Search Results (138)

Gluten proteins are key components in wheat flour that determine the formation of dough and the quality of flour-based products. Upon hydration and mixing, gluten proteins undergo complex structural transformations to form a gluten network, exhibiting a hierarchical multi-scale structure spanning molecular, aggregate, and network scales. Due to the extreme complexity of gluten proteins, accurately characterizing their multi-scale structures remains challenging, requiring the combined application of multiple techniques, which are still relatively limited and thus warrant further exploration. Therefore, this review presents the principles, operational details, and result presentations of current techniques at different structural scales, including electrophoresis, high-performance liquid chromatography, proteomics, Fourier transform infrared spectroscopy, and Fourier transform Raman spectroscopy at the molecular scale; size-exclusion chromatography, asymmetrical flow field-flow fractionation, dynamic light scattering, multi-angle light scattering, differential refractive index, and ultraviolet absorbance at the aggregate scale; and confocal laser scanning microscopy, scanning electron microscopy, confocal Raman microscopy, and two-photon excitation microscopy at the network scale, among others. It further compares the advantages and disadvantages of similar techniques, facilitating their scenario-based selective utilization. Finally, it outlines the ongoing challenges and future perspectives for the development and application of techniques for the multi-scale structural characterization of gluten proteins. Full article

Background: Traditionally, wild jujube (Ziziphus jujuba Mill. var. spinosa (Bunge) Hu ex H. F. Chou) has been used to nourish the heart, calm the spirit, and arrest spontaneous sweating. Modern research confirms its broad pharmacological activities, including antioxidant, anti-inflammatory, neuroprotective, and cognitive-enhancing effects. This study aims to isolate and characterize the structure of jujube polysaccharides and evaluate their protective effects against oxidative stress damage in neural stem cells (NSCs). Methods: We successfully isolated and purified a novel pectin polysaccharide (ZJP-2) from wild jujube. Its structure was characterized in detail using high-performance liquid chromatography coupled with multi-angle laser light scattering and refractive index detection (HPLC-MALS-RI), high-performance anion exchange chromatography (HPAEC), gas chromatography–mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) spectroscopy. Results: Structural analysis revealed that ZJP-2 is a pectin heteropolysaccharide with a molecular weight of approximately 67.93 kDa. Its monosaccharide composition primarily includes galac-turonic acid (GalA), arabinose (Ara), rhamnose (Rha), galactose (Gal), and glucose (Glc). The backbone consists of α-GalA and rhamnose-galacturonic acid-I (RG-I) domains linked by (1→4)-glycosidic bonds. NMR spectroscopy further confirmed its glycosidic bond types. In activity assessment, our study demonstrated that ZJP-2 significantly alleviated DMNQ-induced oxidative stress damage in C17.2 neural stem cells. Its protective effect was achieved by reducing intracellular reactive oxygen species (ROS) levels and upregulating the mRNA expression of antioxidant genes associated with the signaling axis (p < 0.05). Moreover, ZJP-2 suppressed DMNQ-induced overexpression of Nestin and NeuN (p < 0.05), contributing to the maintenance of NSCs’ undifferentiated state and functional homeostasis. Conclusions: In conclusion, ZJP-2 possesses distinct structural characteristics and significant neuroprotective potential, supporting its development as a natural functional food or dietary supplement for preventing oxidative stress-related neural damage. Full article

