Search Results (22,572)

Chia seed mucilage (CSM) is a promising plant-derived hydrocolloid characterized by unique physicochemical and functional properties that are strongly influenced by the extraction methodology. In this research, an optimized sonication–freezing-assisted extraction (SFAE) process was developed to obtain mucilage while preserving its structural integrity. Results indicate that the extracted mucilage has a high total dietary fiber content of 75.87% and a moderate protein level of 8.71%. Fourier transform infrared spectroscopy (FTIR) confirmed the presence of hydroxyl and ionized carboxylate (COO⁻) groups associated with uronic acids, highlighting the anionic and polyelectrolyte nature of the system. Rheological characterization of optimized-CSM revealed Newtonian behavior in dilute solutions, indicating minimal intermolecular interactions and permitting accurate measurement of intrinsic viscosity and viscosity-average molecular weight. A critical overlap concentration (c** ≈ 0.2% w/v) was identified, marking the transition to semi-dilute regimes, chain entanglement, and the onset of shear-thinning and viscoplastic behavior. Functionally, the optimized-CSM exhibited high water holding capacity and competitive emulsifying properties (emulsion activity index (EAI): 62.50%; emulsion stability index (ESI): 49.32%), attributed to synergistic interactions between proteins and polysaccharides. Overall, this work provides new insights into how processing conditions influence the chemical composition and molecular structure, which fundamentally govern the rheological and functional performance of CSM. These findings underscore its potential as a versatile hydrocolloid for food and biomedical applications. Full article

Fungi are the main causative agents of plant diseases and are responsible for substantial and recurrent damage to agricultural systems. Their activity causes significant reductions in crop productivity and food quality, ultimately contributing to plant deterioration and economic losses. It is estimated that phytopathogenic fungi can compromise up to 30% of global agricultural production. To mitigate microbial deterioration, a wide range of control strategies have been employed, with chemical fungicides being one of the most widely used interventions. However, current approaches to fungal control are rapidly transforming owing to the growing prevalence of fungicide resistance, increasingly stringent regulatory frameworks governing chemical applications, and evolving market demands. Taken together, these factors impose new constraints and drive the development of more sustainable alternative options for effective food control. This review examines the diverse strategies used to control fungal diseases in plants, emphasizing advances in biocontrol agents and biofungicides, as well as emerging tools in the molecular biology, genomics, and biotechnology fields. The aim is to highlight recent developments and prospects that can be integrated into comprehensive disease-management approaches. Full article

Aging has a significant influence on the rheological behavior and service performance of asphalt binders. In this study, base asphalt binder (BAB) and rubberized asphalt binder (RAB) with different aging levels were investigated to clarify their aging evolution and performance correlations. Rheological tests were conducted to evaluate high-temperature rutting resistance, intermediate-temperature fatigue performance, and low-temperature cracking resistance. The 2S2P1D viscoelastic model was used to analyze the evolution of viscoelastic parameters, while gel permeation chromatography (GPC) was adopted to characterize molecular weight changes during aging. The results showed that aging increased the rutting resistance of both binders, but reduced fatigue performance and low-temperature cracking resistance. Among the 2S2P1D viscoelastic model parameters, G_∞, δ, and β were more sensitive to aging than the other parameters and exhibited relatively clear variation trends. Selected viscoelastic parameters also showed significant correlations with rheological performance indices. GPC results indicated that both binder systems progressively evolved toward higher molecular weight during aging, with the molecular weight distribution curves shifting toward the high-molecular-weight region. For RAB, M_w was more sensitive to aging than M_n and showed some fluctuation at intermediate aging stages, reflecting a more complex molecular evolution. Overall, the results indicate that selected 2S2P1D viscoelastic parameters can serve as sensitive indicators of aging evolution and provide a useful basis for interpreting the performance correlations and rheological changes of asphalt binders from a viscoelastic perspective. Full article

