Search Results (18,583)

The shortage of protein-rich foods is a major challenge due to the rapid growth of the world’s population. For this reason, efforts are being made to achieve sustainability in the food system to produce nutritious foods with better qualities. The present study aimed to utilize a combination of widely consumed legumes with nutritional properties—such as lentils, chickpeas, and beans—considering their physicochemical and functional characteristics, to produce tempeh as a model. A simple mixture design was employed to develop a legume-based product through the production of fermented flour using Rhizopus oligosporus ATCC 22959. For this purpose, proximate composition, water absorption index (WAI), pH, phenolic content, and antioxidant capacity, via the DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)) radicals, were determined in the raw legumes. Optimal fermentation conditions were determined through digital image analysis, and fermentations were carried out according to the design. The crude and soluble protein content, phenolic content, and DPPH of the fermented samples were determined, and a statistical optimization was performed by maximizing each variable. Through optimization, it was found that a formulation of 80.81% lentil and 19.19% chickpea presented the best desirability (D = 0.75) according to the criteria mentioned above. These results were also compared with those obtained from the preparation of an original soy tempeh using the microorganism Rhizopus oligosporus; it was found that the protein differences between the original tempeh and the one made from the legume blend were 19 g/100 g dry matter for the original tempeh and 27.5 g/100 g dry matter for the one made with the legume blend, demonstrating that the combination of legumes exerts a favorable interaction within the mixture model on the physicochemical properties of tempeh and could represent significant potential for the production of flours applicable to the development of food products as part of alternative protein sources. Full article

The present study investigates the physicochemical behavior of the first-line anti-tuberculosis drugs isoniazid (INH) and ethambutol, in the form of dihydrochloride (E·(HCl)₂), in aqueous solutions containing the synthetic macrocyclic resorcinarene, C-tetra(propyl)resorcin[⁴]tetrasulfonate (Na₄PRA) at 298.15 K. Taylor dispersion experiments were conducted to determine the ternary diffusion coefficients of these systems, offering valuable insights into their transport properties. Non-zero cross-diffusion coefficients (D₁₂ and D₂₁) demonstrate significant coupled transport, collectively indicating interactions between these antibiotics and the resorcinarene host. This behavior is highly consistent with the formation of a host–guest complex. These diffusion measurements were complemented by NMR spectroscopy, which confirmed the formation of host–guest complexes between the respective drugs and this resorcinarene, Na₄PRA. Full article

Objectives: Critical-sized bone defects continue to represent a substantial challenge in orthopedic clinical practice. Decellularized bone matrix (DBM) possesses favorable osteoconductive properties due to its retention of native extracellular matrix architecture and collagen components. However, its limited osteogenic bioactivity restricts its application in complex bone defect repair. This study aimed to construct a dendritic mesoporous silica (DMSN)-modified DBM composite scaffold loaded with teriparatide (DBM-DMSN@TPTD) and to systematically evaluate its physicochemical properties, drug release behavior, biocompatibility, and osteogenic differentiation-promoting capacity. Methods: A DBM scaffold was prepared from bovine femoral cancellous bone via a combined freeze–thaw and chemical detergent decellularization method. DMSNs were synthesized through a sol–gel method, amine-functionalized with APTES, and covalently grafted onto the DBM surface via EDC/NHS crosslinking. Teriparatide was loaded onto the composite scaffolds at three concentrations (1, 10, and 100 nmol/L). The scaffolds were characterized via SEM, TEM, BET, EDS and XPS. Decellularization efficacy was assessed by DAPI staining and nucleic acid quantification. Drug release behavior was evaluated through in vitro release studies, while biocompatibility and osteogenic differentiation of rat BMSCs were examined using Live/Dead staining, phalloidin/DAPI cytoskeletal staining, CCK-8 assays, ALP staining, and RUNX2/OCN immunofluorescence. Results: DMSNs demonstrated a dendritic mesoporous architecture, featuring a specific surface area of 390.44 ± 1.78 m²/g and pore diameters within the range of 15–20 nm. DBM showed effective removal of immunogenicity, with well-preserved collagen architecture. Drug release displayed a biphasic pattern, with 56.03% released within the first 72 h and 83.23% by day 16. None of the tested scaffolds showed obvious cytotoxicity under the experimental conditions. The DBM-DMSN@TPTD-M group (10 nmol/L) produced the strongest effects on BMSC proliferation and osteogenic differentiation, as indicated by the highest ALP activity and elevated RUNX2 and OCN expression (p < 0.05). Conclusions: The DBM-DMSN@TPTD scaffold offers a native bone microenvironment, sustained drug release, and osteogenic activity in vitro. These features may support BMSC proliferation and osteogenic differentiation. Accordingly, this scaffold warrants further investigation as a potential strategy for bone defect repair. Full article

