Search Results (4,196)

Background/Objectives: This study evaluated the anti-inflammatory effects of ocotillol, a compound isolated from the ethanol extract of propolis of the Tetragonula iridipennis stingless bee. Through its ability to inhibit NO production in an in vitro model, it investigated the NO inhibition mechanism using network pharmacology combined with molecular docking. Methods: The NO production inhibitory activity was determined by colorimetric assay using Griess reagent. An in silico study was performed using network pharmacology analysis, molecular docking, and molecular dynamics simulations. Results: The in vitro results demonstrated that ocotillol exhibited significant anti-inflammatory effects by effectively inhibiting NO production, with an IC₅₀ value of 20.29 ± 2.1 µg/mL. The network pharmacology analysis revealed that ocotillol targets 14 molecular sites related to NO, with TACR1 showing the best binding affinity at −10.0 kcal/mol. Molecular dynamics simulations suggest that TACR1 is a potential target. As indicated by the stable interaction profile, further validation in complex biological membranes is warranted. Conclusions: This study also provides evidence for the correlation between in vitro and in silico models, thus laying the groundwork for in vivo evaluations to confirm the anti-inflammatory mechanism of ocotillol. Full article

Unlocking the potential of polymer blends requires innovative strategies that transcend simple mixing. This study presents a novel approach by creating hybrid blends of epoxy and structurally compatible in situ synthesized epoxy acrylate (vinyl ester) resins, further reinforced with halloysite nanotubes (HNTs). We went beyond simple blending by synthesizing the epoxy acrylate (EA) component from the base epoxy resin, ensuring molecular-level compatibility. The epoxy acrylate was successfully synthesized via a ring-opening reaction, as confirmed by FTIR and ¹H-NMR. A series of blends at varying weight ratios of epoxy/epoxy acrylate (75/25, 50/50, and 25/75) was prepared and optimized using dynamic mechanical analysis (DMA) for the best viscoelastic performance and subsequently reinforced with 2 wt% HNTs. Our findings reveal that this unique approach fosters highly interpenetrated polymer networks (IPNs), as evidenced by thermal and viscoelastic behavior. The hybrid epoxy nanocomposite with a 75/25 blend ratio exhibits a superior balance of properties, demonstrating a synergistic enhancement in both thermal and thermomechanical properties compared to the neat epoxy and epoxy acrylate networks. The optimized hybrid epoxy composite exhibits a 147% increase in storage modulus (E’) and a 180% increase in loss modulus (E”) over the neat epoxy composite while enhancing thermal stability. This study not only presents HNT-reinforced epoxy/epoxy acrylate as a new family of robust hybrid nanocomposites but also provides a fundamental blueprint for compatibilizing and reinforcing thermoset blends for advanced applications. Full article

Parasitic infections pose a significant threat to the wild population of Southern catfish (Silurus meridionalis) in Dongting Lake, yet the specific pathogen identity and epidemiological drivers remain unclear. This study combined morphological assessment, 28S rDNA molecular identification, and Generalized Linear Models (GLM) to elucidate the infection dynamics and pathogenicity of trematodes. Molecular analysis confirmed the pathogen as Isoparorchis eurytremus. GLM analysis revealed that apparent spatiotemporal variations in infection were actually sampling bias in fish host size structure; the total length was identified as the decisive predictor of infection risk. The infection probability followed a sigmoid growth pattern with a median infection length (L₅₀) of 70.4 cm, a phenomenon attributed to the host’s ontogenetic diet shift from insectivory to obligate piscivory. Anatomical observations indicated that the infection induced systemic pathology; beyond severe fibrosis and mechanical damage to the swim bladder, varying degrees of parenchymal lesions were evident in the liver, spleen, and kidney. These findings indicate that I. eurytremus infection in S. meridionalis is a size-dependent, accumulative process maintaining a homogenous high pressure across the lake ecosystem, necessitating a shift in perspective from localized lesions to systemic disease management. Full article

