Search Results (1,163)

Although the development of fermented plant-based milk alternatives has become quite popular, the relatively low nutritional value and functional properties of these products present significant challenges. This situation is driving the search for alternative protein sources to improve the quality of plant-based products, and legume proteins are attracting attention as promising components. Accordingly, this study aimed to enrich oat-based vegan yogurt alternatives with different legume protein isolates and evaluate their effects on product quality. In the present study, physicochemical, microbiological, antioxidant capacity, FAA profile, peptide profile, and FTIR analyses were performed on vegan yogurts produced using oat milk as well as mung bean and black bean protein isolates. It was determined that different plant protein isolates used in vegan yogurt production had a statistically very significant (n = 2, p < 0.01) effect on dry matter, protein, pH, L. acidophilus, antioxidant capacity, and all FAA profiles except asparagine and aspartic acid. The addition of legume protein isolates to vegan yogurts contributed to an increase in dry matter content (11.57–14.14%), protein content (2.92–5.20%), ash content (0.22–0.32%), and pH value (4.49–4.59) compared to the control group. Similar effects were also observed in S. thermophilus count (5.79–6.38 log cfu/g), L. delbrueckii subsp. bulgaricus count (5.72–6.43 log cfu/g), DPPH inhibition (10.29–19.93%), and ABTS inhibition (14.66–28.48%). It was determined that the addition of mung bean protein isolate (MBPI-2 and MBPI-4), compared to black bean protein isolate, contributed more to nutritional properties in vegan oat yogurt samples. Vegan yogurts were found to match more frequently with antioxidant, ACE inhibitor, DPP III, and DPP IV inhibitor activity in potential bioactivity predictions. FTIR analysis revealed that using different legume protein isolates in vegan yogurt production did not result in the formation of new absorption bands, but it did affect the intensity of existing regional bands. In conclusion, the addition of different legume protein isolates to oat yogurt was found to generally contribute positively to the parameters examined and represents a promising approach for individuals who cannot consume cow milk due to health problems, as well as for vegans. Full article

In forensic toxicology, the analysis of blood and urine is regarded as the so-called “gold standard.” However, when forensic experts are confronted with advanced postmortem changes, it becomes necessary to secure and examine alternative matrices. Suitable specimens in cases of advanced putrefactive decomposition may include: skin appendages (hair and nails), bones, bone marrow, cartilage tissue, teeth, antemortem fingerprints, cerebrospinal fluid, vitreous humor, breast milk, meconium, placenta and umbilical cord tissue, oral fluid, sweat, and other evidentiary materials. These tissues, owing to their structure and anatomical location, are more resistant to putrefactive decomposition than body fluids and soft tissues. However, several limitations complicate the reliable analysis of these matrices. These include incomplete drug incorporation, depending on physicochemical properties, the inability to correlate analyte concentrations with pharmacological effects, low xenobiotic levels, and the need for highly sensitive analytical methods. Collectively, these factors contribute to interpretative challenges during forensic expert evaluation and reporting. To address key forensic questions, epigenetic variability analyses (forensic epigenetics) may also be employed, particularly when standard DNA profiling is uninformative. DNA methylation patterns in specific tissues and in individual subjects can be used, among other purposes, to identify the tissue of origin of a human biological trace, to differentiate monozygotic twins, and to predict the age of an unidentified trace donor. Over the past few years, this approach has gained increasing importance; in the context of forensic trace analysis, it offers both advantages and limitations. The aim of this study is to present current scientific evidence regarding the use of alternative biological matrices as potential sources of information of forensic relevance. The paper discusses the characteristics of individual biological materials, with particular emphasis on their analytical properties, potential applications, limitations, and possible advantages in forensic toxicological investigations. Furthermore, the key aspects associated with the application of epigenetic methods in forensic science are presented, with particular focus on their role in individual identification and the reconstruction of circumstances surrounding forensic events. Alternative biological matrices and modern analytical approaches may constitute valuable complementary tools to conventional evidentiary materials used in forensic medicine and criminalistics. Due to their physicochemical properties, stability, and ability to preserve specific biological information, these matrices may provide significant data that enable substance identification, assessment of exposure to psychoactive compounds, reconstruction of event circumstances, and support for identification procedures. However, their application requires consideration of analytical limitations, the specific characteristics of the examined matrix, and the necessity for standardization and validation of diagnostic procedures Full article

