Search Results (123)

This work evaluated how ferulic acid (FA) impacted the conformational properties of whey protein isolate (WPI) and altered the environmental tolerance of oleogel/water (Og/W) emulsions formulated with Ganoderma lucidum spore oil (GLSO). Molecular dynamics simulation analyses revealed that FA interacted with α-lactalbumin via hydrogen bonding and hydrophobic interactions, whereas it bound into the hydrophobic cavity of β-lactoglobulin through a “lock-and-key” mode driven primarily by hydrophobic forces. Fourier transform infrared spectroscopy analysis verified that such non-covalent forces triggered the dissociation and structural extension of WPI, which was manifested as a significant loss of α-helix and β-sheet architectures along with a corresponding rise in random coils. FA addition increased the positive charge, mean droplet size, interfacial contact angle and antioxidant stability of WPI-FA nanoparticles when the WPI-to-FA ratio exceeded 1:2 (i.e., WPI was in excess relative to FA). The GLSO-based Og/W emulsions exhibited a weak gel structure with predominantly elastic characteristics. Furthermore, WPI-FA nanoparticles fabricated at a 2:1 ratio minimized emulsion droplet size and imparted optimal stability to the Og/W emulsions, demonstrating superior freeze–thaw and salt resistance, alongside suppressed GLSO flavor release. This work provides critical insights into tailoring protein-polyphenol interactions to stabilize GLSO-based Og/W emulsion delivery systems for food applications. Full article

Despite the aim of meeting the demand for long-term online monitoring of structural cracks in fields such as infrastructure, rail transit, aerospace and others, traditional detection methods fail to realize passive wireless, flexible conformal and non-contact measurement. This paper proposes a flexible wireless passive crack sensor based on resonant rings. Taking polyimide (PI) as the substrate, the sensor integrates a sensitive interdigital resonant ring structure. Variations in crack width disturb the electromagnetic field, which further leads to a resonant frequency shift to realize crack width detection. The sensing mechanism is elaborated based on microwave resonance and equivalent circuit theories. Structural optimization and crack width sensitivity analysis are carried out via electromagnetic simulation. Samples are fabricated by flexible printing technology, and a test platform is established. Experiments reveal that the sensor achieves excellent linearity within the crack width range of 0~2.5 mm, with the resonant frequency decreasing monotonically as crack width increases, and a sensitivity of 67.02 MHz/mm. It can operate stably under varying distances, installation angles and bending conditions, demonstrating outstanding flexible conformability. Featuring no power supply requirement, a chip-free design, a simple structure and strong anti-interference capability, the sensor is suitable for long-term crack monitoring of metal structures. Compared with existing studies, the proposed sensor exhibits prominent advantages in flexible adaptability, wireless passive performance and engineering practicability and can provide a novel wireless passive solution for structural health monitoring. Full article

Rotary and vibro-rotary burnishing create regular arrays of imprints whose geometric interaction depends on the pitch, indentation depth, and relative curvature of the tool–workpiece pair. This paper develops a unified kinematic–curvature model that maps machine settings to an imprint layout on the unwrapped cylindrical surface and constructs the relative curvature tensor. The tensor state and full normalized neighbor metric assign the contact state to one of four mutually exclusive categories: non-elliptic, cell-limited, near-conformal (warning), or isolated elliptic. The tensor formulation is invariant under rotation of the tangent basis and provides a common geometric mapping for external cylinders and internal tubes. The kinematic map and tensor classification are independent of the rigid-plastic mean-pressure approximation and are verified by the factor relation between the center-line slope and imprint orientation, tensor invariance, limiting cases, and a closed-form identity. The calibrated approximation is used solely to estimate the maximum-load penetration and an equivalent projected footprint. At a fixed normal force and effective hardness, the projected area is identical in all curvature cases, whereas the curvature changes the penetration and footprint aspect ratio. Neglecting the workpiece curvature underestimates the external cylinder indentation depth by about 5.8% relative to the full tensor calculation; this ratio is independent of the force and effective hardness within the approximation. For the stated internal tube row pitch and hardness, the axis-aligned cell-limited transition force is 5–8 N. Evaluation with the full metric shows that the consecutive-event vectors are separated well; the periodic-row neighbor nevertheless places the reference case in the cell-limited class. A closed-form expression for this transition force is derived. The model provides a transition criterion verified by analytical identity and consistency checks; residual geometry and post-threshold pressure redistribution require unloading calibration and a periodic unilateral contact formulation, respectively. Full article