Korean pine (Pinus koraiensis) nut-timber plantations are important for both timber and seed production, yet optimal water and fertilizer management for mature cone-bearing stands remains poorly understood. A two-year field experiment was conducted to evaluate the effects of three fertilization levels (F1, F2, and F3, corresponding to N:P₂O₅:K₂O application rates of 50:75:25, 100:150:50, and 150:225:75 kg ha⁻¹, respectively) and three soil moisture regimes corresponding to 80%, 60%, and 40% of field capacity (W1, W2, and W3, respectively) on tree growth, cone yield, and soil physicochemical properties in approximately 35-year-old Korean pine plantations established on Albeluvisol at Maoer Mountain, northeastern China. Tree growth and cone yield generally followed the order F2 > F3 > F1 and W2 > W1 > W3, with F2W2 (N:P₂O₅:K₂O = 100:150:50kg ha⁻¹ and 60% of field capacity) consistently producing the best performance. Compared with the control (CK, no fertilizer application, rainfed under natural ambient conditions), F2W2 increased height, diameter, and crown width increments by 46.2%, 71.4%, and 65.6%, respectively, in 2023. Per-tree cone number, total cone mass, and total pine nut mass increased progressively across years, reaching increases of 88.5%, 100.6%, and 132.4%, respectively, in 2024. In contrast, thousand-seed weight showed relatively small changes and a delayed water–fertilizer interaction. Water–fertilizer coupling significantly altered soil physicochemical properties by reducing soil pH under the optimal treatment, while also regulating inorganic nitrogen availability and soil nutrient distribution. Nitrate nitrogen was highest under W2, whereas ammonium nitrogen peaked under W1. Total nitrogen was highest under F3W1, while available phosphorus and potassium accumulated under high fertilization combined with non-optimal soil moisture, but were lowest under F2W2, indicating enhanced nutrient uptake under the optimal treatment. Cluster analysis showed that nitrate nitrogen was positively associated with growth and yield variables. Overall, F2W2 provided the most favorable balance between stand productivity and soil nutrient status, representing an effective water–fertilizer management strategy for mature Korean pine nut-timber plantations on Albeluvisol. These findings provide a scientific basis for precision water and nutrient management in northeastern China. Full article

The biological fate of lipid-based nanocarriers (LBNs) is shaped at the interface. Whereas core architecture governs cargo loading, protection, and baseline release, surface architecture mediates the carrier’s initial interactions with proteins, cells, extracellular matrices, and tissue barriers, thereby influencing colloidal stability, immune recognition, targeting, biodistribution, barrier transport, and release initiation. Layer-by-layer (LbL) engineering provides a modular strategy for programming this interface through sequentially assembled coatings in which functional components are spatially separated yet mechanistically coordinated. By integrating polymers, biomolecules—including peptides and nucleic acids—and stimuli-responsive materials, LbL systems can decouple functions that are difficult to regulate independently within conventional single-layer or compositionally mixed surface architectures. This review examines recent advances in LbL-engineered LBNs (LbL-LBNs), focusing on how multilayer surface architecture reshapes physicochemical properties, cargo localization and release, biological identity, cellular interactions, and transport across physiological barriers. Particular attention is given to the multilayer interface as a dynamic biointerfacial bridge between a cargo-specific core architecture and the surrounding biological environment, including its capacity for stimuli-responsive switching in pathological microenvironments. The discussion further extends to biomimetic hybrid interfaces and establishes a framework for translating hierarchical surface architectures into reproducible, clinically tractable platforms for precision therapeutic delivery. Full article