Lupinus angustifolius is an important leguminous ornamental species, but its productivity is often compromised by alkaline soil stress. GsEXPA8, an expansin gene identified in wild soybean (Glycine soja), has been implicated in alkali stress tolerance. In this study, we examined how heterologous expression of GsEXPA8 in lupinus affects its biochemical, molecular, and rhizospheric responses to alkali stress. Under NaHCO₃-induced alkaline conditions, transgenic lines overexpressing GsEXPA8 displayed improved leaf vigor, greater root biomass and length, elevated activities of antioxidant enzymes (CAT and POD), increased proline accumulation, and reduced malondialdehyde levels compared to the wild type. Expression analysis revealed time-dependent up-regulation of several alkali-responsive genes (LaSOS1, LaNCED3, LaMYB39, LaNAC56, LaNHX6, and LaP5CS). Moreover, the rhizosphere microbial community was significantly restructured, with a marked increase in beneficial microbial taxa such as Pseudomonas and Lysobacter. We also found that the endogenous lupinus homolog LaEXPA8 is alkali-inducible. Overexpression of LaEXPA8 similarly enhanced alkaline tolerance, whereas CRISPR/Cas9 knockout lines showed no clear phenotypic alteration, suggesting potential functional redundancy within the expansin family. Notably, LaEXPA8 and GsEXPA8 differed in their temporal regulation of downstream genes, indicating both conserved and distinct regulatory roles. Our results demonstrate that GsEXPA8 improves alkali tolerance in lupinus through integrated mechanisms: promoting root growth, enhancing antioxidant and osmotic adjustment capacity, dynamically modulating stress-related gene expression, and enriching beneficial rhizosphere microbiota. This work provides the critical report of modifying alkali tolerance by manipulating an expansin gene alongside the associated rhizosphere microbiome, offering a combined strategy for breeding stress-resistant ornamentals. Full article

Calcium phosphate–poly(methyl-methacrylate) composite layers have been synthetized on silicon substrates in magnetron sputtering discharge by adjusting the radio-frequency power. The electron energy distribution function measured at holder substrate position shifts to lower energies when the radio-frequency power applied to the magnetron source increases from 50 to 150 W and the poly(methyl-methacrylate) molecule dissociation is augmented. The optical emission spectral analysis indicated the dynamics of the excitation and ionization processes in the Ar–calcium phosphate–poly(methyl-methacrylate) plasma mixture, as well as the dissociation patterning of the polymer molecules. The Ca I, P I, and H_α atomic lines and CaO, PO, POH, CO, CH and C₂ molecular bands characteristic to the calcium phosphate and poly(methyl-methacrylate) decomposition were evidenced. At 150 W radio-frequency power a reduction in the polymer content in the composite layer volume was observed even if the α-CH₃ main chain and the C=O molecular bands are still present. More C-C/C-H, C-OH/C-O-C polymeric bonds were revealed at the layer surface, indicating the formation of plasma polymers. The Ca/P ratio changes from 1.72 to 1.9 at 50 to 150 W, respectively, maintaining the amorphous structure of the layers. In this power range, the transition of layer surface morphologies from grain-like to worm-like plasma polymer characteristics is connected to an increase in plasma ion density and layer thickness. Full article

Deep-sea mollusks represent untapped resources for searching novel biologically active peptides effectual against many chronic diseases. Here we presented the identification of four novel angiotensin I-converting enzyme (ACE) inhibitory peptides from the deep-sea mollusk Gigantidas platifrons by using a combined approach of peptidomics and virtual screening. Fifteen protein hydrolysates from five deep-sea macroorganisms were prepared using three different proteases and were determined for their ACE inhibitory activities. Pepsin hydrolysate of G. platifrons protein (GPp) demonstrated the highest inhibition rate against ACE at 400 μg/mL. Then, targeted investigation was conducted on the GPp with peptidomic profiling; more than 3000 peptides were de novo identified, which were then subject to virtual screening using the docking software Smina. Subsequently, 29 peptides were selected and synthesized based on the affinity threshold and the interactions with ACE active sites. More than 58% peptides were biologically active, showing more than 50% inhibition to ACE at 400 μM. Four peptides, LAAHFAR, YAAPYR, NGAGPYGRP, and FTTFGK, exhibited low micromolar inhibition. The most potent peptide, LAAHFAR with an IC₅₀ of 6.01 ± 1.06 μM, was subject to molecular dynamics simulations for revealing atomistic interaction analysis. LAAHFAR forms comprehensively stable hydrogen bonds with the classic active site of ACE, and its N terminal arginine residue is anchored by additional hydrogen bonding to Cys370, Asp377, and Thr372. This study highlights deep-sea mollusks as an important source of novel ACE inhibitory peptides, contributing to the development of new therapeutic ingredients or functional food agents against hypertension. Full article

