Search Results (8,179)

The dynamics of active particles are increasingly being leveraged to design and control micro-robotic swarms. Local interactions play a crucial role in the phase transitions of active particles; how the combined effects of alignment, short-range repulsion, and boundary interactions regulate their packing structure and collective order with different confinement scales remains less systematically explored. In this study, we investigate the packing of active particles within a confined region, focusing on the role of local interaction rules in shaping both the packing structure and the polar order parameter. The effects of key controlling variables related to local interaction rules, including interaction radius, repulsion radius, confined boundary radius, and noise strength, are numerically studied. Specifically, by comparing systems with and without velocity–alignment interactions, we reveal the role of alignment in dictating both structural and dynamical properties of the ensemble. To quantify the packing structure, we employ Voronoi tessellation to evaluate both local and global packing densities. The results show that strong confinement induces a jammed state in which alignment effects are suppressed, resulting in high global packing density and low polar order, regardless of the noise amplitude. Upon increasing the boundary radius beyond a critical threshold, the system unjams, enabling alignment interactions to significantly enhance both the polar order parameter and packing density. Interestingly, the relationship between global packing density and micro-structural parameters, such as coordination number and Voronoi tessellation metrics, is similar in the systems with and without alignment. Our results demonstrate that collective packing and phase behaviour of active matter are governed by the nontrivial interplay between alignment, confinement, and noise, with alignment interactions driving the transition from disordered to ordered states as geometric constraints are relaxed, offering critical insights for the design of targeted micro-robotic swarms and active microfluidic sorting systems. Full article

Hybrid rocket engines (HREs) are increasingly considered for space transportation due to their inherent safety, cost-effectiveness, and operational flexibility. However, their diffusion flame structure promotes soot formation, leading to potentially significant emissions of black carbon (BC) directly into the stratosphere. This review provides a comprehensive analysis of soot formation and evolution in hybrid rocket combustion, covering fuel pyrolysis, polycyclic aromatic hydrocarbon (PAH) growth, particle nucleation, surface growth, and oxidation processes. The physico-chemical properties and nanostructural evolution of soot are discussed in relation to combustion conditions typical of HREs. Particular emphasis is placed on the environmental and climatic implications of BC emissions, including radiative forcing, atmospheric lifetime, and heterogeneous chemical interactions. Existing diagnostic techniques for soot measurement are critically assessed, highlighting their limitations under the extreme conditions of rocket exhaust plumes. A key outcome of this review is the identification of a major knowledge gap: although preliminary experimental emission-index measurements for HRE soot have recently become available, the database remains extremely limited, fuel- and configuration-specific, and not yet supported by standardised diagnostic protocols. Addressing this gap is essential for accurate environmental impact assessments and for the development of sustainable propulsion technologies. Full article

Saline soils subjected to short-term waterlogging are a constraint on the sustainable production of protected vegetables, triggering soil structural degradation, salt accumulation, and oxidative damage in plants, which seriously damages crop yield and quality. Calcium-based amendments have attracted considerable attention for improving soil conditions and enhancing plant stress tolerance. However, the effects of calcium lactate amendment on saline soil improvement and pepper physiological responses under short-term waterlogging conditions remain insufficiently understood. Different application rates of calcium lactate were applied to saline pepper croplands under waterlogged conditions. The effects on soil physicochemical properties, nutrient availability, plant antioxidant physiology, fruit yield, and quality were analyzed. Calcium lactate improved the physicochemical properties of waterlogged soil and increased the available nutrients in the soil, with the content of available phosphorus and available potassium increasing by 565–855% and 1.60–35.54%, respectively. It enhanced the activities of superoxide dismutase, peroxidase, and catalase, reduced malondialdehyde accumulation (up to 39% compared with CK), and increased proline content (up to 54.62% compared with CK), thereby promoting plant physiological adaptation under short-term waterlogging conditions and improving pepper yield and fruit quality. Higher doses of calcium lactate exhibit better ameliorative effects. Correlation analysis and partial least squares path modeling suggested that calcium lactate application was associated with improved pepper yield and quality through pathways related to soil improvement and plant physiological regulation. This study provides insights into the potential application of calcium lactate for saline soil improvement and sustainable pepper production under short-term waterlogging conditions. Full article