Background: Plant-derived virus-like particles (VLPs) are emerging nanoplatforms for local cancer immunotherapy, yet their relative performance across structurally distinct particles remains insufficiently defined. Methods: We performed a comparative benchmarking study of eleven plant-derived VLPs spanning diverse architectures and functional properties using an integrated workflow of physicochemical characterization, immune-functional profiling, and in vivo evaluation. All VLPs were produced in endotoxin-minimized ClearColi BL21 (DE3), enabling assessment of intrinsic particle-associated immunostimulatory activity with reduced bacterial endotoxin confounding. Results: In vitro, several VLPs stimulated macrophage-associated responses and enhanced tumor cell killing, although classical M1/M2 polarization markers in RAW264.7 cells did not consistently predict functional cytotoxicity. In a subset of candidates, HEK-TLR3 reporter activity varied substantially under RNA-normalized conditions and was not predicted solely by total RNA content or apparent RNA size distribution. Five candidates were advanced to intratumoral evaluation in the male-derived B16-F10 melanoma model, where CCMV-ss and CMVtt showed trends toward reduced tumor progression and increased immune cell infiltration in male mice. Furthermore, host sex-associated differences in baseline immune features were observed, though these must be interpreted with caution given the H-Y antigen-driven immunogenicity inherent to the male-derived B16-F10 model in female hosts. Conclusions: This study establishes a standardized comparative framework linking plant VLP properties with immune-functional performance and identifies CCMV-ss and CMVtt as promising candidates for further development as locally administered cancer immunotherapy nanoplatforms. Full article

Yellow River sediment is a promising resource for use in construction materials. However, the effects of Yellow River silt and sand in different applications remain unclear. This review examines the physicochemical properties of these two forms, their engineering applications, and the underlying mechanisms governing material performance. Yellow River sand is mainly used as a fine aggregate in conventional concrete, engineered cementitious composites (ECC), and cement mortar, whereas Yellow River silt is commonly used in subgrade fills, concretes incorporating multiple solid wastes, and building products. Across these applications, the behavior of Yellow River sediment in construction materials reflects both physical packing and chemical reactivity. Their relative contributions depend on sediment form, material system, processing condition, and sediment content. Chemical reactivity is observed mainly in systems containing Yellow River silt, although the contribution of the silt itself has not been isolated. In conventional concrete, the highest compressive strengths are generally observed when Yellow River sand replaces 10–30% of natural sand, but the exact level depends on mixture design. Regional differences in sediment composition further limit the direct transfer of this range and require evaluation based on target performance. Future research should develop predictive models linking sediment characteristics, content, and target performance, establish low-carbon activation methods, and clarify long-term durability under complex service conditions. Full article

Deep eutectic systems (DESs) have evolved from sustainable solvent alternatives to promising bioactive platforms with reported antimicrobial, anti-inflammatory, regenerative, cryoprotective, and cytoprotective properties. However, despite the growing number of biological studies, the mechanistic basis of these effects remains poorly understood because biological activity is still interpreted predominantly from the chemical identity of the hydrogen-bond donor and acceptor, rather than from the supramolecular organization of the eutectic system itself. This review is intended to provide anyone interested in the biomedical and pharmaceutical applications of DESs with a conceptual framework for understanding how supramolecular organization may influence the biological performance of DES-based systems, without requiring extensive expertise in physical chemistry. It critically analyzes the current evidence linking DES structure with biological function. The literature reveals that many reported biological responses cannot be fully explained by the properties of the individual constituents alone, supporting the existence of emergent physicochemical behavior associated with eutectic formation. Current evidence further demonstrates that DESs are dynamic supramolecular systems characterized by hydrogen-bond networks, nanoscale heterogeneity, hydration-dependent structural rearrangement, and persistent local organization under biologically relevant conditions. These structural features generate localized physicochemical microenvironments capable of modulating membrane organization, protein hydration, osmotic balance, and biomolecular interactions, providing a plausible mechanistic basis for the diverse biological effects reported to date. Our analysis also highlights a fundamental disconnect between the extensive physicochemical characterization of DESs and the predominantly composition-based interpretation of their biological activity. While conventional Quantitative Structure–Activity Relationship (QSAR) approaches rely on molecular descriptors of individual components, they fail to capture the higher levels of organization that characterize these dynamic multicomponent systems. Based on concepts established in supramolecular chemistry, self-assembled biomaterials, colloidal science, and soft matter, we propose a Hierarchical Structure–Activity Relationship (H-SAR) framework in which biological activity emerges from successive levels of organization extending from molecular composition and hydrogen-bond networks to nanostructural organization, hydration-dependent restructuring, localized physicochemical microenvironments, and biological interfaces. This framework provides a mechanistic basis for interpreting DES bioactivity and could offer a conceptual roadmap for the rational design, predictive modeling, and biomedical translation of next-generation bioactive deep eutectic systems. Full article