Cryptosporidium parvum is an important apicomplexan parasite that causes severe diarrheal disease in children and immunocompromised individuals. However, the structural basis for the limited immunogenicity of its T-cell epitopes remains poorly understood. This study integrates structural biology and immunological approaches to elucidate the molecular basis underlying the non-immunogenicity of KAV9, a Cp23-derived epitope with the sequence KAVKNPAPI. Biophysical analyses demonstrated that KAV9 forms a high-affinity complex with H-2D^b, with an IC₅₀ of 7.83 nM, and exhibits higher thermal stability (T_m = 59.16 °C) than the immunodominant LCMV gp33 epitope (T_m = 51.15 °C). Despite strong pMHC binding and high pMHC stability, in vivo peptide immunization failed to elicit a detectable KAV9-specific CD8⁺ T-cell response. Crystal structure analysis revealed that KAV9 is tightly accommodated within the H-2D^b binding groove through an extensive hydrogen-bond network. However, its distinct peptide conformation, particularly involving P4-Lys and the proline residues at P6 and P8, markedly reshapes the TCR-exposed surface compared to gp33. AlphaFold3 (AF3) modeling further suggested that these structural deviations disrupt critical hydrogen-bond interactions with the T-cell receptor (TCR) CDR3 loops, thereby eliminating contacts required for TCRβ engagement. Sequence analysis revealed that KAV9 is highly conserved across multiple Cryptosporidium species, suggesting a conserved structural feature associated with limited T-cell recognition. Together, these findings demonstrate that strong MHC binding and pMHC stability are insufficient to ensure CD8⁺ T-cell immunogenicity. Instead, the topology of the TCR-accessible peptide surface represents a critical determinant of epitope immunogenicity, with significant implications for epitope selection and vaccine design against cryptosporidiosis. Full article

Sarcopenia, characterized by loss of muscle mass and strength, causes difficulty in standing and walking and increases fracture risk in older adults, making its prevention a priority for healthy aging. Whey protein isolate (WPI) promotes muscle protein synthesis, while ellagic acid (EA), a polyphenol, alleviates symptoms by reducing oxidative stress. However, WPI is prone to oxidative damage during processing, and EA suffers from low stability and bioaccessibility. For these reasons, a non-covalent complex was prepared from WPI and EA, and its preparation conditions were systematically optimized through single-factor experiments followed by orthogonal design. The objectives were to enhance the stability and bioaccessibility of EA through the protective effect of WPI, thereby enabling synergistic anti-sarcopenia effects. Multi-spectroscopic techniques and molecular simulations were employed for morphological characterization and interaction analysis. The optimal preparation conditions were pH 5.0, a 2 h reaction, and a WPI: EA molar ratio of 1:2.5. Under these conditions, the antioxidant activity of the WPI-EA non-covalent complex increased by 27.20% (p < 0.05). At the same time, protein digestibility decreased by 3.04% (p < 0.05). EA bound non-covalently near the tryptophan and tyrosine residues of WPI, altering its secondary and tertiary structures. WPI-EA non-covalent complex exhibited a 38.94% reduction in its surface hydrophobicity (p < 0.05) and a 2.42% increase in α-helix content (p < 0.05). These conformational changes provided a structural basis for the improved bioaccessibility of WPI. The spectroscopic observations were corroborated by molecular docking and MD simulations, which revealed that both hydrophobic interactions and hydrogen bonds contributed to the stable binding of EA to β-Lg, with hydrophobic contacts predominating in the binding mode and hydrogen bonds playing a critical role in maintaining conformational stability throughout the simulation. In summary, the WPI-EA non-covalent complex exhibited good antioxidant activity, indicating its potential as a functional ingredient for sarcopenia management and for improving skeletal muscle health in aging individuals. Full article