Given the urgent need to regulate oxidative stress microenvironments in chronic wound healing, hydrogel dressings that simultaneously integrate antioxidant, antibacterial, mechanically adaptive, and biocompatible properties are highly desirable. In this study, a natural polymer-based composite hydrogel dressing loaded with zinc-quercetin nanozyme (Zn-Q) was designed. The gel skeleton was constructed via a dual network of photocrosslinked methacrylated silk fibroin (SilMA) and mercaptolated hyaluronic acid (HA-SH) via thiol-ene click chemistry, with the catalase (CAT)-like Zn-Q nanozyme encapsulated in situ within the network, thereby achieving synergy between chemical crosslinking and dynamic metal-polyphenol coordination. Systematic characterization revealed that Zn-Q nanozyme adopted a stable octahedral coordination configuration, and its continuous porous structure exposed abundant catalytically active sites. The composite hydrogels exhibited a highly interconnected, three-dimensional (3D) porous morphology, with swelling ratios that increased significantly with Zn-Q nanozyme content (up to around 1082%). Rheological and mechanical tests demonstrated that although incorporating the nanozyme reduced the storage modulus, the reversible physical crosslinks formed via hydrogen bonding and coordination interactions endowed the material with excellent tensile toughness and energy-dissipation capacity, exhibiting typical Mullins softening behavior. Functional evaluation showed that Zn-Q nanozyme conferred superior free radical scavenging capability to the hydrogels and exerted dose-dependent inhibition against both Staphylococcus aureus and Escherichia coli. Furthermore, the hydrogels exhibited favorable adhesion to various wet organs and heterogeneous material surfaces, with hemolysis rates below 5% and cell viability exceeding 100% after 3 days of culturing with fibroblasts, confirming their excellent hemocompatibility and cytocompatibility. This study provides an experimental basis for developing a new type of wound repair materials that integrate antioxidant, anti-infective, and mechanically adaptive properties, holding significant application potential in oxidative stress-related tissue repair fields. Full article

Task decomposition is a fundamental challenge in multi-agent collaborative maintenance systems, where unstructured natural language instructions must be precisely translated into logically coherent, executable sub-task sequences. This paper formulates task decomposition as a constrained optimal path search problem on a heterogeneous knowledge graph that encodes coal mine equipment topology, fault causality, and maintenance procedures. We construct a composite cost function that systematically integrates semantic similarity from graph neural network embeddings, relation-type weights, and structural path length, transforming instruction parsing into a mathematically tractable combinatorial optimization. The cost function is derived from the principles of shortest-path reasoning in knowledge graphs: the relational weights capture domain-specific association strengths, the semantic similarity term promotes contextually coherent chains, and the path-length penalty prevents unnecessarily long derivations. A multi-hop reasoning algorithm coupling heterogeneous graph convolution with beam search is developed to solve this problem efficiently, achieving high-quality approximate solutions while ensuring computational tractability. The reasoning process is inherently interpretable, as the optimal path directly maps to a traceable atomic task sequence with explicit dependency relations. A formal complexity analysis shows the algorithm scales as $O$($b$·$K$·$d_{max}$), where b is the beam width and d_max is the maximum node degree. Several theoretical properties of the proposed framework are further derived: the cost function is non-negative and strictly monotonic, optimal paths satisfy the optimal substructure property, cycle-free optimal paths always exist, and beam search can yield globally optimal solutions given a sufficiently large beam width. These theoretical conclusions establish mathematical guarantees for the presented decomposition framework. Experiments on 200 composite maintenance instructions with gold-standard annotations (inter-annotator agreement Cohen’s $\kappa =0.88$) demonstrate that the proposed method achieves 94.3% task sequence accuracy (95% CI: 91.2–96.8%) and 96.4% dependency accuracy (95% CI: 93.5–98.1%), substantially outperforming both a rule-augmented baseline (58.6%, 62.1%) and a GPT-4o few-shot chain-of-thought baseline (73.2%, 70.5%); McNemar’s test yields p < 0.001 for both comparisons. The average inference time is 29.7 ms (SD 2.1 ms), meeting stringent industrial real-time constraints. Ablation studies quantify the contribution of each cost function component and confirm the robustness of the chosen beam width and hyperparameters. When integrated into a full multi-agent system, the framework delivers end-to-end response time within 3 s (P50: 1.87 s, P95: 2.83 s) and maintains an 86.7% task success rate even under dual agent failures, validating the robustness of the proposed mathematical formulation. This work establishes a rigorous graph-theoretic foundation for instruction decomposition in multi-agent systems, with direct applicability to safety-critical industrial environments. Full article

