycles as key platforms in anticancer drug design, with an emphasis on integrated molecular architectures combining multiple pharmacophoric fragments. A central and unifying principle emerging from the analyzed studies is the decisive role of hydrazide–hydrazone functionalization as a pharmacophoric enhancer, which should be considered not merely as a substituent but as a core structural element governing conformational flexibility, electronic distribution, and target-binding efficiency. Its incorporation consistently correlates with enhanced antiproliferative activity, apoptosis induction, and improved selectivity across diverse tumor models. Within this framework, the most efficient representatives highlight the practical significance of this design strategy: compound 17 demonstrates exceptional activity with GI50 values of 0.01–0.1 μM among N-heterocyclic systems, while compound 40 emerges as a leading O-heterocyclic analogue, exhibiting IC50 values of 0.45 μg/mL against MCF-7 cells. Collectively, these findings support the strategic prioritization of hydrazide-centered heterocyclic scaffolds as a foundation for the rational development of next-generation anticancer therapeutics.
IntroductionThe sustainable design of jewelry materials has become a critical focus in the pursuit of environmental conservation and responsible manufacturing practices. Traditional approaches to jewelry grade polymer development often prioritize aesthetic and structural qualities while neglecting environmental considerations, leading to significant ecological footprints and limited adaptability to green manufacturing standards. This study introduces SpectralSemanticTopology, a novel methodological framework that integrates advanced green polymer systems with low impact processing strategies to address these challenges.MethodsThe framework is structured around three core modules: the Spectral Consistency Mapper, the Semantic Transition Checker, and the Topology Aware Trajectory Resolver, which collectively enable systematic exploration and optimization of polymer formulations and processing pathways. These modules are complemented by harmonic relation modeling and rule guided inference mechanisms, ensuring that the visual and tactile attributes essential to high end jewelry are preserved without compromising environmental sustainability. The proposed method formalizes the design problem within a rigorous mathematical framework, facilitating precise modeling and optimization of material properties and processing techniques.Results and DiscussionExperimental results demonstrate significant improvements in environmental performance metrics, including reductions in energy consumption and waste generation, while maintaining the aesthetic and structural integrity required for luxury applications. The findings underscore the potential of SpectralSemanticTopology to redefine sustainable practices in jewelry design, offering a pathway to innovative and environmentally responsible material development.
IntroductionShort-acting ketamine-related scaffold design remains an important medicinal-chemistry problem, but computational studies require conservative interpretation until receptor, enzymatic, and pharmacokinetic validation is available.MethodsS-ketamine, S-Remiketamine, and R1-R20 analogues were assessed using ligand curation, NMDA receptor docking, cross-target docking, explicit-solvent molecular dynamics, MM-GBSA analysis, CES1-oriented geometric assessment, and predictive ADMET/metabolite-route analysis.ResultsStatic NMDA docking ranked R2 highest (Glide score -7.308 kcal/mol), while S-Remiketamine showed a more favorable predicted NMDA score than S-ketamine (-6.448 vs. -5.981 kcal/mol). Within the dynamically evaluated subset, NMDA end-state MM-GBSA values were -41.53 kcal/mol for R2, -28.80 kcal/mol for R11, and -42.10 kcal/mol for R14. In CES1 modeling, R14 was the only evaluated compound whose MM-GBSA became more favorable from 0 to 100 ns (-83.91 to -99.44 kcal/mol).DiscussionThese results support R2 as the strongest static NMDA docking/NMDA-preference benchmark and R14 as the most internally consistent integrated computational candidate. The findings are hypothesis-generating and require synthesis and experimental validation.
BackgroundLithium, sulfur batteries are promising next-generation energy, storage systems, but their practical performance is limited by lithium polysulfide (LiPS) shuttling, sluggish sulfur redox kinetics, insulating Li2S formation, and performance decay under high-sulfur-loading and lean-electrolyte conditions.MethodsSingle-atom Ru–NC was synthesized through precursor coordination, pyrolysis, acid washing, and secondary annealing, followed by sulfur loading through melt diffusion to obtain S/Ru–NC. The materials were characterized by microscopy, XRD, Raman spectroscopy, nitrogen sorption, XPS, ICP-OES, XANES, WT-EXAFS, and EXAFS fitting. LiPS adsorption, symmetric-cell redox kinetics, Li2S nucleation/decomposition, standard-loading Li–S cell performance, high-loading lean-electrolyte cell behavior, and DFT adsorption analyses were evaluated. Minimum-energy paths were further examined by climbing-image nudged elastic band calculations, and cycled high-loading cells were characterized by SEM, separator XPS, and cathode TEM.ResultsRu–NC retained a high surface area before sulfur loading and exhibited atomically dispersed Ru–N4 coordination with a Ru content of 0.42 wt%. S/Ru–NC contained 69.4 wt% sulfur. Compared with NC, Ru–NC increased Li2S6 adsorption efficiency from 31.6% to 78.4%, increased adsorption capacity from 0.79 to 1.96 mmol g−1, reduced peak-potential separation from 0.77 to 0.58 V, and lowered interfacial charge-transfer resistance from 58.7 to 31.4 Ω. Ru–NC also improved Li2S nucleation and decomposition, increasing Li2S deposition capacity from 156.8 to 286.4 mAh g−1 and decreasing decomposition overpotential from 232 to 148 mV. In standard-loading cells, S/Ru–NC delivered 1,276.4 mAh g−1 at 0.1 C and retained 612.4 mAh g−1 after 500 cycles at 1.0 C. Under high-loading lean-electrolyte conditions, S/Ru–NC achieved 4.84 mAh cm−2 initially and retained 3.56 mAh cm−2 after 100 cycles. DFT results confirmed stronger adsorption of sulfur species and greater charge transfer on Ru–NC. In high-loading cells cycled at 1.0 C, S/Ru–NC retained 566.3 ± 24.9 mAh g-1 (2.55 ± 0.12 mAh cm−2) after 50 cycles. The calculated rate-determining Li2S2-to-Li2S barrier decreased from 1.32 eV on NC to 0.68 eV on Ru–NC, while the reverse Li2S oxidation barrier decreased from 1.21 to 0.64 eV.ConclusionAtomically dispersed Ru–N4 sites on nitrogen-doped carbon effectively couple LiPS adsorption with catalytic redox conversion, thereby improving Li2S reaction kinetics and Li–S cell performance under both standard and practical operating conditions. The matched reduction and oxidation barriers show that stronger binding does not create an irreversible Li2S trap.