The voltage-gated sodium channel Nav1.7 is a strongly validated target for the development of novel, non-opioid analgesics due to its genetic link to pain signaling. To accelerate the discovery of safe Nav1.7 modulators, this study outlines an integrated computational pipeline to repurpose FDA-approved drugs. A structurally complete model of the Nav1.7 central pore was generated via homology modeling from a high-resolution cryo-EM structure (PDB: 7W9K) to ensure a physically consistent model suitable for dynamic simulations. We conducted a structure-based virtual screening of 2296 FDA-approved compounds, identifying four promising candidates (DB04868, DB00941, DB01419, and DB15982) with strong predicted affinities ranging from −11.38 to −12.57 kcal/mol. Interaction fingerprinting revealed that binding is predominantly driven by hydrophobic contacts with conserved pore-lining residues, including Phe1503, Leu1010, and Ile1500. To validate these static predictions, the top protein–ligand complexes were subjected to single-replica 250 ns molecular dynamics (MD) simulations. Comprehensive trajectory analyses, including RMSD, RMSF, and principal component analysis, revealed a notable discrepancy between static docking scores and dynamic stability. The highest-scoring docking candidate, DB04868, exhibited substantial conformational flexibility and reduced stabilization under simulated physiological conditions. Conversely, DB01419, despite a lower initial docking rank, demonstrated the highest structural stability across all metrics and uniquely formed intermittent stabilizing hydrogen bonds. These findings underscore the value of post-docking MD validation in computational drug discovery and nominate DB01419 and DB15982 as candidate scaffolds that warrant subsequent experimental validation, including electrophysiological characterization and Nav-isoform selectivity profiling. We emphasize that these are computational predictions: in silico binding stability is not equivalent to functional inhibition of Nav1.7 currents, and the lead designations reported here remain hypothesis-generating until confirmed by patch-clamp and biochemical assays. Full article

To investigate the influence of substrate curvature and process deviations on the bonding quality of microchips mounted on curved surfaces, a thermo–mechanical coupled finite element model was developed in ANSYS 19.2 using a 0402 microchip as a representative component. The model was employed to evaluate the effects of substrate curvature radius, chip placement position, chip angular misalignment, and thermocompression-head angular deviation on the stress distribution and bonding behavior during conformal assembly. The simulation results were further validated through thermocompression bonding experiments. The results show that decreasing the substrate curvature radius significantly increases the stress concentration in the chip-pad region and leads to a more non-uniform stress distribution. In addition, placement errors and loading-direction deviations adversely affect bonding quality by altering the contact stress distribution and increasing the tendency for chip displacement and sliding. Quantitative analysis reveals the relative sensitivity of bonding performance to different geometric and process parameters, providing insight into the dominant thermo–mechanical mechanisms governing curved-surface assembly. Experimental results further demonstrate that excessive thermocompression tilt angles can significantly reduce bonding strength and increase chip sliding, suggesting that the tilt angle should be controlled within an appropriate range to ensure assembly reliability. The proposed thermo–mechanical modeling approach provides a quantitative tool for evaluating the influence of process variations on curved-surface microchip assembly and offers practical guidance for process parameter selection, tolerance control, and reliability-oriented design of conformal electronic packaging. Full article

Background: Ferrocene-containing compounds have gained attention in medicinal chemistry due to their unique redox and structural properties. This study investigates ferrocene-based analogues of imatinib and nilotinib to define their binding determinants within the ABL1 kinase domain using an integrated in silico approach, in relation to their previously reported cytotoxic activity. Methods: Ligand geometries were optimized at the B3LYP/def2-TZVP level with D3(BJ) dispersion and SMD solvation. Molecular docking against ABL1 (PDB ID: 2HYY) was performed using Glide SP, validated by re-docking and enrichment screening. Docked poses were refined using MM-GBSA (Prime, VSGB 2.1/OPLS4). The most active compounds (9 and 15a), together with the inactive control 15e, were subjected to three independent 500 ns molecular dynamics simulations (Desmond, OPLS4), followed by trajectory analysis including RMSD, RMSF, radius of gyration, SASA, and polar surface area. Results: Compounds 9 and 15a maintained stable binding within the ATP-binding pocket despite lacking the canonical hinge interaction with Met318, indicating hinge-independent binding. Their binding was mainly driven by interactions with Asp381 (DFG motif) and cation–π contacts with Lys271. In contrast, the compound 15e showed unstable binding, increased conformational flexibility, reduced pocket burial, and loss of key stabilizing interactions. Active compounds also preserved stable P-loop dynamics, with Tyr253 engagement suggesting a role in loop stabilization. Compound 9 exhibited the most constrained and reproducible binding mode among all analogues. Conclusions: Ferrocene-based analogues can sustain stable ABL1 binding via non-classical interaction networks independent of hinge recognition. The clear distinction between active compounds and the inactive analogue 15e supports the robustness of the proposed binding mode and provides a structural basis for their reported cytotoxic activity. These findings support further experimental evaluation of ferrocene-containing scaffolds as potential BCR-ABL1 inhibitors. Full article