To control the impact of the invasive crayfish Faxonius limosus on native crayfish and fish biodiversity in the Danube River ecosystem, one possible approach is the valorization of this species through the production of value-added biopolymers, considering the continuously increasing demand for chitosan. However, there are very limited data regarding the utilization of Faxonius limosus shell waste as a source of chitosan. Therefore, this study evaluated chitosan recovery from spiny-cheek crayfish shell, including conventional chemical treatment with different demineralization intensities and numbers of deproteinization steps, as well as ultrasound and autolysis-assisted deproteinization. The obtained chitosans were characterized in terms of yield, moisture content, degree of deacetylation, color, crystallinity and structural properties. Residual heavy metal concentrations (Hg, Cd and Pb) were determined to assess the safety of crayfish shell as a raw material intended for food-related applications. Particular emphasis was placed on gel-related functional properties of obtained chitosans, including rheological behavior, wettability on fruit surfaces, antioxidant and antimicrobial activities, and film-forming ability. These properties govern the formation of structured biopolymeric networks and their performance as active food coating materials. The relationships between the extraction process, physicochemical characteristics and functional performance were investigated to identify the most suitable chitosan for potential food preservation applications. The results demonstrated that extraction conditions significantly affected the physicochemical and functional properties of chitosan. Samples obtained through intensive deproteinization showed enhanced antimicrobial activity, whereas higher antioxidant activity was observed in samples containing residual bioactive compounds. Most formulations exhibited suitable wettability on apple and nectarine surfaces and successfully formed transparent films, indicating their potential application as edible coatings. Full article

Plant diversity is often expected to enhance soil organic carbon (SOC) storage through greater and more heterogeneous plant inputs, but its relationships with functionally distinct SOC fractions in natural forests remain uncertain. This study compiled published SOC fraction data from 341 surface soil observations in natural forests across China and spatially matched these records with gridded plant alpha diversity, forest age, climate, topographic and soil properties datasets to evaluate biotic and abiotic associations with SOC, particulate organic carbon (POC), mineral-associated organic carbon (MAOC) and MAOC/SOC. Linear regression, multiple regression, piecewise structural equation modelling and stratified analyses were used to evaluate whether plant diversity was associated with the absolute accumulation and relative stabilization of SOC fractions. Plant alpha diversity was negatively associated with ln[SOC], ln[POC] and ln[MAOC] at the national scale, whereas its bivariate relationship with MAOC/SOC was weak. After accounting for forest age and environmental covariates, plant alpha diversity remained negatively related to the absolute contents of SOC fractions while showing a positive association with MAOC/SOC. Forest age was positively associated with ln[SOC], ln[POC] and ln[MAOC], and POC was more strongly related to plant diversity and forest age than MAOC. In contrast, MAOC and MAOC/SOC were more strongly associated with mineral protection potential, soil pH and precipitation background. Structural equation models indicated that mineral protection potential and mean annual precipitation were associated with greater MAOC accumulation and SOC allocation to the mineral-associated fraction, whereas temperature and topography were linked to MAOC partly through indirect associations with soil physicochemical conditions. Stratified analyses showed that plant diversity associations varied among forest types and climatic backgrounds. Additional interaction models showed that mineral protection potential significantly moderated the associations between plant alpha diversity and ln[SOC], ln[POC] and ln[MAOC], with negative diversity associations weakening under higher mineral protection potential. These findings indicate that plant diversity associations with SOC fractions in natural forests cannot be interpreted as universally positive input relationships. Instead, their direction and strength depend on hydroclimatic context and soil mineral protection, especially for the absolute accumulation of SOC fractions. Full article