Cyanobacteria are promising platforms for bioenergy, carbon sequestration, and bioproduct synthesis, but their photosynthetic efficiency is limited by suboptimal light utilization, electron transport constraints, and environmental stress. Titanium dioxide nanoparticles (n-TiO₂) have emerged as powerful photocatalytic materials that can enhance light absorption, modulate electron transport, and influence the redox balance in biological systems. This review advances the concept of photocatalytic-biological coupling, in which n-TiO₂ functions as artificial light amplifiers that augment cyanobacterial photosynthesis. Current evidence on the physicochemical properties of n-TiO₂, their interactions with cyanobacterial cells, and their effects on photosystems, electron transport chains, and downstream metabolic processes is examined. Particular emphasis is placed on the integration of photophysical and biological mechanisms, including reactive oxygen species (ROS)-mediated signaling, proton motive force (PMF) enhancement, and adenosine triphosphate (ATP) synthesis. Emerging approaches, including nano–bio interface engineering, environmental biotechnology applications, and artificial intelligence-guided optimization, are highlighted. By bridging photophysics, cellular bioenergetics, and computational design within a unified mechanistic framework, this review establishes the scientific foundation needed to translate photocatalytic–biological coupling into scalable and biotechnologically deployable nano-enabled photosynthetic systems. Full article

Ethylene accumulation accelerates the ripening of climacteric fruits and may impair their postharvest quality. This study evaluated biochar produced from spent tea leaves and enclosed in cellulose sachets as a material for reducing ethylene concentration and preserving tomato quality during storage. The biochar was produced by pyrolyzing spent black tea leaves at 400 °C for 10 min. Tomatoes were stored for 18 days at 21 °C in sealed glass chambers containing sachets with 1, 2, 3, 4, 5, 7.5, or 10 g of biochar, with a treatment without biochar serving as the control. After 6, 12, and 18 days, ethylene concentration, microbiological quality, and selected physicochemical and antioxidant properties were evaluated. Biochar reduced ethylene accumulation in a mass-dependent manner, with the most pronounced effects generally observed in the 5–10 g range. The 10 g treatment reduced ethylene concentration by 41.1%, 37.8%, and 40.3% relative to the control after 6, 12, and 18 days, respectively. The lowest counts of aerobic mesophilic microorganisms, yeasts, and molds were generally observed in the 7.5 and 10 g treatments. The application of at least 5 g of biochar most effectively limited firmness loss; after 18 days, firmness ranged from 1.77 to 1.80 kgf in the 5–10 g treatments, compared with 1.00 kgf in the control. Higher biochar masses also favored the retention of titratable acidity, total phenolic content, and antioxidant activity measured using the ABTS and FRAP assays. Overall, the beneficial effects on postharvest storage conditions and tomato quality became more evident with increasing biochar mass, particularly between 5 and 10 g. Sachets containing 7.5–10 g of spent-tea-leaf biochar showed the greatest potential as a simple passive system for controlling ethylene and preserving tomato quality. This approach combines waste valorization with the potential reduction in postharvest losses, supporting circular economy principles and Sustainable Development Goal 12 (SDG 12). Full article

Dissolving microneedles offers a minimally invasive approach for transdermal drug delivery by facilitating drug transport across the stratum corneum while overcoming several limitations associated with conventional routes of administration. Benzhydroxamic acid has demonstrated biochemical and computational evidence associated with inflammatory and pain-related pathways; however, its incorporation into a dissolving microneedle platform has not been extensively explored.This study aimed to fabricate and characterize benzhydroxamic acid-loaded dissolving microneedles using a 3D-printing-assisted mold fabrication approach for transdermal drug delivery. A stereolithography-based 3D-printed master mold was used to prepare a reverse polydimethylsiloxane mold. Benzhydroxamic acid-loaded dissolving microneedles were fabricated using a PVA/PVP polymeric matrix and evaluated for their physicochemical, mechanical, insertional, and drug-delivery characteristics. The developed microneedles exhibited shear-thinning behavior, uniform morphology, and satisfactory mechanical properties, with a compression force of 3.5 ± 0.01 N/needle and tensile strength of 3.84 ± 0.21 MPa. The formulation demonstrated a drug-loading efficiency of 94.6 ± 0.35% and effective insertion into the Parafilm^® M skin-simulant model. In vitro drug release reached 97.24% over 24 h, while ex vivo skin permeation reached 94.83% over 24 h. FTIR and XRD analyses indicated successful incorporation of benzhydroxamic acid into the PVA/PVP matrix without major evidence of drug–polymer incompatibility. The findings demonstrate the feasibility of incorporating benzhydroxamic acid into a PVA/PVP dissolving microneedle platform using a 3D-printing-assisted mold fabrication approach. The developed system exhibited suitable physicochemical and mechanical characteristics, efficient drug loading, effective insertion, and satisfactory in vitro and ex vivo drug-delivery performance, supporting its potential as a transdermal drug delivery platform. Full article