Cysteine proteases (bromelain, ficin, and papain) are widely used in biotechnology and medicine, but their application is limited by rapid autolysis and oxidative inactivation. This study aimed to develop effective supports for these enzymes based on graft copolymers of sodium alginate and poly(N-vinylpyrrolidone) (SA-g-PVP) and to elucidate the structure–property relationships governing immobilization efficiency, catalytic activity, and storage stability. Copolymers were synthesized via radical solution polymerization under optimized conditions. Enzymes were immobilized by physical adsorption, and the resulting complexes were characterized by Fourier-transform infrared (FTIR) spectroscopy, protein content assays, proteolytic and amidase activity measurements, and molecular docking. The graft copolymer with a smaller particle size in solution provided a larger accessible surface area, leading to higher bromelain and papain loading. Ficin showed the opposite trend due to its unique surface amino acid composition. Immobilization dramatically increased storage stability: half-life values for bromelain, ficin, and papain reached up to 20, 14, and 14 days, respectively, compared to 1–3 days for the free enzymes. Molecular docking revealed that the dense polymer shell stabilizes the enzyme tertiary structure by forming multiple contacts with internal cavities and tunnels, thereby preventing autolysis and conformational unfolding. Collectively, these findings demonstrate that SA-g-PVP copolymers are promising, non-toxic supports for cysteine proteases, with ficin showing up to 100% activity recovery, making them suitable for food, cosmetic, and biomedical applications. Full article

Parkinson’s disease is strongly linked to lysosomal dysfunction, particularly reduced activity of glucocerebrosidase (GCase) encoded by the GBA1 gene. Stabilizing GCase using small-molecule modulators represents a promising therapeutic strategy. In this study, phytochemicals from Xylia xylocarpa (Roxb.) Taub., a medicinal plant with reported neuroprotective potential, were profiled using LC-QTOF-MS and evaluated as GCase stabilizers through an integrated computational approach. LC-MS analysis in positive and negative modes tentatively identified 19 metabolites, of which 13 low-molecular-weight compounds (<500 Da) were selected for molecular docking against human GCase. Docking revealed six compounds with higher predicted binding affinity than the reference activator Pyrrolopyrazine. Pharmacokinetic screening based on Lipinski’s rule of five and ADMET predictions identified Senbusine A as a viable lead candidate. It exhibited favorable binding interactions, forming stabilizing contacts within a non-catalytic inter-monomer interface associated with structural modulation of GCase. PASS analysis suggested a high probability of neuroactive properties. Molecular dynamics simulations (200 ns) confirmed stable binding and reduced conformational fluctuations compared to apo and control systems. Overall, computational predictions identify Senbusine A as a potential pharmacological chaperone-like stabilizer of GCase, exhibiting a favorable pharmacological profile and warranting further experimental validation. Full article

In this work, three 3-carboxamidecoumarin derivatives (3b, 3c, and 4) were synthesized and characterized by NMR, IR, and single-crystal X-ray. All compounds maintain an essentially planar coumarin scaffold stabilized by an intramolecular N–H⋯O hydrogen bond (S(6) motif), though compound 4 exhibits a more complex bifurcated S₃²(11)[S(6)S(6)S(5)] network that enhances its conformational rigidity. The crystal packing analysis reveals that while all derivatives form one-dimensional (1D) supramolecular tapes through C–H⋯O interactions, their 3D architectures differ significantly: 3b and 3c rely on a diverse combination of π⋯π stacking and lone pair⋯π contacts, whereas 4 is governed by highly directional stacking between the pyran and pyridine rings. Hirshfeld surface analysis and CE-B3LYP energy framework calculations quantified the balance between intermolecular forces, showing that 3b is dispersion-dominated (H⋯H, 43.5%), while 3c achieves a balanced electrostatic–dispersion regime due to the nitro group, which increases O⋯H/H⋯O contacts to 37.1% and yields the highest stabilization energy (−69.1 kJ/mol). These results demonstrate that the electronic nature of the substituents at the 3- and 6-positions drastically modulates the hierarchy of non-covalent interactions, providing key insights for the crystal engineering of coumarin-based supramolecular systems. Full article