Sulfated polysaccharides from red algae are multifunctional hydrocolloids whose properties depend strongly on molecular structure, sulfate content, and chain conformation. In this study, a sulfated galactan extracted from Gracilaria vermiculophylla collected from a coastal region of northwestern Mexico was investigated to elucidate its structural and functional properties. The polysaccharide was extracted by enzymatic treatment and characterized by monosaccharide analysis, FTIR, 1D/2D NMR spectroscopy, and size-exclusion chromatography coupled with multi-angle light scattering and viscometry. The extracted polysaccharide exhibited high carbohydrate (97%) and sulfate (28%) contents, with galactose as the predominant monosaccharide. It showed a moderate molecular weight (Mw = 2.39 × 10⁵ g/mol), a relatively narrow molar mass distribution (Mw/Mn = 1.23), a high intrinsic viscosity (420.9 mL/g), and an Rg/Rh ratio of 2.2, consistent with an expanded macromolecular conformation in solution. The sulfated polysaccharide also exhibited measurable antioxidant activity, particularly in the ABTS⁺ assay (IC₅₀ = 31.8 ± 2.5 mg/mL) compared with the DPPH assay (IC₅₀ = 51.1 ± 3.0 mg/mL), and showed Fe³⁺-responsive association, leading to the formation of microgel-like structures. These findings indicate that the sulfated galactan characterized in this study is a structurally complex and functionally active hydrocolloid with potential relevance for functional food systems and related biomaterial applications. Full article

We elaborate on computational emergence (CE), understood as the emergent acquisition of specific abilities from specific forms of computation, such as artificial neural networks and cascades of rule iterations found in cellular automata. CE leads to the acquisition of properties such as learning abilities, morphological pattern formation, and coherence, and arises from computational mechanisms. We also elaborate on emergent computation (EC), understood as the emergent acquisition of computational abilities by communities of phenomenologically interacting agents, potentially through appropriate interlinkages among them, as in emerging networks. Processes of interaction are understood generically as forms of mutually active interdependence, which can be modeled as self-generated networks. EC arises from phenomenological mechanisms of interaction among agents and leads to the acquisition of properties such as coherent behaviors, resilience, robustness, and collective intelligence. The reason for distinguishing between these two types of emergence is that doing so may open new approaches to modeling collective behavior, especially in artificial ones, such as swarms of unmanned aerial vehicles (UAVs), where introducing parametric and structural changes is more feasible. Combining the two approaches—(a) phenomenological, networked EC arising from populations of interacting (b) in turn computationally emergent agents—allows the consideration of research directions such as identifying relationships between combinations of CE and emergently acquired computational properties within the conceptual frameworks of networked neural networks and intersected neural networks, i.e., networks that share neurons. Such research directions are expected to enable approaches for influencing collective behaviors and complex systems in a non-invasive way, including swarms of UAVs (or drones), autonomous cyborg swarms, and coherent communities of artificial devices equipped with sensors, edge artificial intelligence, and secure communications. We consider the mesoscopic nature of complexity in collective behaviors as a continuous negotiation between these two forms of emergence, with EC playing a macroscopic role and CE a microscopic role. We conclude that this general framework relates to the concept of “The Middle Way” in physics by focusing on what occurs “in between” systems (such as between intersecting neural networks and their dynamic networking) and within transient spaces where non-invasive intervention may be possible and appropriate for guiding, modifying, and inducing changes in complex emergent systems. Full article

Let $X_n=\{1,2,\dots ,n\}$. Previous work has focused on ordinary semigroup identities and the structural properties of individual transformation monoids. Building on related identity-based work involving one of the present authors, we compare the full transformation semigroup ${\mathcal{T}}_n$, the order-preserving semigroup ${\mathcal{O}}_n$, the order-preserving-or-order-reversing semigroup ${\mathcal{OD}}_n$, the orientation-preserving semigroup ${\mathcal{OP}}_n$, and the anti-cyclic one-line family ${\mathrm{OR}}_n$, treated only as a subset of ${\mathcal{T}}_n$. For each family S, we determine the least positive exponent $E_S$ such that $a^{E_S}$ is idempotent for every $a\in S$. This gives $z^{E_S}=z^{2E_S}$. For $n\ge 2$, the exponents for ${\mathcal{T}}_n$, ${\mathcal{O}}_n$, ${\mathcal{OD}}_n$, and ${\mathcal{OP}}_n$ are $lcm(1,\dots ,n)$, $n-1$, $2⌈{\displaystyle \frac{n-1}{2}}⌉$, and $lcm(1,\dots ,n)$, while $\widehat{E}\left({\mathrm{OR}}_n\right)=2⌈{\displaystyle \frac{n-1}{2}}⌉$ is the subset exponent for ${\mathrm{OR}}_n$. We then study $x^{E_S}{y}^{E_S}{x}^{E_S}=y^{E_S}{x}^{E_S}$. With $p=x^{E_S}$ and $q=y^{E_S}$, it reduces to $pqp=qp$. This holds exactly when q maps each kernel block of p into a single kernel block of p, and fails exactly when q splits a block. Together with the automatic cases, this test gives a classification of all ordered pairs into automatic, positive, and negative classes. Full article