Sacha inchi (Plukenetia volubilis L.) leaves are an underutilized by-product of an expanding oilseed crop, yet their use as a food ingredient remains limited. This study evaluated sacha inchi tea leaf powder (STLP) as a partial replacement for wheat flour in cookies at 0%, 2.5%, 5%, and 10% (w/w), and examined the physicochemical properties, antioxidant capacity, in vitro starch digestibility, and sensory acceptability of the cookies. Substitution with STLP significantly increased the protein, dietary fiber, and ash contents of the cookies (p ≤ 0.05). Total phenolic content and ferric-reducing antioxidant power also increased with the substitution level, particularly at 5% and 10% STLP (p ≤ 0.05). In the simulated digestion model, STLP-substituted cookies showed lower glucose release, glucose area under the curve, hydrolysis index, and predicted glycemic index than the control (p ≤ 0.05), indicating reduced starch hydrolysis in vitro. Physical properties were largely maintained at low to moderate substitution levels, whereas 10% STLP increased spread ratio and hardness, and reduced baking loss. Sensory evaluation showed that STLP substitution lowered appearance, color, smell, flavor, and overall acceptability scores compared with the control, while texture scores were not significantly affected. These findings suggest that STLP may be used as a potential ingredient to improve protein, fiber and ash contents, enhance antioxidant properties of cookies, and reduce in vitro starch hydrolysis. Although further formulation optimization is needed to balance these effects with sensory acceptability, STLP is a promising functional ingredient for bakery products and a means of valorizing an underutilized agricultural material. Full article

Triple-negative breast cancer (TNBC) is the most clinically aggressive subtype of breast cancer, characterized by the absence of targetable hormone receptors and HER2 amplification, significantly constraining treatment choices. Estrogen Receptor Beta (ERβ) has emerged as a biologically relevant yet underutilized target in TNBC, with its re-expression linked to tumor suppression and improved prognosis, prompting the development of selective ERβ modulators as a precision therapeutic approach. We introduce ERβ-Score, an interpretable machine learning scoring system developed using a curated dataset of 1699 ERβ bioactive chemicals obtained from ChEMBL, characterized by 39 physicochemical and three-dimensional molecular descriptors. After implementing scaffold-disjoint train/test partitioning to avert structural data leakage, a Gradient Boosting Classifier, fine-tuned through Bayesian hyperparameter optimization, attained in five-fold cross-validation a Precision–Recall AUC (Area Under the Curve) of 0.891, a ROC-AUC (Receiver Operating Characteristic) of 0.888, a Matthews Correlation Coefficient of 0.664, an F1-score of 0.838, and a balanced accuracy of 0.831; on the scaffold-disjoint hold-out test set it attained a Precision–Recall AUC of 0.905, a ROC-AUC of 0.864, and a Matthews Correlation Coefficient of 0.578, indicating strong and balanced discrimination between active and inactive ERβ modulators. We note explicitly that this scaffold-disjoint hold-out constitutes internal validation, since it derives from the same curated ChEMBL workflow used for model development, and it is therefore reported throughout as scaffold-disjoint internal validation rather than as independent external validation. The applicability domain boundaries were established using a k-nearest-neighbor Tanimoto-similarity method with ECFP4 (Extended-Connectivity Fingerprint with a Diameter of 4) fingerprints, offering a quantitative confidence metric that identifies structurally new molecules beyond the model’s reliable prediction range. External validation against independent Tox21 ERβ bioassay data confirmed genuine, statistically significant predictive signal (ROC-AUC = 0.71) while revealing reduced sensitivity for structurally novel active compounds. The model was subsequently used for extensive virtual screening of natural product and drug-like compound libraries, with prioritized candidates undergoing structure-based molecular docking against the ERβ co-crystal structure (PDB: 7XWQ) using Smina, facilitating a comprehensive evaluation of hits based on both ligand and structural properties. To enhance accessibility, the complete pipeline was implemented as an open-access interactive web application utilizing Streamlit, enabling researchers to input any SMILES string and obtain, in real time, an activity prediction with a probability score, applicability domain classification, Lipinski drug-likeness assessment, interactive three-dimensional visualization of protein–ligand interactions, and on-demand docking within the ERβ active site. Full article

