Search Results (10,908)

In vitro cartilage explant culture has been used to assess nutraceuticals on cartilage responses to inflammatory stimuli. However, applying extracts of nutraceuticals directly to cartilage explants does not account for effects of digestion and hepatic biotransformation, or selective exclusion of product metabolites from joint fluid by the synovial membrane. The current study produced a simulated biological extract of a common nutraceutical (glucosamine; G_sim) by exposing it to a simulated upper gastrointestinal tract digestion, hepatic biotransformation by liver microsomes, and purification to a molecular weight cut-off of 50 kDa. This extract was then used to condition cartilage explants cultured for 120 h in the presence or absence of an inflammatory stimulus (lipopolysaccharide). Media samples were analyzed for prostaglandin E₂ (PGE₂), glycosaminoglycan (GAG), and nitric oxide (NO). Tissue was digested and analyzed for GAG content and stained for viability. Conditioning of explants with G_sim significantly reduced media GAG in stimulated and unstimulated explants and reduced nitric oxide production in unstimulated explants. These data provide evidence for the value of glucosamine in protecting cartilage from deterioration following an inflammatory challenge, and the model improves applicability of these in vitro data to the in vivo setting. Full article

Avocado (Persea americana), originally from Mesoamerica, has emerged as a focus of intense scientific and industrial interest due to its unique combination of nutritional richness, bioactive potential, and technological versatility. Its pulp, widely consumed across the globe, is notably abundant in monounsaturated fatty acids, especially oleic acid, which can comprise over two-thirds of its lipid content. In addition, it provides significant levels of dietary fiber, fat-soluble vitamins such as A, D, E and K, carotenoids, tocopherols, and phytosterols like β-sitosterol. These constituents are consistently associated with antioxidant, anti-inflammatory, glycemic regulatory, and cardioprotective effects, supported by a growing body of experimental and clinical evidence. This review offers a comprehensive and critical synthesis of the chemical composition and functional properties of avocado, with particular emphasis on its lipid profile, phenolic compounds, and phytosterols. It also explores recent advances in environmentally sustainable extraction techniques, including ultrasound-assisted and microwave-assisted processes, as well as the application of natural deep eutectic solvents. These technologies have demonstrated improved efficiency in recovering bioactives while aligning with the principles of green chemistry. The use of avocado-derived ingredients in nanostructured delivery systems and their incorporation into functional foods, cosmetics, and health-promoting formulations is discussed in detail. Additionally, the potential of native cultivars and the application of precision nutrition strategies are identified as promising avenues for future innovation. Taken together, the findings underscore the avocado’s relevance as a high-value matrix for sustainable development. Future research should focus on optimizing extraction protocols, clarifying pharmacokinetic behavior, and ensuring long-term safety in diverse applications. Full article

Reactive oxygen species (ROS) are often seen solely as harmful byproducts of oxidative metabolism, yet evidence reveals their paradoxical roles in both promoting and inhibiting cancer progression. Despite advances, precise context-dependent mechanisms by which ROS modulate oncogenic signaling, therapeutic response, and tumor microenvironment dynamics remain unclear. Specifically, the spatial and temporal aspects of ROS regulation (i.e., the distinct effects of mitochondrial versus cytosolic ROS on the PI3K/Akt and NF-κB pathways, and the differential cellular outcomes driven by acute versus chronic ROS exposure) have been underexplored. Additionally, the specific contributions of ROS-generating enzymes, like NOX isoforms and xanthine oxidase, to tumor microenvironment remodeling and immune modulation remain poorly understood. This review synthesizes current findings with a focus on these critical gaps, offering novel mechanistic insights into the dualistic nature of ROS in cancer biology. By systematically integrating data on ROS source-specific functions and redox-sensitive signaling pathways, the complex interplay between ROS concentration, localization, and persistence is elucidated, revealing how these factors dictate the paradoxical support of tumor progression or induction of cancer cell death. Particular attention is given to antioxidant mechanisms, including NRF2-mediated responses, that may undermine the efficacy of ROS-targeted therapies. Recent breakthroughs in redox biosensors (i.e., redox-sensitive fluorescent proteins, HyPer variants, and peroxiredoxin–FRET constructs) enable precise, real-time ROS imaging across subcellular compartments. Translational advances, including redox-modulating drugs and synthetic lethality strategies targeting glutathione or NADPH dependencies, further highlight actionable vulnerabilities. This refined understanding advances the field by highlighting context-specific vulnerabilities in tumor redox biology and guiding more precise therapeutic strategies. Continued research on redox-regulated signaling and its interplay with inflammation and therapy resistance is essential to unravel ROS dynamics in tumors and develop targeted, context-specific interventions harnessing their dual roles. Full article

