Search Results (240)

Quinoa protein isolate (QPI) and sodium alginate (SA) have excellent biocompatibility and functional properties, making them promising candidates for food-grade delivery systems. In this study, we developed, for the first time, a QPI/SA complex-stabilized Pickering emulsion for curcumin encapsulation. The coacervation behavior of QPI and SA was investigated from pH 1.6 to 7.5, and the structural and interfacial characteristics of the complexes were analyzed using zeta potential measurements, Fourier-transform infrared spectroscopy, scanning electron microscopy, and contact angle analysis. The results showed that the formation of QPI/SA complexes was primarily driven by electrostatic interactions, hydrogen bonding, and hydrophobic interactions, with enhanced amphiphilicity observed under optimal conditions (QPI/SA = 5:1, pH 5). The QPI/SA-stabilized Pickering emulsions demonstrated excellent emulsification performance and storage stability, maintaining an emulsification index above 90% after 7 d when prepared with 60% oil phase. In vitro digestion studies revealed stage-specific curcumin release, with sustained release in simulated gastric fluid (21.13%) and enhanced release in intestinal fluid (88.21%). Cytotoxicity assays using HeLa cells confirmed the biocompatibility of QPI/SA complexes (≤500 μg/mL), while curcumin-loaded emulsions exhibited dose-dependent anticancer activity. These findings suggest that QPI/SA holds significant potential for applications in functional foods and oral delivery systems. Full article

The acute rise in temperature due to marine heatwaves has a strong impact on marine phytoplankton. To determine whether these effects depend on ambient temperature and cell size, we acclimated two diatom species, smaller Thalassiosira pseudonana (Hasle and Heimdal, 1970) and larger Thalassiosira rotula (Meunier, 1910), at low (LAT), medium (MAT) and high ambient temperatures (HAT) and examined their physiochemical and transcriptional responses to temperature rise (AT + 6 °C). The specific growth rate (µ) of smaller cells was increased by 32% due to temperature rise at LAT, but decreased by 13% at HAT, with the stimulatory and inhibitory extent being ~50% less than that of larger cells. At LAT, chlorophyll a (Chl a), carotenoid (Car) and carbon (POC) contents were increased in smaller cells due to temperature rise, but were decreased in larger cells; at HAT, Chl a and Car were increased in both smaller and larger cells and POC was increased in only smaller cells. At LAT, temperature rise led to a disproportionate increase in photosynthesis and dark respiration, resulting in an increase in carbon utilization efficiency (CUE) in smaller cells and a decrease in CUE in larger cells; at HAT, there was a decrease in CUE in both the smaller and larger cells, but to a lesser extent in the former than in the latter. Our results also show that smaller cells cope with the acute temperature rise mainly by strengthening their enzyme activity (e.g., the antioxidant system) and conservatively regulating their metabolism, while larger cells mainly regulate their photosynthetic and central carbon metabolism. Moreover, larger cells can outperform their smaller counterparts when the temperature rise occurs at lower ambient temperature. Full article

Cancer is hallmarked by uncontrolled cell proliferation and enhanced cell survival, driven by a complex interplay of factors—including genetic and epigenetic changes—that disrupt metabolic and signaling pathways and impair organelle function. While the roles of mitochondria and the endoplasmic reticulum in cancer are widely recognized, emerging research is now drawing attention to the involvement of peroxisomes in tumor biology. Peroxisomes are essential for lipid metabolism, including fatty acid α- and β-oxidation, the synthesis of docosahexaenoic acid, bile acids, and ether lipids, as well as maintaining redox balance. Despite their critical functions, the role of peroxisomes in oncogenesis remains inadequately explored. Prostate cancer (PCa), the second most common cancer in men worldwide, exhibits a unique metabolic profile compared to other solid tumors. In contrast to the glycolysis-driven Warburg effect, primary PCa relies primarily on lipogenesis and oxidative phosphorylation. Peroxisomes are intricately involved in the metabolic adaptations of PCa, influencing both disease progression and therapy resistance. Key alterations in peroxisomal activity in PCa include the increased oxidation of branched-chain fatty acids, upregulation of α-methylacyl coenzyme A racemase (a prominent PCa biomarker), and downregulation of 1-alkyl-glycerone-3-phosphate synthase and catalase. This review critically examines the role of peroxisomes in PCa metabolism, progression, and therapeutic response, exploring their potential as biomarkers and targets for therapy. We also consider their relationship with androgen receptor signaling. A deeper understanding of peroxisome biology in PCa could pave the way for new therapies to improve patient outcomes. Full article