Background/Objectives: To explore the mechanisms of Hydrangea macrophylla adapting to low light-induced ornamental whitening, this study established treatments involving normal light (CK, 200 μmol·m⁻²·s⁻¹), moderate low light (L1, 100 μmol·m⁻²·s⁻¹), and severe low light (L2, 20 μmol·m⁻²·s⁻¹). Methods: Meanwhile, physiological indicators, including growth, photosynthesis, and antioxidant activity, were assessed, alongside transcriptomic and metabolomic analyses. Results: Results indicate that L1 increased the proportion of leaf whitening area while maintaining plant growth (crown width, biomass), photosynthetic efficiency comparable to CK, and superior to L2. Concurrently, L1 activated a coordinated antioxidant defence system, namely by increasing the activity of key enzymes (e.g., SOD, GR) and the accumulation of protective metabolites (e.g., soluble proteins, total phenolics and total flavonoids), thereby minimising oxidative damage (low MDA). Multi-omics analyses revealed that L1 specifically activated these networks associated with carbon assimilation, energy metabolism, secondary metabolite synthesis, and hormone signalling, indicating a systemic molecular mechanism towards enhanced defence. Conclusions: In summary, moderate low light triggers a synergistic molecular network involving enhanced antioxidant defences and secondary metabolism, enabling H. macrophylla to maintain overall physiological homeostasis and healthy growth while exhibiting ornamental whitening phenotypes, thereby revealing a unique aesthetic adaptation mechanism to environmental stress. Full article

In recent years, plant stress biology has moved beyond single-pathway descriptions toward an integrated framework in which stress perception, hormonal control, and gene regulation are tightly interconnected. Early events such as membrane-associated sensing, calcium influx, reactive oxygen species (ROS) generation, and kinase activation converge with phytohormonal networks to shape context-dependent responses. Within this framework, abscisic acid, salicylic acid, jasmonates, ethylene, auxin, cytokinins, gibberellins, brassinosteroids, and strigolactones function not as isolated regulators but as components of a dynamic signaling matrix that balances survival, defense, growth restraint, and recovery. These hormonal signals are ultimately translated into adaptive outcomes through extensive transcriptional and post-transcriptional reprogramming mediated by transcription factors, RNA-based regulators, chromatin remodeling, and stress memory mechanisms. This review synthesizes current understanding of how plants integrate stress perception, phytohormonal crosstalk, and transcriptional regulation to establish stress tolerance. We first examine the molecular basis of stress sensing and early signaling. We then discuss the central functions of major phytohormones and the logic of hormone–hormone interaction networks in coordinating stress adaptation. Next, we analyze transcriptional, post-transcriptional, and epigenetic mechanisms that determine response specificity, intensity, and persistence. We further highlight points of convergence between abiotic and biotic stress responses and discuss how combined stresses challenge traditional single-stress models. Finally, we consider the roles of omics, systems biology, and translational technologies in decoding and engineering stress-resilient phenotypes. By integrating these perspectives, this review presents plant stress tolerance as a multilevel systems property and outlines key priorities for future research aimed at developing climate-resilient crops. Full article

Background/Objectives: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality and is characterized by substantial molecular heterogeneity, including epigenetic dysregulation. Histone acetylation, regulated by histone acetyltransferases and histone deacetylases (HDAC), has been implicated in CRC development and progression. The aim of the present study was to evaluate HDAC-2 expression in CRC and investigate its association with clinicopathological parameters and patient outcomes. Methods: In this retrospective study, tumor tissue samples from 77 patients with CRC and documented recurrence were examined. HDAC-2 expression was assessed by immunohistochemistry and classified as low or high using a semi-quantitative scoring system. Associations with clinicopathological parameters and survival outcomes (disease-free survival, DFS; overall survival, OS) were analyzed. Results: High HDAC-2 expression was associated with younger patient age and earlier disease recurrence, while its association with overall survival was borderline. Conclusions: HDAC-2 expression may have clinicopathological relevance in CRC, particularly in relation to recurrence-related outcomes, although larger studies are needed to confirm its prognostic significance. Full article