The accurate and effective prediction of PM2.5 concentrations is crucial for mitigating air pollution, improving environmental quality, and safeguarding public health. To address the challenge of strong temporal correlations in PM2.5 concentration forecasting, this paper proposes a novel hybrid model that integrates the Particle Optimization Algorithm (POA) and Variational Mode Decomposition (VMD) with the Long Short-Term Memory (LSTM) network. First, POA is employed to optimize VMD by adaptively determining the optimal parameter combination [k, α], enabling the decomposition of the original PM2.5 time series into subcomponents while reducing data noise. Subsequently, an LSTM model is constructed to predict each subcomponent individually, and the predictions are aggregated to derive hourly PM2.5 concentration forecasts. Empirical analysis using datasets from Beijing, Tianjin, and Tangshan demonstrates the following key findings: (1) LSTM outperforms traditional machine learning models in time series forecasting. (2) The proposed model exhibits superior effectiveness and robustness, achieving optimal performance metrics (e.g., MAE: 0.7183, RMSE: 0.8807, MAPE: 4.01%, R²: 99.78%) in comparative experiments, as exemplified by the Beijing dataset. (3) The integration of POA with serial decomposition techniques effectively handles highly volatile and nonlinear data. This model provides a novel and reliable tool for PM2.5 concentration prediction, offering significant benefits for governmental decision-making and public awareness. Full article

Hyperspectral remote sensing plays a crucial role in guiding and supporting various mineral prospecting activities. Combined with artificial intelligence, hyperspectral remote sensing technology becomes a powerful and versatile tool for a wide range of mineral exploration activities. This study investigates the effectiveness of ensemble learning (EL) algorithms for lithological classification and mineral exploration using EnMAP hyperspectral imagery (HSI) in a semi-arid region. The Moroccan Anti-Atlas mountainous region is known for its complex geology, high mineral potential and rugged terrain, making it a challenging for mineral exploration. This research applies core and heterogeneous ensemble learning methods, i.e., boosting, stacking, voting, bagging, blending, and weighting to improve the accuracy and robustness of lithological classification and mapping in the Moroccan Anti-Atlas mountainous region. Several state-of-the-art models, including support vector machines (SVMs), random forests (RFs), k-nearest neighbors (k-NNs), multi-layer perceptrons (MLPs), extra trees (ETs) and extreme gradient boosting (XGBoost), were evaluated and used as individual and ensemble classifiers. The results show that the EL methods clearly outperform (single) base classifiers. The potential of EL methods to improve the accuracy of HSI-based classification is emphasized by an optimal blending model that achieves the highest overall accuracy (96.69%). The heterogeneous EL models exhibit better generalization ability than the baseline (single) ML models in lithological classification. The current study contributes to a more reliable assessment of resources in mountainous and semi-arid regions by providing accurate delineation of lithological units for mineral exploration objectives. Full article

Hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC) are aggressive malignancies characterized by a poor prognosis and resistance to conventional therapies. Mounting evidence suggests the pivotal role of epithelial–mesenchymal transition (EMT) in tumor progression, metastasis, and therapeutic resistance in these cancers. Protein induced by vitamin K absence II (PIVKA-II)—a valuable HCC detector—has ultimately emerged as a potentially relevant biomarker in PDAC, serving as both a serum biomarker and a prognostic indicator. This study investigates the putative link between PIVKA-II expression and the EMT process in HCC and PDAC. Using a Western blot analysis and electrochemiluminescence immunoassay (ECLIA), we quantified PIVKA-II serum levels alongside two canonical EMT markers—Vimentin and E-cadherin—in selected cohorts. Emerging data suggest a dual, context-dependent role for PIVKA-II. Beyond its diagnostic value in both malignancies, its co-expression with EMT markers points to a potential mechanistic involvement in tumor invasiveness and phenotypic plasticity. Notably, the selective detection of E-cadherin in HCC implies limited EMT activation and a preservation of the epithelial phenotype, whereas the higher expression of Vimentin in PDAC reflects a more substantial shift toward EMT. We provide a comprehensive analysis of key molecular markers, their involvement in EMT-driven pathophysiological mechanisms, and their potential as novel diagnostic tools. Full article