Background/Objectives: Colorectal cancer (CRC) liver metastases present a significant clinical challenge due to high recurrence risks post-resection. Traditional diagnostics often fail to detect early-stage minimal residual disease (MRD). This preliminary pilot study evaluated ctDNA dynamics in 10 patients with liver metastases using a personalized multistep approach. Methods: Following primary tumor Next-Generation Sequencing (NGS) to identify somatic mutations in KRAS, NRAS, TP53, RET, APC, and WRN, custom TaqMan assays were designed for longitudinal plasma analysis. Four methodologies were compared: HRM-PCR, PNA-enhanced qPCR, and two digital platforms (dPCR and ddPCR). Results: While HRM-PCR sensitivity was limited in plasma, digital platforms demonstrated 100% qualitative concordance. MRD-negative status (VAF 0.00%) was identified in 70% of cases (P01, P03, P06, P07, P08, P09, P10), while detectable ctDNA in patients P02, P04, and P05 strongly correlated with aggressive progression. Digital PCR enabled the ultra-low detection of Variant Allele Frequencies (VAFs), identifying high molecular burdens (e.g., P05, VAF 49%) correlating with rapid decline, and capturing early molecular residue in P04 (VAF 0.62%). Conclusions: Our preliminary findings confirm that personalized longitudinal VAF tracking via digital PCR provides superior prognostic value, serving as a robust tool for recurrence monitoring in personalized CRC therapy. Full article

To address the challenge of purifying bioactive polyphenols from the complex matrix of Ziziphus jujuba Mill. var. spinosa pulp, this study established an integrated purification protocol combining Deep Eutectic Solvent (DES) extraction with macroporous adsorption resin (MAR) enrichment. Among five screened resins, AB-8 exhibited superior selectivity, achieving a maximum adsorption capacity of 62.48 mg polyphenols/g dry resin and a desorption ratio of 83.40%. Kinetic analysis revealed that the adsorption process strictly followed a pseudo-second-order model (R² = 0.999), indicating a mechanism dominated by chemisorption. Through dynamic optimization, optimal column parameters were determined as a loading concentration of 2.4 mg/mL, a flow rate of 1.0 mL/min, and elution with 70% (v/v) ethanol. Structural characterization via UV-Vis and FT-IR confirmed the effective removal of polysaccharide and protein impurities, while High-Performance Gel Permeation Chromatography (HPGPC) indicated a low-molecular-weight distribution (M_w approx. 1073 Da). Furthermore, HPLC-MS profiling definitively identified eight key constituents, including chlorogenic acid, catechin, rutin, and quercetin. Collectively, this work elucidates the adsorption mechanism and provides a scalable, efficient technical foundation for the high-purity preparation of jujube polyphenols. Full article

Phospholipases A₂ (PLA₂s) are key mediators of the cytotoxic and inflammatory activities of snake venoms. While PLA₂ isoforms from Bothrops diporus venom have been characterized and shown to possess antimetastatic and antiangiogenic properties, their impact on mitochondrial bioenergetics and immune modulation has not yet been investigated. In this study, we examined the bioenergetic and immunomodulatory effects of B. diporus PLA₂s using integrated biochemical, metabolic, and multiplex cytokine analyses. In MDA-MB-231 breast cancer cells, pooled PLA₂s induced a dose-dependent decrease in MTT-reducing activity, increased mitochondrial ROS, caused Δψm hyperpolarization, and decreased NADH autofluorescence, collectively indicating sustained mitochondrial stress. Real-time impedance measurements further revealed a marked inhibition of cell proliferation. In human PBMCs, pooled PLA₂s elicited a dynamic cytokine program, inducing early cytotoxic (Granzyme B) and chemotactic (CCL2, CCL3, CCL4) mediators, followed by late pro-inflammatory and regulatory factors such as IL-6, TNF-β, IL-10 and IL-15. Analysis of a single purified PLA₂ isoform (Fraction 6) confirmed activation of the canonical IL-6/TNF-α/IL-1β axis but uniquely induced IL-10 and CCL20, revealing isoform-specific immunomodulatory properties. Altogether, these findings provide the first integrated characterization of mitochondrial and immune perturbations induced by B. diporus PLA₂s, expanding their recognized biological scope and underscoring their potential as molecular templates for novel pharmacological strategies targeting mitochondrial vulnerabilities or modulating the tumor immune microenvironment. Full article