Accurate prediction of natural gas production is of great significance for optimizing development strategies, simplifying production management, and promoting decision-making. This paper utilizes partial differentiation to effectively capture the spatiotemporal characteristics of natural gas data and the advantages of grey prediction models. By introducing the fractional damping accumulation operator, a new fractional order partial grey prediction model is established. The new model utilizes partial capture of details and features in the data, improves model accuracy through fractional order accumulation, and extends the metadata of the classic grey prediction model from time series to matrix series, effectively compensating for the phenomenon of inaccurate results caused by data fluctuations in the model. Meanwhile, the principle of data accumulation is effectively expressed in matrix form, and the least squares method is used to estimate the parameters of the model. The time response equation of the model is obtained through multiplication transformation, and the modelling steps are elaborated in detail. Finally, the new model is applied to the prediction of natural gas production in Qinghai Province, China, selecting energy production related to natural gas production, including raw coal production, oil production, and electricity generation, as relevant variables. To verify the effectiveness of the new model, we started by selecting the number of relevant variables, divided them into three categories for analysis based on the number of relevant variables, and compared them with five other grey prediction models. The results showed that in the seven simulation experiments of the three types of experiments, the average relative error of the new model was less than 2%, indicating that the new model has strong stability. When selecting the other three types of energy production as related variables, the best effect was achieved with an average relative error of 0.3821%, and the natural gas production for the next nine months was successfully predicted. Full article

Financial text analytics methods are employed to examine social media comments, allowing investors to gain insights and make informed financial decisions. Some emojis within these comments often convey diverse semantics, emotions, or intentions depending on the context. However, traditional financial text analysis methods relying on public annotations struggle to identify implicit expressions, leading to suboptimal performance. To address this challenge, this paper proposes an implicit expression recognition model of emojis in social media comments (IER-SMCEM). Firstly, IER-SMCEM innovative designs a data enhancement method based on the implicit expression of emoji. This method expands the pure text financial sentiment analysis dataset into the implicit expression dataset of emoji by homophonic replacement. Secondly, IER-SMCEM designs a prompt learning template to identify the implicit expression of emoji. Through hand-designed templates, large-scale language models can predict the true meaning that emojis are most likely to express. Finally, IER-SMCEM recovers implicit expression by choosing the predictions of models. Thus, the downstream financial sentiment analysis model can more precisely realize the sentiment recognition of the text with emoji by the recovered text. The experimental results indicate that IER-SMCEM achieves a 98.03% accuracy in semantically recovering implicit expressions within financial texts. In the task of financial sentiment analysis, the sentiment analysis model achieves the highest accuracy of 3.99% after restoring the true implied expression of the texts. Therefore, the model can be effectively applied to sentiment analysis or quantitative analysis. Full article

Xylanases, important enzymes in the food industry, have severely limited use in industrial applications due to insufficient thermal stability. This study focused on improving the thermostability of XynASP, a glycoside hydrolase family 11 (GH11) xylanase from Aspergillus saccharolyticus JOP 1030-1, through modular assembly and rational mutagenesis. By aligning XynASP with nine thermostable GH11 homologs, six variable structural modules (β1, β3, β6, β7, α1, β14) and eight non-conserved residues were identified. Six chimeras (Z1, Z2, Z3, Z4, Z5, Z6) and eight single mutants (S131T, Y133T, A137G, A144T, T147Y, A156R, V198M, and Y204Q) were constructed. Among these, the β3-module-substituted chimera Z2 exhibited a 15.4-fold extended half-life at 45 °C compared to wild-type XynASP. Single-point mutagenesis revealed that V198M showed the highest residual activity after thermal treatment. To further optimize stability, combinatorial mutagenesis was performed: the double mutant A144T/V198M demonstrated a 4.3-fold longer half-life at 50 °C. Combining Z2 with the A144T/V198M mutations yielded the chimeric ZM, which demonstrated a 26.5-fold increase in half-life at 50 °C and a 5.5-fold improvement in catalytic efficiency (197.4 U/mg) compared to wild-type XynASP. Structural analysis and molecular dynamics simulations showed that increased hydrophobic interactions at both the N- and C-termini improved the structural stability of chimeric ZM, while increasing the flexibility of the thumb can offset the negative impact on catalytic activity during thermal stability modification of GH11 xylanase. This study further confirmed that modular assembly is an effective approach for obtaining high-activity, heat-resistant xylanases. This study also notably deepened our understanding of the thermal stability mechanisms of xylanases. Full article

