Search Results (159)

Metal-free electrodes are essential to promote electrochemical reactions, the core of sustainable energy resources. In search of better carbon-based electrode materials, we have explored several spatial arrangements of boron (B) within proximity in the graphene lattice, as evident in recent experimental observations. Multi-boron substitution enriches sites by tuning electronic structure and strengthens binding of key intermediates of oxygen reduction, oxygen evolution, and hydrogen evolution reactions facilitating electrocatalytic performance. Our optimal B-doped site shows near thermo-neutral H adsorption ($\Delta G_{H^{*}}$∼$\pm 0.4\mathrm{eV}$), consistent with experiments. The overpotentials are highly sensitive to the dopant motifs and the spread among configurations shows that experimentally accessible multi-B doping can serve as a practical active site engineering knob to achieve optimized multi-functional performance. In parallel, we find that specific multi-B configurations selectively capture and pre-activate NO_x (NO/NO₂) under ambient conditions while retaining weak affinity for NH₃. These sites also interact with SO₂ and related hazardous species, enabling selective air filtration and targeted NO_x control within the electrocatalytic scope of this study. Full article

Aspergillus flavus infection and accumulation of carcinogenic aflatoxins are detrimental to maize (Zea mays) production and consumption. We investigated lncRNA–RBP interactions during maize–A. flavus crosstalk using transcriptomic profiling, structural analysis, molecular docking simulations, and machine learning approaches. Analysis of 18 RNA-seq datasets identified 2104 lncRNAs in maize, of which 461 were differentially expressed under A. flavus infection. Distinct lncRNAs were preferentially induced under infection (e.g., Zm00001eb303170) or normal germination (e.g., Zm00001eb144150, Zm00001eb406410). RNA secondary structure predictions indicated high structural heterogeneity and thermodynamic stability, consistent with dynamic regulatory potential. Docking simulations with six key RNA binding proteins (RBPs)—including branch point bridging protein (BPB), KH domain protein, and pentatricopeptide repeat (PPR) proteins—demonstrated strong lncRNA–protein binding, with the lncRNA1–BPB complex exhibiting the highest binding affinity. ML algorithms identified the crucial role of tryptophan in determining interactions, while lncRNA17-KH and lncRNA1-BP complexes were found to have the best interaction under normal germination and A. flavus infection, respectively. The lncRNA–miRNA–mRNA regulatory network highlighted lncRNAs functioning as decoys or precursors of stress-responsive miRNAs (e.g., zma-miR156, zma-miR164, zma-miR399). These interactions targeted transcriptional regulators, splicing factors, and metabolic enzymes implicated in stress tolerance, seed germination, and systemic acquired resistance. The maize lncRNAs are active regulatory molecules embedded in complex RBP and miRNA interaction networks that fine-tune gene expression during A. flavus infection. The study provides novel insights into lncRNA-mediated resistance mechanisms and offers potential molecular targets for breeding or gene editing to mitigate aflatoxin contamination. Full article

Hydrophobic nanofiber membranes derived from the biopolymer alginate were fabricated by electrospinning followed by metal ion crosslinking, and their potential as oil-water separation membranes was primarily investigated. Sodium alginate (SA) was co-electrospun with polyethylene glycol and subsequently crosslinked using calcium chloride and group IV metal ions (zirconium or titanium). Metal ion crosslinking changed the surface wettability of the nanofiber membranes, as confirmed by water contact angle measurements. Both zirconium- and titanium-crosslinked SA nanofiber membranes exhibited effective gravity-driven oil–water separation with complete water blocking. Although hydrophobic modification reduced direct water affinity, the resulting membranes retained residual adsorption capability toward methylene blue, indicating the presence of accessible internal polar sites. The adsorption behavior varied depending on the crosslinking ion. In addition, titanium-crosslinked membranes showed an auxiliary UV-assisted dye removal contribution under irradiation, arising from photoactive Ti species. These findings demonstrate that metal ion crosslinking provides a practical route for tuning the functional properties of alginate nanofiber membranes, with oil-water separation as the primary application and dye adsorption/photocatalysis as secondary functionalities. Full article