Background/Objectives: Rules for predicting blood–brain barrier (BBB) permeability, including the CNS multiparameter optimization (CNS MPO) score, Lipinski’s Rule of Five, and Veber’s rules, were developed using relatively limited datasets and have not been systematically re-evaluated using modern large-scale experimental databases. Using the B3DB database, which contains 1058 experimentally measured logBB values, we derived quantitative, data-driven structural thresholds for BBB permeability and benchmarked them against established heuristic rules. Methods: Six key physicochemical properties were calculated for all compounds, and optimal classification thresholds were identified through exhaustive optimizations. Decision trees and scaffold analyses were used to generate interpretable medicinal chemistry guidelines. Results: The topological polar surface area (TPSA) emerged as the strongest single predictor of BBB permeability, with an optimal threshold of 66.8 Ų (AUC = 0.731, 95% CI: 0.689–0.771). This threshold outperformed the approximated CNS MPO ≥ 4 (AUC = 0.625), Lipinski’s Rule of Five (AUC = 0.546), and Veber rules (AUC = 0.566). A simple two-parameter rule combining TPSA < 67 Ų and H-bond donors ≤ 1 achieved 96.6% precision for BBB-permeable compounds while maintaining an AUC of 0.720. Decision tree analysis further confirmed TPSA as the dominant determinant of BBB permeability, whereas scaffold analysis identified the molecular frameworks associated with highly permeable and impermeable compounds. External validation provided preliminary support for the improved specificity of the proposed rule, compared with existing approaches. Conclusions: These findings suggest that the commonly applied TPSA threshold of 90 Ų may be overly lenient. A data-driven threshold of approximately 67 Ų substantially improved the discrimination of BBB permeability across the entire dataset. Compounds with TPSA values between 67 and 90 Ų should be assessed on a case-by-case basis, considering the ionization state and active transport potential, rather than being automatically classified as BBB-permeable. These experimentally grounded rules offer a practical framework for the early-stage design of CNS leads. Full article

Sweet basil (Ocimum basilicum L.), the defining ingredient of “pesto alla Genovese”—a traditional uncooked Ligurian sauce prepared by blending fresh basil leaves with olive oil, pine nuts, garlic, salt, and aged cheeses- has become an increasingly important industrial raw material, yet current knowledge remains fragmented across agronomy, postharvest physiology, and food processing. This review critically proposes “raw material functionality” as an integrative framework describing the measurable ability of basil to retain the physicochemical, sensory, and technological properties required for high-quality pesto production throughout processing and storage. Evidence from the literature is critically analyzed to connect preharvest factors, postharvest handling, and processing technologies with key functional attributes, including pigment stability, phenolic content, volatile composition, enzymatic activity, microbial quality and oxidative stability. The review highlights how agronomic and technological variables jointly determine color retention, aroma preservation, shelf-life, and product consistency, while identifying major knowledge gaps in linking basil composition with industrial performance. Finally future perspectives are discussed, emphasizing predictive, quality-by-design approaches that integrate compositional markers with processing behavior and shelf-life outcomes to support more consistent and sustainable industrial pesto production. Full article