Poly(butylene adipate-co-terephthalate) (PBAT) is a promising biodegradable polymer with balanced mechanical properties and excellent degradability, making it an ideal material to reduce plastic pollution. However, its susceptibility to ultraviolet (UV) degradation, due to photosensitive aromatic rings and carbonyl groups in its structure, limits its use in outdoor settings like mulch films. Conventional methods of incorporating small-molecule UV stabilizers face challenges such as poor compatibility, uneven dispersion, and migration under environmental conditions, reducing their effectiveness over time. This study developed a novel strategy to enhance PBAT’s UV resistance by chemically bonding UV-stabilizing moieties directly into its molecular chains to address these limitations. A novel UV absorber containing a polymerizable group was synthesized and copolymerized with PBAT’s main chain, creating an intrinsically UV-stable PBAT. The UV-stable PBAT was evaluated for UV resistance, mechanical performance, and durability through accelerated aging and solvent extraction tests. The results demonstrated that UV-stable PBAT exhibited exceptional light stabilization effects, with no detectable UV absorber leaching in ethanol even after 114 h, whereas PBAT blends lost nearly 90% of UV-0 within 24 h. Furthermore, UV-stable PBAT maintained 67.1% tensile strength and 48.8% elongation at break after aging, which exhibited the best mechanical retention performance. Even when subjected to solvent extraction, the 42.6% tensile strength retention outperformed the PBAT blends. This innovative chemical modification overcomes the limitations of additive-based stabilization, offering improved durability, compatibility, and performance in outdoor applications. Our research provides key insights into the fundamental properties of PBAT films for UV resistance, demonstrating their potential for use in demanding fields such as agricultural films. Full article

(1) Background: In the era of generative AI (GenAI), assessing AI literacy is essential for understanding how effectively non-expert users can interact with AI. However, existing assessment tools primarily focus on users’ understanding of AI principles or rely on self-reported scales, neglecting critical thinking and actual interaction capabilities. To address this gap, this study aims to design and validate evaluation indicators targeting the behavioral process of human–GenAI interactions and analyze the impact of critical thinking. (2) Methods: Grounded in information literacy and critical thinking frameworks, this study operationalized human–AI interaction capabilities into behavioral indicators and rubrics through observation, surveys, and pilot studies. Data were collected from 121 undergraduates completing two real-world tasks with GenAI, and their interaction processes were documented and evaluated. (3) Results: The indicators showed acceptable inter-rater and internal consistency reliability. Exploratory and Confirmatory Factor Analysis confirmed a three-dimensional structure. Further analysis showed that interaction capabilities varied across gender, academic background, AIGC use frequency, critical thinking disposition levels, and question chain logic. (4) Conclusions: The developed evaluation indicators are reliable and valid. Further analysis reveals that a high critical thinking disposition can offset the disadvantage of lower usage frequency. This highlights the significance of critical thinking in enhancing human–GenAI interaction capabilities. Full article