Nucleation remains one of the least understood steps during protein crystallization, although it strongly impacts product quality attributes, including total crystal numbers, final crystal size distributions, and thus downstream processing. In this work, the nucleation behavior of Lactobacillus brevis alcohol dehydrogenase (LbADH) wild type (WT) and five mutants (Q207D, Q126H, K32A, D54F, and T102E) is investigated in a stirred 7 mL crystallizer monitored by in situ multi-angle dynamic light scattering (MADLS). Nucleation was studied with highly pure homotetrameric LbADHs by establishing a crystallization, lyophilization, and re-solubilization protocol combined with size exclusion chromatography (SEC) and size exclusion high-performance liquid chromatography (SE-HPLC), yielding tetramer purities above 94% and removing low molecular weight impurities. During stirred batch crystallizations initiated by the addition of polyethyleneglycol 550 monomethyl ether (PEG 550 MME), SEC and SE-HPLC revealed decreasing tetramer peak areas but essentially constant peak apex positions, indicating that no long-lasting oligomeric intermediates accumulate at detectable levels. Time-resolved MADLS measurements using a custom-made flow-through cuvette in a bypass to the stirred crystallizer uncovered transient cluster populations. All protein variants exhibited an initial tetramer peak, followed by the formation of larger aggregates and a rapid rise in signal above a hydrodynamic diameter of 1000 nm, coinciding with the onset of macroscopic turbidity. A simple mesoscale nucleation model was formulated, yielding end-of-nucleation times, crystallized fractions, critical soluble concentrations, and apparent nucleation rate constants. The crystal contact mutations modulate both the timing and magnitude of the nucleation burst (rapid build-up of nuclei/cluster populations). The mutant Q207D showed strongly attenuated nucleation compared to the WT, whereas the other mutants (K32A, D54F, and particularly T102E) display markedly accelerated nucleation at nearly invariant critical concentrations. The combined workflow demonstrates how in situ MADLS, together with a tailored kinetic description, can provide mechanistic insight into protein nucleation in stirred batch crystallizers. Full article

Silica-based multifunctional coatings hold great promise for applications in optical devices, lenses, and solar panels. Herein, we report a facile, low-temperature route to integrate super-hydrophobicity with high transparency and low haze. By precisely controlling particle gradation and applying fluorine passivation, a multi-scale structure with micro-scale uniformity and nano-scale asperity was constructed. This unique architecture, combined with low surface energy, effectively reduces light scattering and enhances air trapping. Consequently, the coated glass achieves a high optical transmittance of 95.24% with a low haze of 0.97%, alongside a water contact angle of 153° and a sliding angle of 3°. The coating also exhibits distinct anti-reflection (an improvement of ~5.0% relative to the bare substrate) and self-cleaning properties. Furthermore, it demonstrates impressive robustness and durability, withstanding extreme conditions including cryogenic temperatures (−50 °C), hygrothermal environments, and long-term outdoor exposure. This work demonstrates the versatile potential of our strategy for fabricating highly transparent and superhydrophobic surfaces. Full article

This study focuses on polysaccharides from Cistanche deserticola and Cistanche tubulosa, medicinal plants renowned for their health benefits. The “water extraction and alcohol precipitation” method was used to obtain the crude polysaccharides of the wine-making residues of C. deserticola (CDP) and C. tubulosa (CTP), respectively. Then, ultrafiltration membrane (UFM), DEAE-52, and Sephadex-G75 or Smartdex-G100 gel chromatography were used to separate and purify the crude polysaccharides, yielding the homogeneous fractions CDP1-5-1, CDP2-2-2, CDP2-3-2, CTP1-5-1, and CTP1-5-3. Structural analysis was conducted by using Fourier-transform infrared spectroscopy (FT-IR), high-performance anion-exchange chromatography coupled with multi-angle laser light scattering and refractive index detection (HPAEC-MALLS-RID), gas chromatography–mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), congo red, and scanning electron microscopy (SEM). CDP1-5-1 was found to be an arabinan, while CDP2-2-2 and CDP2-3-2 were agavin-like fructans with different molecular weights. CTP1-5-1 and CTP1-5-3 were identified as a heteropolysaccharide and a galacturonan, respectively. Immunological evaluation using RAW264.7 macrophages showed that they all significantly enhanced nitric oxide (NO) production, with CDP1-5-1 exhibiting the most potent activity. The structural–activity relationship is summarized as follows: the arabinose was a key active unit with NO stimulatory effects. This research provides foundational data on the structure and immune-enhancing potential of Cistanche polysaccharides, supporting their further development and application. Full article