Graph Neural Networks (GNNs) have become a central methodology for modelling biological systems where entities and their interactions form inherently non-Euclidean structures. From protein interaction networks and gene regulatory circuits to molecular graphs and multi-omics integration, the relational nature of biological data makes GNNs particularly well-suited for capturing complex dependencies that traditional deep learning methods fail to represent. Despite their rapid adoption, the effectiveness of GNNs in bioinformatics depends not only on model design but also on how biological graphs are constructed, parameterised and trained. In this review, we provide a structured framework for understanding and applying GNNs in bioinformatics, organised around three key dimensions: (1) graph construction and representation, including strategies for deriving biological networks from heterogeneous sources and selecting biologically meaningful node and edge features; (2) GNN architectures, covering spectral and spatial formulations, representative models such as Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs), Graph Sample and AggregatE (GraphSAGE) and Graph Isomorphism Network (GIN), and recent advances including transformer-based and self-supervised paradigms; and (3) applications in biomedical domains, spanning disease–gene association prediction, drug discovery, protein structure and function analysis, multi-omics integration and biomedical knowledge graphs. We further examine training considerations, including optimisation techniques, regularisation strategies and challenges posed by data sparsity and noise in biological settings. By synthesising methodological foundations with domain-specific applications, this review clarifies how graph quality, architectural choice and training dynamics jointly influence model performance. We also highlight emerging challenges such as modelling temporal biological processes, improving interpretability, and enabling robust multimodal fusion that will shape the next generation of GNNs in computational biology. Full article

Dissolution of iron oxides in water plays a critical role in corrosion, mineral cycling, and surface reactivity; yet, the atomic-scale mechanisms governing Fe release remain poorly understood. Here, we employ ab initio molecular dynamics and well-tempered metadynamics simulations to investigate the stepwise dissolution of surface Fe atoms from the -Fe₂O₃(0001) surface in aqueous solution. The dissolution process initiates from a stable surface configuration in which Fe is coordinated to three lattice oxygen atoms and one water molecule. It proceeds through a series of metastable states involving additional water coordination, proton-assisted Fe-O bond weakening, and eventual detachment from the substrate. The first major transition, requiring 46.5 kJ/mol, involves breaking the hydrogen-bonding net and overcoming steric hindrance to allow adsorption of a second water molecule. Intermediate barriers (10.9–30.3 kJ/mol) are associated with further coordination and bond cleavage steps. In contrast, the final release of Fe into the solution, corresponding to a state coordinated with four water molecules and no lattice oxygen, exhibits a much higher free-energy barrier of ~ 93.0 kJ/mol. This barrier arises from the formation of a rigid hydrogen-bonded water cage and the loss of proton access to the remaining surface oxygen site, as confirmed by radial distribution function analysis. Our findings reveal why -Fe₂O₃(0001) is highly resistant to complete dissolution yet prone to surface roughening, defect formation, and adatom structures under aqueous conditions. Full article

Background: Tubulin plays a pivotal role in cell division and other essential cellular processes, making it a key pharmacological target for cancer therapy, antiparasitic treatments, and neurodegenerative diseases. Numerous compounds have been developed to regulate microtubule polymerization through tubulin binding; however, most have shown significant limitations, including adverse side effects, poor bioavailability and limited specificity. In recent years, peptide-based therapies have gained considerable attention, particularly for their ability to modulate protein–protein interaction while offering improved selectivity and safety profiles. Methods: In this study, we employed an integrated computational–experimental approach combining molecular docking, molecular dynamics simulations, and MM-GBSA free energy calculations to design and evaluate 14 peptides derived from the αβ-tubulin dimer interface. Results: The peptide NH₂-P14-COOH emerged as the most promising candidate, displaying the stronger inhibition of tubulin polymerization activity (IC₅₀ = 11.24 ± 3.82 μM), selective cytotoxicity against NCI-H1299 lung carcinoma cells (IC₅₀ = 45.64 ± 3.20 μM), and no significant toxicity toward non-cancerous EA.hy926 endothelial cells (IC₅₀ > 100 μM). Flow cytometry analysis confirmed that NH₂-P14-COOH induces apoptosis, supporting a mechanism of action based on microtubule disruption. Conclusions: These findings highlight NH₂-P14-COOH as a selective antimitotic peptide with a favorable therapeutic index and demonstrate the potential of structure-guided peptide design for the development of novel microtubule-targeting agents with reduced off-target toxicity. Full article