Codonopsis pilosula, a medicinal plant in the Campanulaceae family, is a classic Qi-tonifying herb in traditional Chinese medicine. Research on the pharmacological basis of its activity has spanned several decades. As pivotal active constituents, Codonopsis pilosula polysaccharides (CPPs) exhibit strong bioactivities, including immunomodulatory, antioxidant, anti-inflammatory, and antitumor effects. To date, approximately 42 homogeneous polysaccharide fractions have been reported from C. pilosula roots, with varying degrees of structural characterization depending on the analytical strategies employed. These CPP fractions exhibit considerable structural diversity in terms of molecular weight, monosaccharide composition, glycosidic linkage patterns, branching architecture, and higher-order conformations. Increasing evidence suggests that these structural characteristics contribute to their diverse biological activities; however, comprehensive understanding of the precise structural determinants underlying CPP bioactivities remains limited. This review systematically summarizes the structural characteristics and pharmacological properties of CPPs, with a specific emphasis on the structure–activity relationships (SAR) underlying their biological effects. We also clarify the molecular mechanisms responsible for their immunomodulatory and antitumor actions and discuss how structural modifications enhance efficacy through well-defined SARs.
Hydrogen is a key alternative to fossil fuels and plays a crucial role in industrial hydrogenation. This study employs first-principles density functional theory (DFT) simulations to investigate transition-metal-decorated Al12N12 single-atom catalysts (SACs) for H2 adsorption and dissociation. Interaction energy calculations indicate excellent thermodynamic stability of the catalysts, with Ti@Al12N12 exhibiting the strongest interaction energy of −2.56 eV. Natural bond orbital (NBO) and frontier molecular orbital (FMO) analyses reveal significant electron transfer from TM atoms to Al12N12, and a reduction of the HOMO-LUMO gap from 3.86 eV to 1.72 eV. The Ti@Al12N12 catalyst exhibits the lowest activation barrier, 0.005 eV, for H2 dissociation. Mechanistic insights indicate that atomic hydrogen (2H*) is more stable than molecular H2, with an energy release up to −1.64 eV. Bidirectional IRC calculations validated the H2 dissociation pathways on TM@Al12N12 catalysts. The blue patches in IRI analysis confirm covalent interactions between hydrogen and TM atoms. This study provides insights into designing efficient SACs for hydrogen dissociation.
Interferon-γ (IFN-γ) is a pivotal inflammatory cytokine whose abnormal expression is associated with autoimmune disorders, infectious diseases, and cancer. Herein, a signal-off electrochemiluminescence (ECL) immunosensor was developed by integrating catalytic signal amplification with oriented antibody immobilization. An amino-functionalized vertically ordered mesoporous silica film (NH2-VMSF) was rapidly grown on indium tin oxide (ITO) electrode by electrochemically assisted self-assembly (EASA), and gold-platinum bimetallic nanoparticles (AuPt NPs) were electrodeposited under nanoconfinement within its vertical nanochannels. The coupled Au and Pt sites promoted both dissolved oxygen (DO) reduction to superoxide radical anion (O2•−) and luminol oxidation, thereby enhancing luminol-DO ECL response. For construction of the biorecognition interface, glutaraldehyde was attached to the external film surface of NH2-VMSF while surfactant micelles still occupied the nanochannels, minimizing nanochannel blockage. Protein A was subsequently covalently coupled and used to orient anti-IFN-γ antibodies through their fragment crystallizable regions. IFN-γ binding formed an interfacial immunocomplex layer that hindered the transport of luminol, producing a concentration-dependent decrease in ECL intensity. The immunosensor can detect IFN-γ from 100 fg mL−1–100 ng mL−1 with limit of detection (LOD) of 31 fg mL−1. This platform provides sensitive strategy for cytokine analysis in complex biological matrices using catalytically amplified luminol-DO ECL system.