Lipid droplet (LD) coalescence is a critical cellular process that reshapes lipid storage, drives metabolic disease progression, and dictates the stability of LD-mimetic drug carriers. However, the rate-limiting step—fusion of the phospholipid monolayers surrounding neutral-lipid cores—remains poorly quantified compared to bilayer fusion. Here, we quantitatively determine the activation barrier for LD coalescence by tracking the kinetics in protein-free adiposome models. Using a multi-technique approach combining time-resolved dynamic light scattering and small-angle X-ray scattering, we reveal that monolayer fusion is the kinetic bottleneck. We demonstrate that lipid composition is a powerful regulator of this barrier: cone-shaped lipids (e.g., dioleoylphosphatidylethanolamine) lower the barrier and promote fusion, while phosphatidylcholine-rich monolayers enhance stability. A continuum fusion model, adapted for curved monolayers, explains these results through changes in spontaneous curvature, hydration repulsion, and stalk energetics. Our findings establish composition-dependent design rules for controlling LD dynamics in metabolic health and for engineering stable or triggerable lipid-based delivery vehicles. Full article

Nanocellulose has attracted significant attention in recent years due to its distinctive properties and vast potential applications across various fields. This study encompasses two distinct yet interconnected activities: the characterisation of eight different types of nanocellulose test materials, including crystalline, fibrillated, and bacterial nanocellulose, using a range of analytical techniques such as dynamic light scattering (DLS), asymmetric flow field-flow fractionation (AF4) coupled to multi-angle light scattering (MALS) and DLS, and transmission electron microscopy (TEM), and a focused case study employing a tiered analytical approach to identify bacterial nanocellulose in commercially available food products like pudding and drinks with nata de coco, SCOBY, and kombucha. The results demonstrate that different types of nanocellulose can be distinguished by their unique physicochemical properties using a combination of analytical techniques. This finding was used for the identification of bacterial nanocellulose in food products by combining pyGC-MS for cellulose identification, TEM for nanosize range determination, and XRD for crystallinity analysis to distinguish between bacterial and fibrillated nanocellulose. The study advances fundamental understanding of nanocellulose and provides tools to facilitate potential future regulatory compliance. Full article

The surface quality of optical components plays a decisive role in advanced imaging, precision manufacturing, and high-power laser systems, where even defects can induce abnormal scattering and degrade system performance. Addressing the limitations of conventional single-view inspection methods, this study presents a panoramic multi-angle scattered light field acquisition approach integrated with deep learning-based recognition. A hemispherical synchronous imaging system is designed to capture complete scattered distributions from surface defects in a single exposure, ensuring both structural consistency and angular completeness of the measured data. To enhance the interpretation of complex scattering patterns, we develop a tailored lightweight network, SFD-YOLO, which incorporates the PSimam attention module for improved salient feature extraction and the Efficient_Mamba_CSP module for robust global semantic modeling. Using a simulated dataset of multi-width scratch defects, the proposed method achieves high classification accuracy with strong generalization and computational efficiency. Compared to the baseline YOLOv11-cls, SFD-YOLO improves Top-1 accuracy from 92.5% to 95.6%, while reducing the parameter count from 1.54 M to 1.25 M and maintaining low computational cost (Flops 4.0G). These results confirm that panoramic multi-angle scattered imaging, coupled with advanced neural architectures, provides a powerful and practical framework for optical surface defect detection, offering valuable prospects for high-precision quality evaluation and intelligent defect inversion in optical inspection. Full article

Acute inflammation is frequently triggered by pathogen infections and contributes to host mortality. In this study, a new exopolysaccharide (ObEPS) was isolated from the moss endophyte Ovatospora brasiliensis and characterized for its structure and biological activity. Monosaccharide composition analysis revealed that ObEPS was mainly composed of galactose, glucose, mannose, and glucuronic acid. Multi-angle light scattering and conformation analysis showed a molar mass of 10⁵–10⁶ Da and a compact chain conformation. In vitro experiments showed that ObEPS markedly inhibited nitric oxide production and reduced pro-inflammatory cytokine expression in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. In a systemic Candida albicans infection model, ObEPS combined with fluconazole significantly reduced fungal colony-forming units (CFUs)/g kidney from 3.8 × 10⁵ to 0.1 × 10⁵, with the reduction of pro-inflammatory cytokine levels and tissue damage compared with the EPS-free groups suffering from C. albicans infection. Overall, these findings indicate that ObEPS has potent anti-inflammatory activity and may serve as a promising natural adjunct for mitigating infection-associated inflammatory damage. Full article