Type 2 diabetes (T2D) causes systemic metabolic and inflammatory changes that affect the oral cavity, but salivary molecular markers remain poorly characterized. A peptide-centric reanalysis of salivary proteomics data was performed using DIA-NN for peptide-level quantification, without collapsing peptide signals into protein-level summaries. Although the qualitative peptide repertoire was largely conserved between T2D and control samples (>96% overlap), T2D showed coordinated quantitative changes in specific peptide subsets. Differentially abundant peptides primarily originated from complement C3, alpha-2-macroglobulin, serotransferrin, mucins, apolipoproteins, and hemoglobin, with a significant enrichment of oxidized cysteine-containing peptides, indicating redox imbalance and low-grade inflammation. Structural analysis with AlphaFold showed that T2D-associated peptides are located in solvent-exposed and conformationally dynamic regions of proteins. These findings suggest that disease specificity in diabetic saliva occurs mainly at the peptide level, offering mechanistic insight into non-invasive biomarker identification and longitudinal disease monitoring. Full article

Silphium perfoliatum is a promising economic plant rich in bioactive secondary metabolites, yet the molecular regulation of phenylpropanoid biosynthesis across development remains unclear. To elucidate the regulatory networks underlying these metabolic processes, we integrated metabolomic and transcriptomic analyses across six developmental stages, from cotyledon to flowering. LC–MS/MS identified 1964 metabolites, with phenylpropanoids representing the largest class (601 compounds). Differential accumulation analysis showed pronounced temporal dynamics in phenylpropanoid levels, especially chlorogenic acid and its derivatives, with many compounds peaking at the flowering stage. In parallel, RNA-seq revealed 31,624 differentially expressed genes (DEGs). Functional enrichment highlighted phenylpropanoid and flavonoid biosynthetic pathways as major metabolic hubs. Correlation analysis indicated that PAL, 4CL, HCT, F3H, FLS, and F3′H expression was tightly coordinated with the accumulation of phenolic acids and flavonoids, suggesting these gene encoded enzymes may represent rate-limiting steps. Furthermore, weighted gene co-expression network analysis (WGCNA) identified a “blue” module strongly associated with phenylpropanoid accumulation and significantly enriched in pathway-related genes. Together, these results provide a comprehensive regulatory framework for phenylpropanoid biosynthesis in S. perfoliatum and offer valuable genetic targets for metabolic engineering and molecular breeding to enhance bioactive compound production. Full article

Lactation is a dynamic process characterised by a production peak at 6–8 weeks, followed by a steady decline. To understand the molecular drivers of these phases and the influence of production systems, this study aims to provide a transcriptomic characterisation of bovine milk somatic cells (BMSCs) in Holstein (HO), Simmental (SM), Simmental × Holstein crossbreed (SM × HO), and Podolica (POD) cows at 60 and 120 days in milk (DIM). Total RNA was sequenced at high coverage, and differential expression and functional enrichment analyses were performed. While a core set of milk protein and fatty acid genes was identified, breed-specific analysis showed SM × HO had the highest variation (677 differentially expressed genes, DEGs). Genes upregulated at 120 DIM involved mitochondrial metabolism and oxidative phosphorylation, while downregulated genes were associated with nuclear transcriptional regulation. At 60 DIM, SM × HO vs. HO showed 66 DEGs, with upregulated genes linked to chromatin remodelling and immune regulation. Comparing production systems, 28 DEGs between POD and HO/SM highlighted differences in mitochondrial activity and transcriptional regulation. This study bridges a knowledge gap by profiling the milk transcriptome of unexplored cattle breeds, providing novel insights into the molecular regulation of lactation. Full article