Chemokines play a central role in orchestrating neutrophil recruitment from the bloodstream and determining their effector functions at sites of infection. Chemokine activity is determined by three key properties: reversible monomer–dimer equilibrium, binding to glycosaminoglycans (GAGs), and signaling through the GPCR class of receptors CXCR1 and CXCR2. In this study, we investigated the structural basis of CXCL8 monomer and dimer binding to GAG chondroitin sulfate (CS) using nuclear magnetic resonance (NMR) spectroscopy, docking, and molecular dynamics (MD) measurements. Our studies reveal that both the monomer and dimer use essentially the same set of basic residues for binding, that the interface is extensive, that the dimer is the high-affinity CS ligand, and that the CS-binding residues form a contiguous surface within a monomer. Several of these residues also participate in receptor interactions, suggesting that CS-bound CXCL8 is likely impaired in its ability to bind receptors. Notably, we observe that the same basic residues are involved in binding CS and heparin/heparan sulfate, even though these GAGs differ in backbone structures and sulfation patterns. We conclude that the strategic distribution and topology of basic residues on the CXCL8 scaffold enable engagement with diverse GAG structures, which likely allows fine-tuning receptor signaling to regulate neutrophil trafficking and effector functions. Full article

Background/Objectives: NANOBODY^® molecules (VHHs) are attractive vectors for radiopharmaceuticals due to their small size and high target affinity, but rapid clearance and pronounced kidney retention limit their therapeutic applicability. Binding to serum albumin is a widely used strategy to prolong circulation, yet the respective contributions of albumin-binding affinity and molecular format remain insufficiently defined. This study aimed to systematically evaluate how affinity and valency modulate VHH pharmacokinetics. Methods: Four monovalent albumin-binding VHHs spanning nanomolar to micromolar affinities and two bivalent constructs were engineered, generated by fusing an albumin-binding VHH to an irrelevant non-binding VHH. All constructs incorporated a site-specific cysteine for DFO* conjugation, enabling uniform zirconium-89 labeling with high radiochemical purity. Pharmacokinetics were assessed in healthy mice using serial blood sampling and positron emission tomography. Blood and kidney exposure were quantified by non-compartmental analysis. Results: All albumin-binding constructs showed increased systemic exposure and reduced kidney uptake relative to a non-binding control. Nanomolar-affinity binders reached maximal exposure, and further affinity increases (K_D < ~100 nM) did not improve pharmacokinetics, suggesting a threshold. The micromolar binder showed intermediate exposure but still reduced renal retention compared with control. Valency effects were affinity-dependent. They were negligible at high affinity but pronounced at low affinity, where bivalency reduced systemic exposure and increased kidney uptake toward control levels. Conclusions: Albumin binding enables tuning of VHH pharmacokinetics in an affinity-dependent manner. Above an apparent affinity threshold, pharmacokinetics become format independent, whereas below this threshold, molecular format substantially influences systemic and renal disposition. Full article

Nanoparticles interact dynamically with proteins, often leading to adsorption-induced conformational changes that alter protein function and contribute to corona formation. Here we investigated the adsorption and unfolding of a model protein GB1 on latex nanoparticle surfaces using a combination of mutational analysis, equilibrium binding assays, stopped-flow kinetics and Φ-value interpretation. Seven site-directed variants of GB1 were studied to dissect residue-specific contributions to adsorption energetics. Fluorescence binding isotherms revealed that D46A and T53A mutations weakened surface affinity, while kinetic analysis demonstrated that D46A reduced adsorption rate by ~6-fold and produced a dramatic unfolding/refolding shift, identifying Asp46 as a key docking site. Φ-value analysis further highlighted Asp46 and Thr53 as central residues in the adsorption transition state, whereas mutations in the hydrophobic core or distal loops had negligible effects. These results support a dock–loosen–unfold mechanism in which electrostatic recognition initiates binding, followed by hydrophobic exposure and hairpin stabilization. This residue-level sampling of key sites advances mechanistic understanding of protein–nanoparticle interactions and suggests strategies for tuning surface charge to control corona formation. Our approach provides a generalizable method to map adsorption transition states, with implications for designing safer nanomaterials, predicting protein corona composition, and harnessing protein unfolding in biosensing applications. Full article