Segregative phase separation technology demonstrates substantial potential for precise molecular fractionation in food and biomaterial applications. The investigation elucidates the causal relationship between viscosity variations and phase separation dynamics, which govern molecular fractionation in GA/HPMC composite systems. By conducting a comparative analysis of two GA subtypes (CGA and SGA) and three HPMC grades with controlled viscosity gradients, we utilized gel permeation chromatography-multi-angle laser light scattering (GPC-MALLS) coupled with rheological characterization to elucidate the critical relationship between continuous phase viscosity and fractionation efficiency. Notably, increasing HPMC viscosity significantly intensified phase separation, resulting in selective enrichment of arabinogalactan-protein complexes: from 6.3% to 8.5% in CGA/HPMC systems and from 27.3% to 36.5% in SGA/HPMC systems. Further mechanistic investigation revealed that elevated HPMC viscosity enhances thermodynamic incompatibility while slowing interfacial mass transfer, synergistically driving component redistribution. These findings establish a quantitative viscosity–fractionation relationship, offering theoretical insights for optimizing GA/HPMC systems in emulsion stabilization, microencapsulation, and functional biopolymer purification via viscosity-mediated phase engineering. Full article

Adeno-associated virus (AAV) is a promising gene therapy vector due to its high transduction efficiency, low pathogenicity, low immunogenicity, and the ability to mediate the long-term stable expression of exogenous genes. The viral particle titer is an essential quality attribute of recombinant adeno-associated virus (rAAV) gene therapy products. Multiangle light scattering (MALS) is an important means of directly measuring the absolute molecular weight and distribution of macromolecular drugs. This study established and validated a method based on SEC-UV-MALS-RI tandem technology for accurately determining rAAV particle titers. The verification results indicated that the method exhibited good specificity, linearity, precision, accuracy, and durability. Several collaborative laboratories used this method to calibrate the standard substances needed for rAAV particle titer determination. The results suggested that combining the SEC-MALS method with standard substances enables the rapid and accurate measurement of the viral particle titers in rAAV gene therapy products. Full article

Land surface reflectance is a basic physical parameter in many quantitative remote sensing models. However, the existing reflectance conversion techniques for drone-based (or UAV-based) remote sensing need further improvement and optimization due to either cumbersome operational procedures or inaccurate results. To tackle this problem, this study proposes a novel method to mathematically implement the separation of direct and scattering radiation using a self-developed multi-angle light intensity device. The verification results from practical experiments demonstrate that the proposed method has strong adaptability, as it can obtain accurate surface reflectance even under complicated conditions where both illumination intensity and component change simultaneously. Among the six selected typical land cover types (i.e., lake water, slab stone, shrub, green grass, red grass, and dry grass), green grass has the highest error among the five multispectral bands with a mean absolute error (MAE) of 1.59%. For all land cover types, the highest MAE of 1.01% is found in the red band. The above validation results indicate that the proposed land surface reflectance conversion method has considerably high accuracy. Therefore, the study results may provide valuable references for quantitative remote sensing applications of drone-based multispectral data, as well as the design of future multispectral drones. Full article

In this study, a Bacillus velezensis SDU strain capable of producing poly-γ-glutamate (γ-PGA) was newly identified from the rhizosphere soil of Baimiao taro. The strain is a glutamate-independent strain and can produce polyglutamic acid in a culture medium completely free of glutamate. The hydrolyzed product of the polyglutamic acid produced is D-glutamic acid. The molecular weight of γ-PGA, estimated via the Mark–Houwink equation, was 1390 kDa. Furthermore, the molecular weight measured by Waters gel permeation chromatography with multi-angle laser light scattering (GPC–MALLS) was 1167 kDa. The production of γ-PGA and its antioxidant and tyrosine inhibition properties were investigated. The γ-PGA production reached 23.1 g/L, and the productivity was 0.77 g L⁻¹ h⁻¹. Specifically, γ-PGA exhibited superoxide anion (·O₂⁻) radical scavenging activity and tyrosinase inhibitory activity. This study introduces a promising strain and a highly efficient application method for γ-PGA, which can be broadly utilized in the pharmaceutical, food, and cosmetic industries. Full article