Soybean (Glycine max L.) is a vital grain and oil crop, serving as a primary source of edible oil, plant-based protein, and livestock feed. Its production is crucial for ensuring global food security. However, soybean yields are severely impacted by various diseases, and the development of disease-resistant cultivars remains the most sustainable strategy for mitigating these losses. While stable genetic transformation is a common approach for studying gene function, virus-induced gene silencing (VIGS) offers a rapid and powerful alternative for functional genomics, enabling efficient screening of candidate genes. Nevertheless, the application of VIGS in soybean has been relatively limited. In this study, we established a tobacco rattle virus (TRV)-based VIGS system for soybean, utilizing Agrobacterium tumefaciens-mediated infection. The TRV vector was delivered through cotyledon nodes, facilitating systemic spread and effective silencing of endogenous genes. Our results demonstrate that this TRV–VIGS system efficiently silences target genes in soybean, inducing significant phenotypic changes with a silencing efficiency ranging from 65% to 95%. Key genes, including phytoene desaturase (GmPDS), the rust resistance gene GmRpp6907, and the defense-related gene GmRPT4, were successfully silenced, confirming the system’s robustness. This work establishes a highly efficient TRV–VIGS platform for rapid gene function validation in soybean, providing a valuable tool for future genetic and disease resistance research. Full article

This study explored how potted treatments (with and without Scleroderma bovista inoculation) shape rhizosphere microbial diversity in hazel across five soils using split-root cultivation. Three treatments (control, split-root, split-root with S. bovista) were analyzed for root growth and microbial dynamics. S. bovista inoculation consistently enhanced root parameters (number, tips) in all soils. Potted treatments (with and without S. bovista inoculation) altered microbial features (OTU/ASV), with only 0.9–3.3% of features remaining unchanged. At the class level, potting increased Agaricomycetes abundance while reducing Sordariomycetes, a trend amplified by S. bovista. Potting decreased species richness estimates (ACE and Chao1), while both treatments lowered diversity index (Shannon index). Potted treatments without S. bovista inoculation drove stronger shifts in species composition than inoculation. Findings reveal potting and S. bovista synergistically recruit symbiotic fungi via root exudates, establishing disease-suppressive communities that selectively inhibit pathotrophic fungi (particularly plant pathogen Coniothyrium and fungal parasite Cladobotryum) while roughly maintaining non-pathogenic saprotrophic microbes essential for organic matter decomposition. This work provides insights for optimizing hazel orchard management and ectomycorrhizal agent development. Full article

Rural tourism has become a key driver of rural revitalization in China, contributing to poverty alleviation while also irreversibly altering the spatial evolution of rural settlements. In the ecologically fragile regions of northwest China, the rapid expansion of rural tourism destinations has raised ecological concerns, particularly regarding land resource utilization. Therefore, it is crucial to examine the phenomenon of industrial agglomeration in the evolution of rural tourism within the context of tourism-driven poverty alleviation. This study uses Lanzhou City as a case study and employs nearest neighbor analysis and kernel density estimation to analyze the spatial agglomeration patterns of rural tourism destinations, focusing on agglomeration forms, scales, and patterns. Additionally, it explores the spatial coupling distribution between agglomeration levels and influencing factors. The results show that from 1987 to 2022, the development of rural tourism destinations in Lanzhou City has progressed through several stages, from initial emergence to rapid growth. The form of industrial agglomeration has shifted from a dispersed to a clustered distribution, gradually expanding from urban centers to peripheral areas. The spatial agglomeration follows a multi-core hierarchical point-axial diffusion model, forming multiple core and sub-core agglomeration zones of varying scales. This transformation is primarily driven by geographical factors, transportation accessibility, and the presence of high-quality tourist attractions. However, a comparison of land use changes and ecological vulnerability indices over multiple periods indicates that the industrial agglomeration of rural tourism has led to irregular land use patterns and ecosystem instability. Finally, based on the complex relationship between rural tourism development, industrial agglomeration, and ecological sustainability, this study proposes strategies for the development of rural tourism in Lanzhou City, with the aim of providing valuable insights for the development of rural tourism in ecologically fragile regions of China. Full article

China is one of the countries most seriously affected by soil salinization, while the impact of salt-controlled irrigation on the relationship between soil dissolved organic matter (DOM) and microbial in farmland affected by salinization remains largely unexplored. We conducted a comprehensive survey of soil DOM and a microbial survey of Ordos’s salinized farmland in China before and after salt-controlled irrigation. Our findings reveal a reduction of 18.4 mg/L in surface soil (0–10 cm) DOC following irrigation, whereas the subsurface soil (20–40 cm) DOC increased by 20.7 mg/L. Moreover, irrigation led to an increase in the aromaticity and humification of the soil, with the salt content of the subsurface soil rising from 2.7 to 3.7 mg/g. Additionally, the total dissolved solids (TDS) in the drained water were 2463 mg/L higher than in the irrigation water (1416.3 mg/L). This suggests that the DOM and salts from the surface soil either leached into deeper layers or were lost via runoff. Furthermore, SEM analysis and a Mantel test revealed that microbial composition significantly influenced soil DOM contents, especially increased levels of Marmoricola and MND1, which are associated with decomposing organic matter and may contribute to the leaching of soil DOM in deep layers following irrigation. Full article