This study presents a green synthesis of zinc oxide (ZnO) nanoparticles (NPs) capped with Haloxylon (P1) and Calligonum (P2) extracts. The use of plant-derived biomolecules as natural capping agents offers an environmentally friendly strategy to tune surface chemistry and to enhance the photocatalytic behavior of ZnO NPs. ZnO/plant extracts nanocomposites were prepared via a hydrothermal route and systematically characterized using transmission electron microscopy (TEM), X-ray diffraction (XRD), UV–Vis spectroscopy, and photoluminescence (PL), followed by evaluation of their photocatalytic performance against methylene blue (MB) under UV irradiation. XRD confirmed a wurtzite structure with crystallite sizes ranging from 8.95 to 10.93 nm, while PL spectra indicated an improved charge carrier separation in extract-capped ZnO. The characteristics and pollutant removal performance of the greenly synthesized ZnO composites were compared with those of a chemically synthesized ZnO nanoparticles reference sample. Adsorption tests under dark conditions revealed a strong difference between the materials: ZnO-P1 removed 48% of MB, whereas ZnO-P2 adsorbed only 7%, demonstrating a much higher affinity of the Haloxylon-derived surface groups toward MB. In comparison, the chemically synthesized ZnO exhibited an adsorption capacity of 54%, confirming that the Haloxylon-mediated surface provides a comparable efficient dye uptake prior to irradiation. After UV irradiation, all samples exhibited a photocatalytic activity with a total MB removal reached ~59% for the reference ZnO sample and ~53% for ZnO-P1 compared to about 13% for the ZnO-P2. Kinetic analysis also confirmed that ZnO-P1 possessed a high degradation rate constant, indicating a better intrinsic photocatalytic efficiency in addition to the strong adsorption contribution. The enhanced performance of plant-capped ZnO is attributed to phytochemical-induced surface defects, which facilitated charge separation and boosted the generation of reactive oxygen species (ROS). Overall, these results demonstrate that Haloxylon and Calligonum extracts are effective and sustainable capping agents, providing a low-cost, eco-friendly approach for designing ZnO nanocatalysts composites with promising applications in wastewater treatment and environmental remediation. Full article

Mine-induced surface subsidence threatens infrastructure and can trigger cascading geohazards, so accurate and computationally efficient monitoring and forecasting are essential for early warning. We integrate Persistent Scatterer InSAR (PS-InSAR) time series with a Bayesian-optimized CNN–LSTM designed for spatiotemporal prediction. The CNN extracts spatial deformation patterns, the LSTM models temporal dependence, and Bayesian optimization selects the architecture, training hyperparameters, and the most informative exogenous drivers. Groundwater level and backfilling intensity are encoded as multichannel inputs. Endpoint anchoring with affine calibration aligns the historical series and the forward projections. PS-InSAR indicates a maximum subsidence rate of 85.6 mm yr⁻¹, and the estimates are corroborated against nearby leveling benchmarks and FLAC^3D simulations. Cross-site comparisons show acceleration followed by deceleration after backfilling and groundwater recovery, which is consistent with geological engineering conditions. A symmetry-aware preprocessing step exploits axial regularities of the deformation field through mirroring augmentation and documents symmetry-breaking hotspots linked to geological heterogeneity. These choices improve generalization to shifted and oscillatory patterns in both the spatial CNN and the temporal LSTM branches. Short-term forecasts from the BO–CNN–LSTM indicate subsequent stabilization with localized rebound, highlighting its practical value for operational planning and risk mitigation. The framework combines automated hyperparameter search with physically consistent objectives, reduces manual tuning, enhances reproducibility and generalizability, and provides a transferable quantitative workflow for forecasting mine-induced deformation in complex goaf systems. Full article

Despite the groundbreaking impact of currently approved CAR T-cell therapies, substantial unmet clinical needs remain. This highlights the need for CAR T treatments that are easier to tune, combine, and program with logic rules, in oncology and autoimmunity. Modular CAR T cells use a two-part system: the CAR on the T cell binds an adaptor molecule (AM), and that adaptor binds the tumour-associated antigen (TAA). This design separates recognition of the target antigen and activation of the T cells, resulting in a cellular therapy concept with better control, flexibility, and safety compared to established direct-targeting CAR T-cell systems. The key advantage of the system is the adaptor molecule, often an antibody-based reagent, that targets the TAA. Adaptors can be swapped or combined without re-engineering the T cells, enabling straightforward multiplexing and logic-gated control. The CAR itself is designed to recognise the AM via a unique tag on the adaptor. Only when the CAR, AM, and antigen-positive target cell assemble correctly is T-cell effector function activated, leading to cancer cell lysis. This two-component system has several features that need to be considered when designing a modular CAR: First, the architecture of the CAR, i.e., how the binding domain and the backbone are designed, can influence tonic signalling and activation/exhaustion parameters. Second, the affinity of CAR–AM and AM–TAA will mostly define the engagement kinetics of the system. Third, the valency of the AM has an impact on exhaustion and non-specific activation of CAR T cells. And lastly, the architecture of the AM, especially the size, defines the pharmacokinetics and, consequently, the dosing scheme of the AM. The research conducted on direct-targeting CAR T cells have generated in-depth knowledge of the advantages and disadvantages of the technology in its current form, with remarkable clinical success in relapsed/refractory disease and long-term survival in otherwise difficult-to-treat patient populations. On the other hand, CAR T-cell therapy poses the risk of severe adverse events and antigen loss coupled with antigen-negative relapse which remains the main reason for failed therapies. Addressing these issues in the traditional setting of one CAR targeting one antigen will always be difficult due to the heterogeneous nature of most oncologic diseases, but the flexibility to change target antigens and the modulation of CAR T response by dosing the AM in a modular CAR system might be pivotal to mitigate these hurdles of direct CAR T cells. Since the first conception of modular CARs in 2012, there have been more than 30 constructs published, and some of those have been translated into phase I/II clinical trials with early signs of success, but whether these will progress into a late-stage clinical trial and gain regulatory approval remains to be seen. Full article