With the rise in global temperatures, it is of great significance to achieve rapid and accurate detection of greenhouse gases, such as carbon dioxide and methane. Raman spectroscopy not only overcomes the weakness of absorption spectroscopy in simultaneously measuring homonuclear diatomic molecules but also enables the simultaneous detection of multiple gases using a single-wavelength laser. However, due to the small Raman scattering cross-section and weak intensity of molecules, its application in gas detection is limited. To enhance the intensity of Raman scattering, this paper designs and constructs a multi-pass enhanced Raman spectroscopy setup. This study focuses on the effects of Raman scattering collection geometry, laser multi-pass patterns, and laser polarization relative to the Raman collection direction on signal intensity. Investigations into Raman scattering collection angles of 30°, 60°, and 90° reveal that the Raman scattering signal intensity increases as the collection angle decreases. Different laser multi-pass patterns also impact the signal, with the near-concentric linear multi-pass pattern found to collect more signals. To minimize the influence of excitation light on the signal, a side collection system is employed. Experiments show that the Raman scattering signal is stronger when the laser polarization is perpendicular to the collection direction. This study achieves overall system performance enhancement through coordinated optimization of multiple physical mechanisms, including Raman scattering collection geometry, laser multi-pass patterns, and laser polarization characteristics. The optimized setup was employed to characterize the laser power dependence for nitrogen, oxygen, and carbon dioxide detection. The results showed that the Raman scattering intensity varied linearly with the laser power of the gases, with linear fitting goodness R² values of 0.9902, 0.9848, and 0.9969, respectively. Finally, by configuring different concentrations of carbon dioxide gas using nitrogen, it was found that the Raman scattering intensity varied linearly with the concentration of carbon dioxide, with a linear fitting goodness R² of 0.9812. The system achieves a CO₂ detection limit of 500 ppm at 200 s integration time, meeting the requirements for greenhouse gas emission monitoring applications. Full article

Accurate fruit detection is of great importance for yield assessment, timely harvesting, and orchard management strategy optimization in precision agriculture. Traditional optical imaging methods are limited by lighting and meteorological conditions, making it difficult to obtain stable, high-quality data. Therefore, this study utilizes near-field millimeter-wave MIMO-SAR (Multiple Input Multiple Output Synthetic Aperture Radar) technology, which is capable of all-day and all-weather imaging, to perform high-precision detection of apple targets in orchards. This paper first constructs a near-field millimeter-wave MIMO-SAR imaging system and performs multi-angle imaging on real fruit tree samples, obtaining about 150 sets of SAR-optical paired data, covering approximately 2000 accurately annotated apple targets. Addressing challenges such as weak scattering, low texture contrast, and complex backgrounds in SAR images, we propose an innovative detection framework integrating Dynamic Spatial Pyramid Pooling (DSPP), Recursive Feature Fusion Network (RFN), and Context-Aware Feature Enhancement (CAFE) modules. DSPP employs a learnable adaptive mechanism to dynamically adjust multi-scale feature representations, enhancing sensitivity to apple targets of varying sizes and distributions; RFN uses a multi-round iterative feature fusion strategy to gradually refine semantic consistency and stability, improving the robustness of feature representation under weak texture and high noise scenarios; and the CAFE module, based on attention mechanisms, explicitly models global and local associations, fully utilizing the scene context in texture-poor SAR conditions to enhance the discriminability of apple targets. Experimental results show that the proposed method achieves significant improvements in average precision (AP), recall rate, and F1 score on the constructed near-field millimeter-wave SAR apple dataset compared to various classic and mainstream detectors. Ablation studies confirm the synergistic effect of DSPP, RFN, and CAFE. Qualitative analysis demonstrates that the detection framework proposed in this paper can still stably locate apple targets even under conditions of leaf occlusion, complex backgrounds, and weak scattering. This research provides a beneficial reference and technical basis for using SAR data in fruit detection and yield estimation in precision agriculture. Full article