Reliable potato quality monitoring during postharvest handling requires compact sensing systems that can acquire chemically relevant information while operating on irregular tuber surfaces. In this study, a Flexible Spectral Sensing Gripper (FSSG) was developed by integrating a low-cost 12-channel visible/near-infrared (Vis/NIR) spectral sensor array, electronic components, and an ESP32-S microcontroller onto a flexible printed circuit (FPC) substrate encapsulated with PDMS. By embedding the sensing units into the grasping interface, the FSSG enables conformal, multi-point spectral acquisition during potato handling, reducing optical-coupling uncertainty associated with unstable contact. Spectral reflectance data were collected from potato tubers, and dry matter content (DMC) and starch content (SC) were determined by standard chemical analysis as reference values. Multiple linear regression (MLR) and partial least squares regression (PLSR) models were compared under Norm, SNV, MSC, SNV-Norm, and MSC-Norm preprocessing conditions, and support vector machine (SVM) classification was used to distinguish healthy and artificially induced deteriorated samples. Normalization combined with MLR provided the best performance among the evaluated regression approaches, achieving cross-validation coefficients of determination ($R_{CV}^2$) of 0.847 and 0.817 and RPD values of 2.557 and 2.345 for DMC and SC, respectively. The SVM model achieved 98.67% accuracy for healthy versus artificially induced deteriorated potato samples. Overall, the FSSG demonstrates the value of combining gripper-integrated spectral sensing with interpretable chemometric modeling for potato quality screening. The FSSG enables real-time non-destructive quality prediction and disease-detected classification of potatoes, improves sorting accuracy and production efficiency, and provides general sensing solutions for controlled-environment agriculture, cold-chain logistics, and value-added processing of agricultural products. Full article

Continuous monitoring of pig behavior is essential for timely health management and welfare assessment in commercial production systems. Although vision-based methods have been widely studied, their practical application in commercial barns is often limited by variable lighting, frequent occlusion, and high stocking density. Acoustic sensing offers a non-contact alternative that is independent of lighting conditions; however, reliable behavior classification from pig vocalizations remains challenging in commercial environments because of background noise and temporal variability in sound patterns. In this study, an attention-guided acoustic framework, termed ATF-Conformer, was developed for pig vocalization classification under farm conditions. A five-class vocalization dataset was collected from finishing Landrace pigs and multiparous sows on a commercial farm, including cough, scream, estrus, feeding, and normal behavior sounds. The proposed framework combined spectrogram denoising with interactive attention to enhance behavior-related acoustic information, while a time-frequency-decoupled Conformer encoder was introduced to improve feature representation under noisy conditions. Final classification was performed using mask-based temporal pooling with an additive angular margin Softmax objective. In five-fold grouped cross-validation, ATF-Conformer achieved an accuracy of 97.34% ± 0.42 and outperformed several existing acoustic models across multiple evaluation metrics. A similar accuracy of 97.38% was obtained on an independent test set, indicating stable performance across datasets. These results suggest that the proposed method can support continuous, non-invasive pig vocalization-based behavior monitoring and may assist farm owners or workers in pen-level screening of frequent cough or abnormal vocal events, thereby supporting targeted on-site inspection in precision livestock farming. Full article

In this paper, a novel multiband microwave resonator is proposed and investigated for non-invasive glucose sensing applications. The structure is based on a compact, planar spiral-like geometry fed by a Coplanar waveguide (CPW) transmission line, designed to support multiple resonant modes through nested concentric rings. A full electromagnetic model was developed to predict the resonance behavior analytically, achieving excellent agreement with Computer Simulated Technology (CST) simulations across four resonant frequencies (2.7, 6.44, 8.0, and 12.8 GHz). The sensor demonstrated high glucose sensitivity at multiple frequencies, with peak values reaching 0.05 dB/mg/dL and 0.038 dB/mg/dL at 10.1 GHz and 6.22 GHz, respectively. To enhance conformability and skin contact, the antenna was further transformed into a semi-cylindrical flexible form suitable for finger-wrapping. Despite the mechanical deformation, the structure preserved its resonance while offering enhanced near-field interaction with biological tissues. The folded sensor achieved a sensitivity of 0.032 dB/mg/dL at 5.25 GHz and a peak gain of 6.05 dB, validating its robustness for wearable deployment. The clear correlation between reflection magnitude and glucose level (with R > 0.99) confirms the sensor’s potential as a passive, multiband, and non-invasive glucose monitoring platform. The physics-informed residual deep learning framework significantly enhances prediction accuracy, achieving an RMSE of 0.28 mg/dL, MARD of 0.13%, and confining 100% of both training and holdout predictions within the <5% ISO-like risk region, thereby ensuring robust and clinically reliable non-invasive glucose estimation. 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