The catalytic hydrogenation of CO₂ to methanol represents a promising route for carbon recycling and hydrogen storage. However, the stability of current catalysts remains one of the main technological challenges. In this work, we investigate the promotional effect of MoO₃ and ReO₃ on Cu/ZnO-based catalysts with metal loadings ranging from 0.06 to 3.5 wt%. Spectroscopic (XPS and in situ Raman) and kinetic studies reveal that the incorporation of ultra-low promoter amounts (0.06 wt%) enhances methanol productivity, whereas higher concentrations lead to partial blocking of the active copper sites. Rhenium promotes the stabilization of Cu⁺ species, while molybdenum establishes strong Cu-Mo interactions that modify the reducibility and surface composition of the catalyst. Remarkably, long-term stability tests (80 h, 240 °C, 20 bar and CO₂/H₂ = 3) demonstrate that Mo-promoted catalysts exhibit superior durability, reducing the deactivation constants by up to 82% compared to the un-promoted Cu/ZnO sample. This enhanced stability is attributed to the higher Cu-MoO₃ interaction, enhanced Cu dispersion and high water affinity of Mo species, which trap water as Mo-OH bonds, preventing copper sintering under reaction conditions. These findings highlight the dual role of Re and Mo in tuning both activity and stability, emphasizing the crucial influence of Mo on the long-term performance of Cu-based catalysts for CO₂ to methanol conversion. Full article

Organophosphate pesticides are among the most persistent and toxic contaminants in aquatic environments, requiring effective strategies for detection and remediation. In this work, density functional theory (DFT) calculations were employed to investigate the adsorption of nine representative organophosphates (glyphosate, malathion, diazinon, azinphos-methyl, fenitrothion, parathion-methyl, disulfoton, tokuthion, and ethoprophos) on mercaptobenzothiazole disulfide (MBTS) and MBTS-functionalized graphene (G–MBTS). All simulations were performed in aqueous solution using the SMD solvation model with dispersion corrections and counterpoise correction for basis set superposition error. MBTS alone displayed a range of affinities, suggesting potential selectivity across the organophosphates, with adsorption energies ranging from 0.27 to 1.05 eV, malathion being the strongest binder and glyphosate the weakest. Anchoring of MBTS to graphene was found to be highly favorable (1.26 eV), but the key advantage is producing stable adsorption platforms that promote planar orientations and $\pi$–$\pi$/dispersive interactions. But the key advantage is not stronger binding but the tuning of interfacial electronic properties: all G–MBTS–OP complexes show uniform, narrow HOMO-LUMO gaps (∼0.79 eV) and systematically larger charge redistribution. These features are expected to enhance electrochemical readout even when adsorption strength was comparable or slightly lower (0.47–0.88 eV) relative to MBTS alone. A Quantum Theory of Atoms in Molecules (QTAIM) analysis of the G–MBTS–malathion complex revealed a dual stabilization mechanism: multiple weak C–H⋯$\pi$ interactions with graphene combined with stronger S⋯O and hydrogen-bonding interactions with MBTS. These results advance the molecular-level understanding of pesticide–surface interactions and highlight MBTS-functionalized graphene as a promising platform for the selective detection of organophosphates in water. Full article

Cytochrome P450 enzymes (CYPs) are versatile biocatalysts capable of performing selective oxidation reactions valuable for industrial and pharmaceutical applications. However, their catalytic efficiency is often constrained by dependence on costly electron donors, the requirement for redox partners, and uncoupling reactions that divert reducing power toward reactive oxygen species. Improving electron transfer efficiency through optimized redox partner interactions is therefore critical for developing effective CYP-based biocatalysts. In this study, we investigated the interaction between CYP119, a thermophilic CYP from Sulfolobus acidocaldarius, and putidaredoxin (Pdx), the redox partner of P450cam. Using rational design and computational modeling with PyRosetta 3, 14 CYP119 variants were modeled and analyzed by docking simulations on the Rosie Docking Server. Structural analysis identified three key mutations (N34E, D77R, and N34E/D77R) for site-directed mutagenesis. These mutations (N34E, D77R, and N34E/D77R) enhanced Pdx binding affinity by 20-, 3-, and 12-fold, respectively, without affecting substrate binding. Catalytic assays using lauric acid and indirect assays to monitor electron transfer revealed that, despite improved complex formation, the N34E variant showed reduced electron transfer efficiency compared to D77R. These findings highlight the delicate balance between redox partner binding affinity and catalytic turnover, emphasizing that fine-tuning electron transfer interfaces are essential for engineering efficient CYP biocatalysts. Full article