Background: The global healthcare system faces a significant challenge due to the escalating prevalence of type 2 diabetes, affecting over 10% of the world’s population. Suppression of postprandial hyperglycemia through inhibition of carbohydrate-hydrolyzing enzymes is an effective therapeutic strategy. Although curcumin effectively inhibits α-amylase and α-glucosidase activities, its lower solubility and bioavailability restrict its clinical application. In this study, five mono-carbonyl curcumin analogues (CA1–CA5) were synthesized and evaluated for their antidiabetic potential following selective experimental methods both in vitro, and in vivo. Enhanced delivery for the most potent analogue was achieved through PEGylated graphene oxide (PEG-GO) to overcome the shortcomings of curcumin compounds. Methods: In silico ADME profiling was conducted using SwissADME, and molecular docking studies were performed with AutoDock Vina (v1.5.7) to assess enzyme binding interaction. The synthesized compounds were further evaluated using in vitro α-amylase and α-glucosidase inhibition assays, followed by in vivo blood profile analysis. The most active analogue CA3 (chloro derivative) was loaded onto PEG-GO and characterized using UV–visible spectroscopy, Fourier-transform infrared spectroscopy, and scanning electron microscopy. Results: Among all of the compounds, CA3 exhibits the strongest binding affinity and highest enzyme inhibitory activity, followed by CA2 and CA4. PEG-GO-CA3 demonstrated significantly enhanced biological activity compared to its free form. In vivo studies showed marked improvements in body weight and lipid profile, along with significant reductions in blood glucose, glycated hemoglobin, urea, creatinine, alanine aminotransferase, and aspartate aminotransferase levels over a 28-day treatment period as compared to a diabetic control. Spectroscopic and morphological analyses confirmed successful loading of CA3 onto PEG-GO (27.7–31.5%) with a release profile of 38–57% after 12 and 36 h in a controlled environment at pH 7. Conclusions: These findings suggest that PEG-GO-loaded mono-carbonyl curcumin analogues represent promising therapeutic candidates for the management of T2DM. Full article

Background: Gliomas are the most common malignant brain tumors in adults, characterized by a poor prognosis. Although the current World Health Organization (WHO) classification provides clear guidelines for classifying oligodendroglioma, astrocytoma, and glioblastoma patients, significant heterogeneity persists within each class, limiting the effectiveness of current treatment strategies. With the increasing availability of large-scale multi-omics datasets resulting from advancements in sequencing technologies and online repositories that provide them, such as The Cancer Genome Atlas (TCGA), it is now possible to investigate these tumors at multiple molecular levels. Methods: In this work, we apply integrative multi-omics analysis to explore the interplay between genomic (mutations), epigenomic (DNA methylation), and transcriptomic (mRNA and miRNA) layers. Our approach relies on Multi-Omics Factor Analysis (MOFA), a Bayesian latent factor analysis model designed to capture sources of variation across different omics types. Results: Our results highlight distinct molecular profiles across the three glioma types and identify potential relationships between methylation and genetic expression. In particular, we uncover novel candidate biomarkers associated with survival as well as a transcriptional profile associated with neural system development. Conclusions: These findings may contribute to more personalized therapeutic strategies, potentially improving treatment effectiveness and survival outcomes in this disease. Full article

Liver cancer remains a significant global health burden, requiring the development of precise nucleic acid delivery systems. Lipid nanoparticles (LNPs) are leading candidates; however, their efficiency is governed by the pK_a of ionizable lipids, which dictates nanoparticle stability and endosomal escape. In this study, we employed a machine learning–driven quantitative structure–activity relationship framework to predict the pK_a of ionizable lipids derived from the DLin–KC2–DMA scaffold. Utilizing a dataset of 56 compounds, we compared Random Forest, Artificial Neural Network, and Extreme Gradient Boosting (XGB) models integrated with Permutation Importance (PI) for feature selection. The optimized PI–XGB model exhibited exceptional predictive accuracy (R² = 0.970, R²_CV = 0.901, RMSE_test = 0.115) and robust generalization confirmed via external validation (RMSE_ext. = 0.313). Mechanistic insights derived from SHapley Additive exPlanation analysis identified charge distribution, molecular topology, and polarity as critical determinants of lipid ionization. These results demonstrate the power of interpretable machine learning in elucidating molecular structure–property relationships, offering a robust computational strategy for the rational design of next–generation ionizable lipids to optimize LNP–mediated gene therapy for liver cancer. Full article