Common reed (Phragmites australis) is a native dominant plant in many coastal wetlands. To determine how rhizosphere effects and soil depth shape microbial communities, we sampled the rhizosphere and three bulk-soil layers (0–15, 15–30, and 30–45 cm) in a monodominant common-reed stand in a coastal salt marsh. Soil physicochemical properties and bacterial and fungal α-diversity, community composition, and assembly processes were evaluated using one-way ANOVA, principal coordinates analysis (PCoA), permutational multivariate analysis of variance (PERMANOVA), neutral community models, and phylogenetic null models. Rhizosphere pH was lower than that of 0–15 cm bulk soil (mean 8.434 vs. 8.712) but remained alkaline; soil organic matter, total nitrogen, hydrolyzable nitrogen, and total phosphorus were greatest in the rhizosphere. Neither bacterial nor fungal richness or Shannon diversity differed significantly among compartments (p > 0.05); fungal Shannon means ranged from 2.083 to 3.077, with relatively higher Bacteroidota and lower Acidobacteriota abundance in the rhizosphere. Fungal composition did not differ significantly (pseudo-F = 0.609, R² = 0.102, p = 0.9112), although Mucoromycota and Rozellomycota were relatively more abundant in the rhizosphere. Phylogenetic null models indicated predominantly deterministic bacterial assembly, with 10% dispersal limitation in the 15–30 cm layer. Fungal assembly was predominantly stochastic in bulk soils, whereas the rhizosphere was an exception: heterogeneous selection accounted for 60% of pairwise comparisons and median βNTI exceeded +2. The Mantel test identified only the association between total phosphorus and bacterial diversity as significant (0.01 < p < 0.05). These results show that rhizosphere filtering strongly structured bacterial composition and imposed deterministic selection on rhizosphere fungi. Full article

Background: The leading cause of cancer-related deaths globally is lung cancer, and the P2X7 receptor (P2X7R) is a promising therapeutic target due to its role in the disease progression. Methods: A deep learning-based molecular generation framework that integrates a fragment-based drug method with Relational Graph Convolutional Networks (RGCNs) and a Wasserstein Generative Adversarial Network (WGAN) was employed. Known P2X7R targeting drugs were fragmented to construct a fragment library, which was used to generate new candidate molecules. The generated molecules from the model were evaluated for chemical validity, novelty, Lipinski’s Rule of Five compliance, quantitative estimate of drug-likeness (QED), lipophilicity (LogP), similarity using the Tanimoto coefficient, and binding affinity through molecular docking. Results: The model generated 4498 chemically valid molecules, including 968 unique and 384 novel molecules. Approximately 97% satisfied standard drug-likeness criteria, with QED values predominantly above 0.6 and LogP values within acceptable pharmacokinetic ranges. The novel molecules demonstrated an improved docking score against P2X7R compared to the seed molecules. Conclusions: Despite training on 5000 SMILES due to limited computational resources, the model achieved high validity, strong molecular diversity, and drug-like physicochemical properties, demonstrating the feasibility of a scalable, target-specific AI pipeline for lung cancer drug discovery using fragment-based molecular generation, RGCN and WGAN. Nevertheless, the biological activity of the generated molecules remains experimentally unvalidated, and the findings are based solely on computational analyses. Full article