The concentrations of dissolved N₂O in river systems at the basin scale exhibit significant spatial and temporal variability, particularly under diverse landscape conditions. This study focused on a temperate basin—the Yiluo River (YLR) basin in China—to investigate the variations in dissolved N₂O concentrations and the indirect emission factors (EF_5r) between the dry and wet seasons. The differences among tributaries were analyzed to assess the impact of land use types. The findings revealed that N₂O concentrations and saturation levels were lower during the wet season in both the main streams and tributaries. In the dry season, the N₂O concentrations were strongly correlated with NH₄⁺-N, NO₃⁻-N, and oxidation–reduction potential (ORP) (R² = 0.743, p < 0.001), while in the wet season, the N₂O concentrations were correlated with dissolved phosphorus (DP), water temperature (Tw), NH₄⁺-N, and DOC (R² = 0.640, p < 0.001). Impervious land was identified as the primary source of nitrogen in both seasons, rather than cropland. Natural land, particularly shrubland, demonstrated a notable mitigating effect on N₂O accumulation and played a significant role in reducing NO₃⁻-N levels. The YLR basin exhibited lower EF_5r values (0.005–0.052%) compared to the default value recommended by the IPCC, with a significant decrease observed during the wet season (p < 0.001). Data analysis indicated that nutrient dynamics, particularly NO₃⁻-N, the ratio of dissolved organic carbon to NO₃⁻-N (DOC/NO₃⁻-N), and the ratio of NO₃⁻-N to DP (NO₃⁻-N/DP), were significantly correlated with EF_5r. These results underscore the need to re-evaluate regional N₂O emission potentials and provide new insights into mitigating N₂O emissions through strategic land use management. Full article

Bone tissue injuries are a significant health risk, and their repair is challenging. While various materials have potential for bone repair, issues like sourcing and immune rejection limit their use. Marine-derived collagen, abundant and free from religious and disease transmission concerns, is a promising biomaterial in bone tissue engineering. Cross-linking modification can enhance its mechanical properties and degradation rate, making it more suitable for bone repair. However, detailed analysis of cross-linking methods, property changes post-cross-linking, and their impact on bone repair is needed. This review examines marine collagen’s modification methods, improved characteristics, and potential in bone tissue repair, providing a foundation for its effective use in bone tissue engineering. Full article

Anoectochilus formosanus is a rare medicinal plant with anti-inflammatory, antioxidant, hepatoprotective, and immunomodulatory properties. Its morphological growth and accumulation of medicinal compounds are strongly influenced by environmental factors such as light intensity. To investigate the physiological and ecological responses of Anoectochilus formosanus to varying light intensities, we examined physiological, morphological, and growth parameters across different growth stages under five different light intensities. Correlation, plasticity, and principal component analysis (PCA) were performed. The results showed that high and low light intensities altered physiological and biochemical indicators at different stages. Leaf area, fresh weight, dry weight, stem thickness, and non-photochemical quenching (NPQ) increased with increasing light intensity, whereas chlorophyll fluorescence parameters (Fv, Fm, and Fv/Fm) and flavonoid content decreased, reflecting reduced light capture and consumption under high light intensities. The phenotypic plasticity index of the morphological traits (<0.5) was lower than that of the photosynthetic physiological parameters (>0.5), indicating a greater plasticity of the photosynthetic traits. Biomass indicators—leaf area ratio and relative growth rate—were strongly correlated, driving the response to light intensity. Growth and biomass allocation peaked at moderate light intensity (70 μmol·m⁻²·s⁻¹). These findings highlight the conservative strategy employed by A. formosanus for slow carbon use under low-light conditions, and the adventurous strategy employed for rapid carbon use under strong light, offering insights into efficient cultivation practices. Full article