Chalcones are naturally occurring open-chain flavonoids widely distributed in plants and recognized for their broad spectrum of pharmacological activities. Their versatile scaffold allows for extensive structural modifications, leading to a diverse range of natural and synthetic derivatives with notable biological potential. In the context of viral infections, chalcones have demonstrated remarkable efficacy against a variety of human pathogens, including dengue virus, HIV, HCV, influenza A, SARS-CoV-2, and other emerging viruses. Beyond human health, several chalcones have shown potent activity against plant viruses such as tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV), and animal viruses including porcine reproductive and respiratory syndrome virus (PRRSV) and mammalian reovirus (MRV), underscoring their broad antiviral spectrum. These compounds act through multiple mechanisms, including the inhibition of viral enzymes (e.g., proteases, polymerases, and integrases), interference with viral entry and replication, and the modulation of host-related pathways. Recent advances in molecular docking, structure–activity relationship (SAR) studies, and synthetic optimization have further highlighted chalcones as a promising scaffold for antiviral drug discovery. Accordingly, this review summarizes and categorizes antiviral chalcones reported over the last two decades, emphasizing and critically discussing their molecular targets, mechanisms of action, and pharmacological potential as lead compounds. It also provides a comparative perspective on their pharmacological relevance by correlating their activities against standard therapeutic agents and reference inhibitors. Furthermore, the most recurrent viral targets were critically discussed regarding their conservation, expected genetic barriers to resistance, and the global SAR trends identified for the corresponding antiviral chalcones. Finally, in silico ADMET profiling of the most promising naturally occurring chalcones was performed to evaluate their drug-likeness and pharmacokinetic properties, offering guidance for future structural optimization and translational development. Collectively, these findings highlight the chalcone scaffold as a versatile platform for the development of novel antiviral agents targeting diverse viral and host pathways. Full article

Constitutive models for clays have historically treated yield geometry, plastic-flow direction, and compression as separate problems, with little regard for their interaction. This paper presents a controlled numerical assessment of how three components—Chatwong et al.’s verified teardrop yield surface, a stress-fractional flow rule, and an AJOP-derived hardening modulus— interact when coupled in a 2 × 2 × 2 factorial design. The components are integrated incrementally along one idealized shear-strain-controlled constant-p′ path with an approximate undrained variant for two independently calibrated clays (Boston Blue Clay and London Clay) under a specified state-dependent fractional order. Within this scope, the main flow effect is consistently the largest single quantity for both soils, and the flow × compression interaction is comparably large wherever defined. Compression’s role grows substantially with the overconsolidation ratio, and the main geometry effect is markedly soil-dependent, scaling with the surface-shape parameter. Two structural singularities are identified: a phase-transformation point in the teardrop surface’s non-associated flow rule, absent from the fractional rule, and a hardening singularity in the AJOP-based modulus, whose tangent falls to the swelling index at a finite, soil-dependent preconsolidation stress, bounding the evaluable overconsolidation range of the compression-related interactions; a proportional-κ variant removes this singularity by construction while preserving the factorial ranking, identifying it as a property of the constant-κ embedding, not of AJOP itself. Under an approximate undrained path, the geometry × flow interaction carries over unchanged, while compression’s role is suppressed several-fold. The borrowed yield surface and flow rule are validated independently against 379 points from real undrained triaxial tests across four calibrated soils using this paper’s own re-calibrated predictions; the fractional–AJOP framework itself is assessed for internal consistency only, and its laboratory validation, together with K₀, cyclic and multi-axial paths, remains for future work. Full article

Climate change has been associated with an increasing occurrence of extreme wind phenomena, including hurricanes, tornadoes, and downbursts, with noticeable rises in both their frequency and severity. These events have heightened concerns regarding their devastating impacts on structures, infrastructure, and economies. To provide a comprehensive and reliable review, a large number of previous studies and scientific references were collected and carefully screened. The selection process focused primarily on studies directly related to structural engineering applications, wind-induced structural responses, tornado and hurricane loading mechanisms, and simulation techniques used in wind engineering research. References unrelated to structural behavior, engineering analysis, or wind-resistant design were excluded to maintain the technical relevance and consistency of the review. This review explores parameters influencing wind loads, focusing on tornado flow field characteristics such as swirl ratio, ground roughness, translation speed, and topography. It also examines structural properties such as geometry, material, orientation, and proximity to the tornado path that govern a building’s ability to withstand wind-induced forces. The review evaluates experimental techniques, including wind tunnel tests, tornado simulators, and numerical simulations using Computational Fluid Dynamics (CFD) to improve understanding and resilience. These approaches are compared for effectiveness in replicating real-world scenarios and enhancing predictive accuracy. Furthermore, key engineering standards, such as ASCE 7-22 and FEMA guidelines, are highlighted, showing their role in improving structural design, identifying gaps in research, and advocating for future studies. It emphasizes integrating emerging computational technologies, including machine learning, to enhance structural design efficiency and disaster response performance. This review aims to guide researchers and engineers toward developing resilient structures capable of mitigating the impacts of extreme wind events. Full article