Hantaviruses, the etiological agents of hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS), represent a high-risk zoonotic threat with substantial global health impact. Currently, there is no FDA-approved vaccine. The viral surface glycoprotein (GP) is crucial for host cell entry and is regarded as a key target for vaccine development. However, its variability among hantavirus species limits the effectiveness of conventional vaccine strategies. Epitope-based vaccines offer a promising alternative by enabling the design of broadly protective constructs. In this study, we applied immunoinformatics approaches to design a universal multi-epitope vaccine candidate targeting both HFRS- and HPS-associated hantaviruses through a multi-layered workflow integrating B-cell and T-cell epitope prediction, antigenicity scoring, IFN-γ induction potential, conservation analysis, and population coverage assessment. Viral GPs from SEOV, PUUV, SNV, and ANDV were analyzed using algorithms for B-cell and T-cell epitope prediction. Predicted epitopes were assessed for allergenicity, toxicity, conservation, and population coverage. Two vaccine constructs incorporating β-defensin or 50S ribosomal protein L7/L12 as adjuvants were assessed for physicochemical properties, structural stability and immunogenic potential. Molecular docking analyses provided exploratory ectodomain-compatibility screening, suggesting potential interactions with TLR4 that require future experimental confirmation. The in silico immune simulations suggested potential robust and long-lasting responses with memory cell persistence exceeding one year. Simulations also indicated balanced humoral and cellular responses, robust antibody production, and long-term memory formation suggestive of durable protective immunity. These findings support the rational design of broad-spectrum multi-epitope vaccines against genetically diverse hantaviruses, offering a rational framework for preclinical development of next-generation universal vaccines against hantavirus-associated diseases. Full article

A strategy based on the hyperbranched polyol process (HB-polyol process) is presented for the synthesis of hemocompatible cobalt nanocomposites Co/G_nOH with controlled morphology and predictable functional properties. Third-generation (G₃OH) and fourth-generation (G₄OH) hyperbranched polyester polyols were used as smart polyol nanoreactors. We establish, for the first time, the fundamental physicochemical principles of the HB-polyol process based on a comprehensive analysis of FT-IR, UV-Vis, NMR, NTA, and TEM data. These principles encompass the stages of pre-organization, nucleation, polyol oxidation and the stabilization of cobalt-loaded metallopolymer nanocomposites within the binary [CoCl₂–G_nOH] system (n = 3, 4). Magnetic measurements revealed that the samples exhibit paramagnetic properties at 5 K. The size of the magnetic cores in the Co/G₃OH samples was estimated by fitting the field-dependent magnetization curves to the Langevin function and was found to range from 1.4 nm to 7.2 nm, indicating the superparamagnetic behavior of the nanocomposites. In vitro biological tests of the Co/G_nOH nanocomposites demonstrated high hemocompatibility, as well as pronounced modulatory and antimycotic activity across all samples. The obtained results hold promise for the development of simple design technologies for multifunctional “intelligent” materials based on metal and dendritic nanoparticles for biomedical applications. Full article

This study investigated the repurposing potential of clomiphene citrate as a topical therapeutic candidate for tegumentary leishmaniasis (TL) and candidiasis. Comparative in silico analyses were performed to evaluate absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties in comparison with meglumine antimoniate and amphotericin B. In addition, molecular docking was conducted to investigate the interaction of clomiphene with Leishmania spp. arginase and the Sap5 protease of Candida albicans. Clomiphene exhibited a favorable physicochemical profile, characterized by high lipophilicity, moderate skin permeability, and predicted oral bioavailability and intestinal absorption superior to those of the reference drugs. Toxicological predictions also indicated a lower systemic toxicity profile compared with conventional therapies. Molecular docking revealed favorable binding energies and interactions with key residues within the active sites of both targets. Experimental assays demonstrated that clomiphene inhibited the early stages of C. albicans biofilm formation and exhibited potent leishmanicidal activity against L. amazonensis promastigotes, with a high selectivity index in macrophages. Together, these findings indicate that clomiphene citrate represents a promising candidate for further investigation as a potential therapeutic agent against tegumentary leishmaniasis and candidiasis. Full article