Food-derived bioactive peptides are known to possess immunomodulatory properties, although their molecular mechanisms remain incompletely characterized. In this study, we investigated the immunoregulatory effects and underlying mechanisms of YPFPGPIH, a peptide derived from bovine β-casein, using the RAW264.7 macrophage model. Our results demonstrate that YPFPGPIH enhanced macrophage proliferation and phagocytosis in a dose-dependent manner and promoted chemotactic migration through the upregulation of monocyte chemoattractant proteins MCP-1 and MCP-3. Under lipopolysaccharide (LPS)-induced inflammatory conditions, YPFPGPIH significantly reduced the levels of pro-inflammatory mediators, including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and nitric oxide (NO), while increasing the production of the anti-inflammatory cytokine interleukin-10 (IL-10), thereby reestablishing cytokine balance. Mechanistic studies revealed that YPFPGPIH inhibited LPS-induced activation of the NF-κB and MAPK pathways, as indicated by reduced nuclear translocation of p65 and decreased phosphorylation of ERK, JNK, and p38. Molecular docking analysis indicated strong binding affinities between YPFPGPIH and Toll-like receptors TLR2 and TLR4, suggesting the involvement of TLR-mediated signaling. Notably, YPFPGPIH downregulated inducible nitric oxide synthase (iNOS) expression and upregulated chemokine mRNA levels, reflecting its dual role in modulating inflammatory and migratory responses. These findings highlight YPFPGPIH as a multifunctional immunomodulatory peptide that fine-tunes macrophage activity through crosstalk between TLR, NF-κB, and MAPK signaling pathways. This study provides new insights for developing peptide-based therapeutics and functional foods aimed at managing inflammatory diseases. Full article

Karst rocky desertification on the Qinghai–Tibet Plateau poses a severe threat to the region’s fragile ecosystem. Accordingly, the rapid and accurate delineation of plateau karst landforms is essential for monitoring ecological degradation and guiding restoration strategies. However, automatic recognition of these landforms in remote sensing imagery is hindered by challenges such as blurred boundaries, fragmented targets, and poor intra-region consistency. To address these issues, we propose the Region Affinity Propagation Network (RAP-Net). This framework enhances intra-region consistency, edge sensitivity, and multi-scale context fusion through its core modules: Region Affinity Propagation (RAP), High-Frequency Multi-Scale Attention (HFMSA), and Global–Local Cross Attention (GLCA). In addition, we constructed the Plateau Karst Landform Dataset (PKLD), a high-resolution remote sensing dataset specifically tailored for this task, which provides a standardized benchmark for future studies. On the PKLD, RAP-Net surpasses eight state-of-the-art methods, achieving 3.69–10.31% higher IoU and 3.88–14.28% higher Recall, thereby demonstrating significant improvements in boundary delineation and structural completeness. Moreover, in a cross-regional generalization test on the Mount Genyen area, RAP-Net—trained solely on PKLD without fine-tuning—achieved 2.38% and 1.94% higher IoU and F1-scores, respectively, than the Swin Transformer, confirming its robustness and generalizability in complex, unseen environments. Full article

Lead-free perovskite solar cells (PSCs) provide a viable alternative to lead-based versions, thereby reducing significant environmental issues related to toxicity. MASnIBr₂ has emerged as a very attractive lead-free perovskite material due to its environmentally friendly characteristics and advantageous optoelectronic capabilities. However, more tuning is required to achieve superior conversion efficiencies (PCEs). This study uses SCAPS-1D simulations to systematically develop and optimize the electron and hole transport layers (ETLs/HTLs) in MASnIBr₂-based perovskite solar cells (PSCs). Iterative simulations are used to carefully examine and optimize critical parameters, including electron affinity, energy bandgap, layer thickness, and doping density. Additionally, the thickness of the MASnIBr₂ absorber layer is optimized to enhance charge extraction and light absorption. Our findings showed a maximum power conversion efficiency of 20.42%, an open-circuit voltage of 1.38 V, a short-circuit current density of 17.91 mA/cm², and a fill factor of 82.75%. This study establishes a basis for future progress in sustainable photovoltaics and offers essential insights into the design of efficient lead-free perovskite solar cells. Full article