Marine-derived bioactive compounds have attracted considerable attention as functional ingredients for food and nutraceutical applications due to their various biological activities. Among marine resources, macroalgae represent a sustainable and abundant source of structurally diverse bioactive compounds, including polyphenols, pigments, and polysaccharides. This review provides a comprehensive overview of macroalgal bioactive compounds, with particular emphasis on their sources, the environmental and seasonal factors influencing their composition, chemical classification and characteristics, extraction technologies, biological properties and food and nutraceutical applications. Particularly, attention is given to the molecular mechanisms underlying their antioxidant and anti-inflammatory effects, including radical scavenging, metal chelation, modulation of endogenous antioxidant defense systems, and regulation of key signaling pathways involved in inflammation. Green extraction techniques and encapsulation strategies for improving the stability, bioavailability, and functionality of macroalgal bioactives are critically discussed. Current applications in foods and nutraceutical products are reviewed alongside the major challenges related to biomass variability, large-scale production, standardization, and regulatory compliance. Overall, macroalgal bioactive compounds represent a promising class of sustainable health-promoting ingredients, and continued advances in cultivation, processing, extraction technologies, formulation, and regulatory frameworks will be essential to support their broader industrial utilization. Full article

Background: Dihydromyricetin (DHM) is a food-derived flavonoid enriched in vine tea and has been reported to possess antioxidant and metabolism-regulating properties. This study was designed to characterize the multi-level nutritional responses to dietary DHM supplementation, with emphasis on hepatic redox–inflammatory status, jejunal barrier-related phenotypes, cecal microbiota remodeling, hepatic metabolomic alterations, and homocysteine (Hcy) metabolism-related markers in mice. Methods: Forty-eight healthy mice were assigned to a basal-diet control group or diets containing 50, 100, or 200 mg/kg DHM for 4 weeks. Growth performance, serum biochemistry, antioxidant parameters, hepatic antioxidant-related expression, hepatic inflammatory cytokines, jejunal morphology and tight junction proteins, cecal 16S rRNA profiles, hepatic metabolomics, and Hcy metabolism-related markers were assessed. Results: Dietary DHM improved serum and hepatic antioxidant status, as reflected by increased T-AOC and GSH-Px activity and decreased MDA concentrations (p < 0.05). DHM also modulated the hepatic cytokine profile, with decreased TNF-α concentration (p < 0.05) and increased IL-10 concentration (p < 0.01). DHM increased hepatic Nrf2 protein abundance, HO-1 protein abundance, and Gclc mRNA expression (p < 0.05). DHM also improved jejunal villus architecture, as indicated by increased villus height, decreased crypt depth, and an increased villus height-to-crypt depth ratio (p < 0.05). Jejunal Occludin and ZO-1 protein expression were increased in the DHM-treated groups (p < 0.05). Cecal microbiota analysis showed increased richness and diversity indices and altered microbial community structure. Hepatic metabolomics revealed changes involving vitamin B6 metabolism, purine metabolism, the pentose phosphate pathway, and α-linolenic acid metabolism. Serum Hcy levels decreased (p < 0.05), accompanied by increased hepatic BHMT and MTHFR protein abundance (p < 0.01). Conclusions: Dietary DHM supplementation improved hepatic redox status and supported a less pro-inflammatory cytokine profile in mice, accompanied by enhanced jejunal barrier-related phenotypes, cecal microbiota remodeling, hepatic metabolic alterations, and Hcy metabolism-related responses. These findings provide a multi-level nutritional evaluation of DHM and suggest its potential relevance for supporting intestinal barrier integrity and hepatic metabolic homeostasis under basal physiological conditions. Full article