The growing interest in isotonic drinks translates into the need to develop formulations based on natural raw materials, which limit the use of synthetic additives while simultaneously increasing the bioactive value and sensory appeal of the products. The aim of this study was to develop innovative formulations for isotonic drinks based on natural fruit juices and to evaluate their physicochemical properties and sensory acceptance. Formulations containing 10–15% (v/v) fruit juice, with the addition of salt (0.13 g/100 mL) and organic sugar, were prepared, taking care to maintain osmolality within the range of 270–330 mOsm/kg. The 10 most appealing variants were selected and subjected to sensory analysis using the QDA; physicochemical analyses, including the determination of total polyphenol content (TP) and the DPPH free radical scavenging capacity; and the measurement of color parameters in the CIE Lab system. All the drinks analyzed received positive ratings in the sensory test (average acceptability scores ranging from 6.9 to 8.1). Physicochemical analyses revealed that the drinks had significant antioxidant activity: polyphenol content ranged from 46 mg to nearly 170 mg GAE/100 mL, whilst DPPH free radical scavenging capacity ranged from 45% to nearly 90%. We found that the use of fruit juices makes it possible to create isotonic drinks which not only effectively rehydrate, but also provide valuable antioxidant compounds. Full article

Colorectal cancer therapy requires drug delivery systems that improve treatment efficacy and minimize systemic toxicity. In this study, chitosan-based nanoparticles were fabricated and functionalized with folic acid (FA), phenylalanine (PA), and butyric acid (BA) to enhance the delivery of curcumin to Caco-2 cancer cells. The nanoparticles were prepared using an ionic gelation method, and their physicochemical properties, cellular uptake efficiency, and cytotoxicity—including safety evaluation against normal HIEC-6 cells—were investigated. Results showed that ligand conjugation significantly influenced the physicochemical properties of the nanoparticles. CRFANP (FA-modified) exhibited the largest particle size (263.5 nm) due to its rigid aromatic structure, while CRPANP (PA-modified) showed an intermediate size (138.0 nm) and the lowest surface charge (15.59 mV). In contrast, CRBANP (BA-modified) presented the smallest particle size (128.2 nm) and the highest positive surface charge (23.27 mV). These distinct physicochemical properties directly influenced their cellular interactions; CRBANP and CRFANP showed higher uptake than CRPANP, with CRBANP yielding the maximum accumulation of curcumin in Caco-2 (21.92 nM/mg protein) and HT-29 cells (22.09 nM/mg protein). Correlating with the uptake data, cytotoxicity assays revealed that CRBANP was the most potent formulation, exhibiting the lowest IC₅₀ of 1.30 µM in Caco-2 cells, which was significantly lower than that of CRFANP (3.49 µM) and CRPANP (7.40 µM), while demonstrating high selectivity against Caco-2 cells with an SI of 46.5 and no apparent toxicity toward normal HIEC-6 cells. This enhanced efficacy is attributed to the synergistic action of butyric acid as a histone deacetylase inhibitor (HDACi), which complements curcumin’s anticancer activity. These findings indicate that integrating butyric acid into chitosan nanoparticles provides an effective and selective strategy for targeted colorectal cancer therapy. Full article

Background: In Northeast China’s cold rice (Mollisol) regions, low temperatures slow straw decomposition, causing early microbial nitrogen (N) immobilization that competes with crop demand. Delayed N release from slow-release fertilizer (SRF) exacerbates this deficit, hindering high yield and grain quality. Methods: A two-year (2024–2025) pool planting experiment was conducted on rice ‘Jinongda 667’ with a total N application rate of 150 kg ha⁻¹. Six treatments were established: a 7:3 blend of slow-release fertilizer and urea, alongside controls of conventional urea and slow-release fertilizer alone, under both straw removal and incorporation conditions. Results: This blend increased grain yield by 6.64–7.75% over conventional urea, achieving the highest yield among all treatments, whereas SRF alone under straw incorporation reduced yield by 7.57% relative to N + S. The 30% urea (45 kg N ha⁻¹) alleviated immobilization deficit (15–30 kg N ha⁻¹) during the tillering-to-jointing stage, promoting root growth and panicle formation, while 70% SRF sustained N supply during mid-to-late stages, delaying senescence and enhancing photosynthesis. At peak grain filling, SSS and SBE activities increased by 94.01% and 10.53–11.08%, respectively. Under straw incorporation, it reduced chalky grain rate by 4.56–35.55% and chalkiness by 1.77–41.86%, increased protein content by 0.47–6.95% and gel consistency by 43.59–52.99%, decreased amylose by 2.2–5.77%, and optimized RVA profiles. Conclusions: The 7:3 blend synchronizes N supply with crop demand through temporal complementarity with straw nutrient dynamics, offering a one-time fertilization strategy for achieving high yield and quality under straw incorporation. However, given inter-annual variation (2024–2025) in tillering and N accumulation, its performance may be sensitive to climatic fluctuations, warranting further validation under diverse conditions. Full article