The solid-state landscape of pharmaceutical compounds is often characterized by the occurrence of polymorphs, hydrates, and solvates, which may significantly influence their physicochemical and biopharmaceutical properties. In contrast, some active pharmaceutical ingredients exhibit a remarkable resistance to crystal form diversification, despite extensive experimental investigation. In the present work, vinpocetine was subjected to an extensive solid-form screening campaign aimed at exploring its propensity to generate alternative polymorphs, hydrates, and solvates. Mechanochemical experiments were performed under neat grinding and liquid-assisted grinding conditions using a broad range of organic solvents and water, including two-step milling procedures and formulations containing surfactants. Additional investigations included high-energy planetary milling, high-pressure compaction, exposure to controlled humidity, thermal cycling, slurry-bridging experiments in various media, and crystallization after mechanochemical neutralization of vinpocetine salts. The resulting solids were systematically characterized by powder X-ray diffraction, and thermal and morphological analyses. In all cases, the recovered solid corresponded to the commercially available crystalline form of vinpocetine, with no evidence of alternative polymorphs, solvates, or hydrates. These results demonstrate the unusual robustness of vinpocetine crystal structure across a wide range of mechanical, thermal, and solvent-mediated conditions. Notably, this behavior contrasts with the well-established ability of vinpocetine to form numerous salts and salt cocrystals, suggesting that solid-state diversification in this compound is primarily driven by proton-transfer processes rather than by neutral polymorphism or solvent incorporation. The present study provides experimentally defined boundaries for the solid-state landscape of vinpocetine and contributes valuable data for future crystal-form prediction and pharmaceutical development studies. Beyond the specific findings reported herein, the systematic documentation of both successful and unsuccessful experimental outcomes represents a valuable source of experimentally validated positive and negative data that may support the future development and validation of AI-assisted crystal-form prediction tools. Full article

The production of olive oil inherently involves the handling of various oily fluids which, depending on the stage of the process, may contain impurities capable of affecting the physicochemical and sensory properties of the final product. Considering this, the detection, quantification, and removal of such substances should be prioritised to ensure the production of a high-quality product. Against this background, this study investigates the potential of using smartphones to predict the impurity content (C) in olive oil. Such devices are noteworthy for their ability to capture and analyse images with high precision, offering a viable alternative to conventional colorimeters. The proposed method encompasses sample preparation, the design of a smartphone-compatible image acquisition system, and the processing of colorimetric coordinates using linear estimation models. One of the most notable findings of this research is that the present approach, which was developed using a low-cost design, is able to estimate the value of the impurity content in oily fluids with an error on the order of 0.07% when C is below 2%. Full article

Rapid estimation of the melt flow index (MFI) is essential for the timely control of industrial polypropylene polymerization because conventional plastometer measurements require offline sampling and introduce analytical delays. This work investigates the physicochemical limits of MFI model transferability using 425 reactor-grade polypropylene production runs spanning homopolymer, random copolymer, and impact copolymer architectures. Principal component analysis (PCA), partial least squares (PLS), PCR-Ridge, Random Forest, Extra Trees, and Gradient Boosting were evaluated using within-pool, repeated five-fold, and product group validation. The latent structure, predictive performance, and dominant process descriptors were strongly architecture-dependent. Hydrogen-related variables remained central to molecular weight control, whereas comonomer descriptors, catalyst and donor variables, hydrodynamic conditions, and second reactor variables gained importance as compositional and morphological complexity increased. Nonlinear ensembles improved prediction within heterogeneous pools, but product group validation still revealed transferability losses when models crossed architecture-dependent process–structure–property domains. Repeated cross-validation and preprocessing sensitivity analyses confirmed that the principal model rankings and architecture-dependent conclusions were stable under resampling and correlation filtering. These results show that the polymer architecture defines a practical applicability boundary for industrial MFI soft sensors and supports architecture-specific or architecture-routed calibration when universal models fail cross-family validation. Full article