Polybrominated diphenyl ethers (PBDEs), widely used as brominated flame retardants, are known to exert persistent adverse effects on the immune systems of humans and other organisms. Previous studies have demonstrated that 2,2′,4,4′-tetrabromodiphenyl ether (BDE-47), a prevalent congener, induces apoptosis, impairs phagocytic function, and triggers aberrant immune-inflammatory reactions in RAW264.7 macrophages via the induction of elevated intracellular reactive oxygen species (ROS). However, the underlying regulatory mechanism remains unclear. The nuclear factor erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE) signaling pathway is a key cellular defense system against oxidative stress. In this study, we investigated the role of the Nrf2/ARE pathway in BDE-47-induced macrophage immunotoxicity. Network toxicology analysis identified Nrf2 as a hub gene within the BDE-47-associated immunotoxicity network. Molecular docking and molecular dynamics simulations suggested a potential interaction between BDE-47 and the Keap1-Nrf2 complex, with moderate binding affinity. Experimental studies in RAW264.7 cells showed that BDE-47 exposure activated the Nrf2/ARE pathway, as evidenced by Nrf2 nuclear translocation and the differential upregulation of downstream genes (GCLC, GCLM, HO-1, NQO1, SOD1, and CAT). Importantly, Nrf2 knockdown via lentiviral shRNA or pharmacological inhibition with brusatol significantly exacerbated BDE-47-induced apoptosis and immune dysfunction, including enhanced pro-inflammatory cytokine production and impaired phagocytosis. These results demonstrate that Nrf2/ARE pathway activation represents an adaptive antioxidant response and contributes to limiting BDE-47-induced cytotoxicity and immune impairment in macrophages. Full article

Fluorosis, a systemic condition caused by chronic excessive fluoride intake, poses significant threats to livestock health and agricultural productivity worldwide. This systematic review synthesizes current evidence on the modulatory effects of exercise against fluorosis, integrating human studies, animal experiments, and methodological considerations. Human studies indicate negative associations between fluoride exposure and cognitive development, muscle function, and exercise capacity, with exercise influencing fluoride pharmacokinetics in an exercise-intensity-dependent manner. Animal experiments consistently demonstrate that regular moderate-intensity exercise attenuates fluoride-induced damage across multiple organ systems through activation of the Nrf2/ARE antioxidant pathway, modulation of BMP-2/Smads and OPG/RANKL/RANK signaling, suppression of inflammatory responses, and preservation of intestinal barrier integrity. Substantial heterogeneity exists among current fluorosis models regarding exposure dosages, durations, and exercise protocols, underscoring the need for standardization and consideration of genetic background. Overall, exercise shows promise for mitigating fluorosis-induced multi-organ damage, although human evidence remains limited. Future research should prioritize model optimization, elucidation of molecular targets, and exploration of synergistic interventions to provide a foundation for veterinary clinical management. Full article

Type II toxin–antitoxin (TA) systems are significantly expanded in the Mycobacterium tuberculosis complex; however, the functional role of the VapBC40 system in Mycobacterium bovis(M. bovis) pathogenesis remains poorly characterized. This study aimed to investigate the role of VapBC40 in mycobacterial virulence and evaluate its potential as a target for rational vaccine attenuation. We performed evolutionary analysis and yeast two-hybrid assays to characterize VapBC40 system specificity, conducted in vitro macrophage infection models and in vivo murine studies to assess virulence contribution, and evaluated the immunoprotective efficacy of a VapC40 knockout strain. Evolutionary analysis revealed progressive sequence conservation and stringent homologous pairing specificity within the VapBC40 system. The VapC40 toxin correlates with enhanced intracellular bacterial survival, increased host cell death, and more severe pulmonary pathology with systemic dissemination. Based on these findings, we evaluated the vaccine potential of a vapC40 knockout strain. Immunization with this attenuated strain elicited a Th1 cellular immune response, characterized by enhanced IFN-γ production and increased frequency of CD4⁺IFN-γ⁺ T cells. Upon challenge with virulent M. bovis, the knockout strain conferred superior protection compared to the conventional BCG vaccine, significantly reducing lung pathology and restricting extrapulmonary bacterial dissemination. Although the molecular mechanisms underlying VapC40-mediated effects remain to be fully elucidated, our findings suggest an important role of the VapBC40 system in mycobacterial-host interactions and support its potential as a target for next-generation tuberculosis vaccine development. Full article