Hypothermia-related deaths present significant diagnostic challenges due to non-specific and often inconsistent autopsy findings. This study investigated the histological and immunohistochemical alterations associated with primary and secondary hypothermia in an experimental Rattus norvegicus model, focusing on the effects of benzodiazepine and alcohol ingestion. Twenty-one male rats were divided into three groups: control (K), benzodiazepine-treated (B), and alcohol-treated (A). After two weeks of substance administration, hypothermia was induced and multiple organ samples were analyzed. Histologically, renal tissue showed hydropic and vacuolar degeneration, congestion, and acute tubular injury across all groups, with no significant differences in E-cadherin expression. Lung samples revealed congestion, emphysema, and hemorrhage, with more pronounced vascular congestion in the alcohol and benzodiazepine groups. Cardiac tissue exhibited vacuolar degeneration and protein denaturation, particularly in substance-exposed animals. The spleen showed preserved architecture but increased erythrocyte infiltration and significantly elevated myeloperoxidase (MPO)-positive granulocytes in the intoxicated groups. Liver samples demonstrated congestion, focal necrosis, and subcapsular hemorrhage, especially in the alcohol group. Immunohistochemical analysis revealed statistically significant differences in MPO expression in both lung and spleen tissues, with the highest levels observed in the benzodiazepine group. Similarly, CK7 and CK20 expression in the gastroesophageal junction was significantly elevated in both alcohol- and benzodiazepine-treated animals compared to the controls. In contrast, E-cadherin expression in the kidney did not differ significantly among the groups. These findings suggest that specific histological and immunohistochemical patterns, particularly involving pulmonary, cardiac, hepatic, and splenic tissues, may help differentiate primary hypothermia from substance-related secondary hypothermia. The study underscores the value of integrating toxicological, histological, and molecular analyses to enhance the forensic assessment of hypothermia-related fatalities. Future research should aim to validate these markers in human autopsy series and explore additional molecular indicators to refine diagnostic accuracy in forensic pathology. Full article

Salmonella serovar identification typically requires multiple enrichment steps using selective media, consuming considerable time and resources. This study presents a rapid, culture-independent method leveraging artificial intelligence (AI) to classify Salmonella serovars from rich hyperspectral microscopy data. Five serovars (Enteritidis, Infantis, Kentucky, Johannesburg, 4,[5],12:i:-) were analyzed from samples prepared using only sterilized de-ionized water. Hyperspectral data cubes were collected to generate single-cell spectra and RGB composite images representing the full microscopy field. Data analysis involved two parallel branches followed by multimodal fusion. The spectral branch compared manual feature selection with data-driven feature extraction via principal component analysis (PCA), followed by classification using conventional machine learning models (i.e., k-nearest neighbors, support vector machine, random forest, and multilayer perceptron). The image branch employed a convolutional neural network (CNN) to extract spatial features directly from images without predefined morphological descriptors. Using PCA-derived spectral features, the highest performing machine learning model achieved 81.1% accuracy, outperforming manual feature selection. CNN-based classification using image features alone yielded lower accuracy (57.3%) in this serovar-level discrimination. In contrast, a multimodal fusion model combining spectral and image features improved accuracy to 82.4% on the unseen test set while reducing overfitting on the train set. This study demonstrates that AI-enabled hyperspectral microscopy with multimodal fusion can streamline Salmonella serovar identification workflows. Full article

Orange allergy is estimated to account for up to 3–4% of food allergies. Major allergens identified in orange (Citrus sinensis) include Cit s 1 (germin-like protein) and Cit s 2 (profilin), while Cit s 3 (non-specific lipid transfer protein, nsLTP) and Cit s 7 (gibberellin-regulated protein) have also been described. The objective of this study was to investigate the presence and IgE-binding capacity of germin-like proteins in citrus fruits other than oranges. We describe five patients with immediate allergic reactions after orange ingestion. All patients underwent skin prick tests (SPT) to aeroallergens and common food allergens, prick-by-prick testing with orange, lemon, and mandarin (pulp, peel, seeds), total IgE, specific IgE (sIgE), anaphylaxis scoring (oFASS), and the Food Allergy Quality of Life Questionnaire (FAQLQ-AF). Protein extracts from peel and pulp of orange, lemon, and mandarin were analyzed by Bradford assay, SDS-PAGE, and IgE immunoblotting using patient sera. Selected bands were identified by peptide mass fingerprinting. A 23 kDa band was recognized by all five patients in orange (pulp and peel), lemon (peel), and mandarin (peel). This band was consistent with Cit s 1, a germin-like protein already annotated in the IUIS allergen database for orange but not for lemon or mandarin. Peptide fingerprinting confirmed the germin-like identity of the 23 kDa bands in all three citrus species. Germin-like proteins of approximately 23 kDa were identified as IgE-binding components in peel extracts of orange, lemon, and mandarin, and in orange pulp. These findings suggest a potential shared allergen across citrus species that may contribute to allergic reactions independent of LTP sensitization. Full article