Wound healing is a dynamic and highly coordinated process that involves inflammation, cell proliferation, angiogenesis, re-epithelialization, extracellular matrix remodeling, and tissue maturation. The altered expression of important signaling pathways, such as transforming growth factor-β (TGF-β)/Smad, nuclear factor-κB (NF-κB), phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), mitogen-activated protein kinase (MAPK), and Wnt/β-catenin, may be responsible for slower wound healing, chronic inflammation, excessive fibrosis, and impaired tissue regeneration. Multifunctional nanomaterials are a promising strategy for tuning these highly coordinated processes due to their tunable physicochemical properties, high surface area, and the ability to deliver cargo, as well as the integration of antimicrobial, antioxidant, anti-inflammatory, and pro-angiogenic properties. The aim of current review is to summarize the potential of multifunctional nanomaterials to promote wound healing, with a focus on mechanisms of action and modulation of key cellular signaling pathways. A systematic review of the literature was conducted using PubMed, Scopus, Web of Science, and Google Scholar, searching for publications from 1996 to June 2026, and representative experimental, mechanistic, preclinical, and translational studies were critically evaluated. In this review, the authors discuss the role of nanomaterial properties, therapeutic payload, molecular targets, modulation of cellular signaling pathways, and regenerative effects. These platforms have been shown in in vitro and animal studies to influence inflammatory signaling, oxidative stress, angiogenesis, collagen remodeling, re-epithelialization, cellular proliferation, and migration. However, the modulation of these pathways are dose-responsive, time-dependent, and cell- and wound-stage-specific. Despite the promising therapeutic potential of nanomaterial-based wound care strategies, the available evidence remains predominantly preclinical, with relatively limited clinical data supporting their use in humans. Concerns regarding long-term toxicity, biodistribution, batch-to-batch reproducibility, sterilization, scalable manufacturing, regulatory approval, and commercial feasibility further challenge translation into clinical practice. Multifunctional nanomaterials may offer a promising approach for pathway-specific and multimodal wound management; however, comprehensive mechanistic studies, long-term safety and biodistribution assessments, and well-designed clinically relevant investigations are required to establish their efficacy, safety, and true translational potential. Full article

Sustainable management of biodegradable waste is a key component of the circular economy and resource recovery strategies. Composting is a complex biological process whose efficiency depends on numerous operational and physicochemical factors. Under industrial conditions, continuous laboratory monitoring of waste properties is often limited by time and cost constraints, necessitating reliable predictive tools to support process management. This study investigates the use of artificial neural networks (ANNs), decision trees (C&RT), and principal component analysis (PCA) for optimizing the composting of biodegradable waste under industrial-scale conditions. The research was conducted at a full-scale mechanical–biological treatment facility in Poland processing both the organic fraction mechanically derived from mixed municipal waste and separately collected biowaste. A dataset containing 23 records was developed from operational parameters (airflow, water addition, turning frequency, and process duration) and physicochemical properties of composted waste, including moisture content (MC), loss on ignition (LOI), total organic carbon (TOC), respiration activity (AT4), and higher heating value (HHV). The best-performing neural model achieved a predictive accuracy of 0.999 (coefficient of determination R² in the test set). For each of the neural networks, goodness of fit indices were also determined: MAE and RMSE. PCA confirmed strong relationships among key waste properties, while decision tree analysis identified airflow as the dominant operational factor affecting MC, LOI, and TOC, whereas turning frequency had the strongest influence on AT4. The results demonstrate that machine learning tools can effectively support industrial composting optimization by predicting operational parameters required to achieve desired waste stabilization characteristics, providing practical decision-support solutions for composting plant operators. It is recommended to implement single-output MLP models for dynamic, real-time process control and C&RT rules as emergency procedures. This study aligns with circular economy principles and the Sustainable Development Goals by demonstrating the potential of artificial intelligence to enhance sustainable biodegradable waste management, resource recovery, and industrial composting performance. Full article