Computational chemistry has played a central role in early-stage drug discovery by accelerating target selection, hit identification, and lead optimization. This review summarizes recent developments in molecular docking, pharmacophore modeling, molecular dynamics (MD), and virtual screening (VS), with a focus on their application in practical drug discovery workflows. Advances in docking protocols, including consensus scoring, physics-based rescoring, and ensemble approaches, addressed the challenges of receptor flexibility. Both ligand-based and structure-based pharmacophore models facilitated scaffold hopping and guided library prioritization. MD simulations were used to assess binding pose stability, identify cryptic binding pockets, and characterize solvent interactions. These simulations also supported free-energy calculations using endpoint and alchemical methods. Large-scale VS campaigns employed curated compound libraries, often composed of make-on-demand molecules, and relied on high-performance computing or cloud infrastructure to screen up to 10⁹ compounds. Hits were validated using orthogonal biophysical assays and filtered by absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions. Integrated pipelines combining pharmacophore modeling, docking, MD, and free-energy calculations improved enrichment rates and reduced the number of compounds requiring synthesis. Several case studies demonstrated the identification of nanomolar-affinity leads from ultra-large screening campaigns. The review also addressed ongoing challenges, such as inconsistent scoring of binding affinity, protonation, and tautomeric errors, dataset bias, and reproducibility issues. Strategies to mitigate these limitations included standardized library preparation, adherence to FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, and the use of prospective benchmarking protocols. The review discussed emerging trends, including the use of quantum chemistry for electronic structure refinement, ensemble docking guided by cryo-electron microscopy (cryo-EM) data, and the integration of computational tools with automated synthesis and high-throughput screening in closed-loop discovery systems. These approaches have the potential to accelerate the design–make–test cycle, increase hit novelty, and improve decision-making in early drug development programs. Full article

Epigenetic mechanisms profoundly regulate gene expression, developmental trajectories, and phenotypic variation, extending biological influence beyond DNA sequence alone. A growing body of evidence suggests that environmental exposures, including pollutants, drugs, stress, and diet, can induce germline and early embryonic epimutations that alter developmental programs with lasting consequences for neurodevelopmental and cognitive outcomes. However, the fields most relevant to these processes have largely developed independently. These include germline epigenetics, early embryonic patterning, neurodevelopment and cognitive regulation, and intergenerational or transgenerational inheritance. Each field has its own conceptual frameworks and mechanistic models. This fragmentation obscures the biological reality that these systems are tightly interconnected: environmentally induced epigenetic perturbations in gametes can reshape the epigenetic landscape of the early embryo, influence lineage allocation during gastrulation, and ultimately modify the molecular architecture of the developing central nervous system. A systems–biology perspective capable of linking germline epimutations and early embryonic epigenetic instability to later neurodevelopmental and cognitive phenotypes and their potential inheritance is therefore required. This review synthesizes current evidence across these traditionally isolated domains and proposes a coherent mechanistic framework linking germ cell epimutations and early embryonic epigenetic instability to the emergence of neurodevelopmental and cognitive phenotypes. By bridging these conceptual gaps, we aim to establish a cohesive foundation for understanding how early epigenetic disruptions generate long-lasting and in some cases heritable effects on brain development and cognitive function. Full article

Easier measurement of 17β-estradiol could promote the early diagnosis and treatment of medical conditions in women. In this study, we developed a fluorescence-based assay using a nucleic acid aptamer labeled with a fluorescent dye for the detection of estrogen. Upon binding to 17β-estradiol, the aptamer undergoes a conformational change, resulting in a measurable change in fluorescence intensity. The assay enables rapid detection within 30 min, with a limit of detection of 0.2 pg/mL and a linear dynamic range of 1 pg/mL–1000 pg/mL. High selectivity toward 17β-estradiol was confirmed against structurally related compounds. The method was successfully applied to human saliva samples, demonstrating high sensitivity, precision, and reproducibility with recoveries of 98.8% and coefficients of variation below 3.0%. In addition, a compact desktop fluorescence detector was developed, allowing direct measurement in polymerase chain reaction tubes without sample transfer, thereby simplifying the procedure and minimizing sample loss. These results demonstrate that the proposed system provides a simple and practical platform for estrogen detection in biological samples and has potential applications in clinical and research settings. Full article