IntroductionGreen-synthesized metal nanoparticles, primarily derived from plant sources, have attracted interest due to their inherent sustainability. In this study, we reported the green synthesis of zinc oxide nanoparticles (ZnO NPs) using an aqueous extract of dried lemon peel. In addition, antibacterial activity and in silico analysis of the as-prepared ZnO NPs were performed.MethodsDifferent techniques, including X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), high-resolution transmission electron microscopy (HR-TEM), selected-area electron diffraction (SAED), Thermogravimetric Analysis (TGA) and Zeta potential were used to confirm the synthesis of ZnO NPs using lemon peel extract. MIC and disk diffusion assays were performed to evaluate the antibacterial activity of the ZnO NPs. In silico target prediction and protein–protein interaction (PPI) network analysis of phytochemical compounds present in the lemon peel extract were performed.ResultsMultiple characterization techniques demonstrate the production of ZnO NPs from the lemon peel extract as a capping and stabilizing agent. The antibacterial efficacy of ZnO nanoparticles was assessed against six Gram-positive and Gram-negative bacterial strains, with minimum inhibitory concentrations (MICs) varying from 5 to 15 μg/mL. Furthermore, antimicrobial activity was evaluated by well and disc diffusion assays at different concentrations, confirming its antibacterial activity. Biofilm inhibition was observed at concentrations of 50 μg/mL and 75 μg/mL. In addition, in silico target prediction and PPI network analysis of major lemon peel-derived phytochemicals (eriocitrin, hesperidin, and pectin), which may remain associated with the biosynthesized nanoparticles as capping or stabilizing agents, revealed interactions with multiple bacterial proteins, particularly in E. coli, with significant enrichment in nucleotide biosynthesis, fatty acid metabolism, and central carbon metabolism pathways.DiscussionOverall, the results suggest that biogenic ZnO NPs exhibit strong antibacterial and antibiofilm activity. Computational analyses further indicate that major lemon peel-derived phytochemicals associated with nanoparticle synthesis may contribute to antibacterial activity through interactions with multiple bacterial metabolic pathways, alongside established ZnO-mediated mechanisms such as reactive oxygen species generation, membrane disruption, and zinc ion release.
Femoral fractures represent a major global orthopedic burden, particularly among elderly and osteoporotic populations, and are associated with substantial morbidity, mortality, and healthcare costs. Intramedullary fixation, in which a metallic nail is inserted into the medullary canal to stabilize fractured bone, remains the clinical gold standard because it provides load-sharing stabilization through a minimally invasive approach. Nevertheless, implant–bone mismatch, cortical impingement, fixation instability, infection, and delayed osseointegration continue to compromise long-term outcomes owing to patient-specific anatomical variability, age-related skeletal remodeling, and the limited biological activity of conventional implants. This review provides a comprehensive overview of femoral isthmus morphology, age-dependent anatomical remodeling, and their implications for personalized intramedullary fixation. Particular emphasis is placed on recent advances in functional biomaterials designed to improve implant performance and bone regeneration. Representative strategies include bioactive ceramic coatings (e.g., barium titanate and hydroxyapatite), piezoelectric ceramics, electroactive polymers such as poly (vinylidene fluoride) and poly (L-lactic acid), nanostructured coatings, antibacterial interfaces, multifunctional composite scaffolds, and ultrasound-responsive platforms. These materials have demonstrated the ability to regulate osteoblast proliferation and differentiation, enhance osseointegration, modulate inflammatory responses, inhibit bacterial colonization, and accelerate bone healing by providing biochemical, topographical, and electromechanical stimulation at the bone–implant interface. Furthermore, this review discusses emerging technologies, including additive manufacturing, artificial intelligence-assisted implant design, digital twin modeling, shape-adaptive materials, and patient-specific fixation strategies, which collectively offer new opportunities for precision orthopedic care. By integrating advances in femoral anatomy, biomechanics, materials chemistry, nanotechnology, and piezoelectric bioengineering, this review highlights the development of intelligent and multifunctional intramedullary fixation systems that improve implant integration, promote bone regeneration, and address the growing clinical demands of an aging population.
Polarized luminescent perovskite nanocrystals (PNCs) have emerged as promising optoelectronic materials due to their high photoluminescence quantum yield, narrow emission linewidth, and excellent structural tunability. Benefiting from unique structural anisotropy, chiral ligand modulation and stimulus responsiveness, PNCs enable efficient linear and circular polarized luminescence. This review systematically elaborates the intrinsic mechanisms of PNC-based polarized emission, summarizes advanced macroscopic assembly and structural engineering strategies for stabilizing film state polarized luminescence, and outlines state-of-the-art applications in optoelectronic devices, encryption and spintronics. The current bottlenecks and future development perspectives are also proposed, aiming to promote the advancement of polarized perovskite optoelectronics.