Skeletal muscle development is a critical economic trait in livestock, governed by myogenic satellite cell regulation. Integrins mediate mechanical anchorage to the ECM and enable ECM–intracellular signaling. CIB2, as an EF-hand-domain protein involved in mechanotransduction, shows significant developmental regulation in goat muscle. Although the role of CIB2 in skeletal muscle growth is poorly characterized, we observed pronounced developmental upregulation of IB2 in postnatal goat muscle. CIB2 expression increased >20-fold by postnatal day 90 (P90) compared to P1, sustaining elevation through P180 (p < 0.05). Functional investigations indicated that siRNA-mediated knockdown of CIB2 could inhibit myoblast proliferation by inducing S-phase arrest (p < 0.05) and downregulating the expression of CDK4/Cyclin D/E. Simultaneously, CIB2 interference treatment was found to decrease the proliferative activity of goat myogenic satellite cells, yet it significantly promoted differentiation by upregulating the expression of MyoD/MyoG/MyHC (p < 0.01). Mechanistically, CTCF was identified as a transcriptional repressor binding to an intragenic region of the CIB2 gene locus (ChIP enrichment: 2.3-fold, p < 0.05). Knockdown of CTCF induced upregulation of CIB2 (p < 0.05). RNA-seq analysis established CIB2 as a calcium signaling hub: its interference activated IL-17/TNF and complement cascades, while overexpression suppressed focal adhesion/ECM–receptor interactions and enriched neuroendocrine pathways. Collectively, this study identifies the CTCF-CIB2–integrin α7β1–PI3K/AKT axis as a novel molecular mechanism that regulates the balance of myogenic fate in goats. These findings offer promising targets for genomic selection and precision breeding strategies aimed at enhancing muscle productivity in ruminants. Full article

Alopecia, a prevalent dermatological disorder affecting over half of the global population, is strongly associated with psychological distress. Extracts from Periplaneta americana (L. PA), a medicinal insect resource, exhibit pharmacological activities (e.g., antioxidant, anti-inflammatory, microcirculation improvement) that align with core therapeutic targets for alopecia. This study aimed to systematically investigate the efficacy and mechanisms of PA extracts in promoting hair regeneration. A strategy combining network pharmacology prediction and in vivo experiments was adopted. The efficacy of a Periplaneta americana extract was validated by evaluating hair regrowth status and skin pathological staining in C57BL/6J mice. Transcriptomics, metabolomics, RT-qPCR, and 16s rRNA techniques were integrated to dissect the underlying mechanisms of its hair-growth-promoting effects. PA-011 significantly promoted hair regeneration in depilated mice via multiple mechanisms: enhanced skin superoxide dismutase activity and upregulated vascular endothelial growth factor expression; modulated FOXO/PI3K/AKT signaling pathway and restored skin microbiota homeostasis; and accelerated transition of hair follicles from the telogen to anagen phase. PA-011 exerts hair-promoting effects through synergistic modulation of FOXO/PI3K/AKT signaling and the skin microbiome. As a novel therapeutic candidate, it warrants further systematic investigation for clinical translation. Full article

Acid soils are often a limiting factor in the production of most cultivated plants. In practice, the application of inadequate, physiologically acidic fertilizers, urea and NPK, is often encountered, which further worsens the already poor physicochemical properties of such soils. In this study, the influence of different amounts of NPK and urea fertilizers and methods of their application on the chemical properties of a very acidic soil and the accumulation of essential biogenic elements (N, P, K, Ca, Mg, and Al) in raspberry plants (leaves and fruits) was evaluated. The field trial with the raspberry plants was set up on a very acidic soil (pH in KCl 3.6), type Dystric Cambisol, and was monitored for 2 years. The application of NPK and urea mainly increased soil acidity in the second year in all treatments (for 0.10–0.18 pH unit) (except for urea applied in rows). The application of higher amounts of NPK increased the content of available forms of P (for 9.3–30.8 mg/kg) and K (for 57–95 mg/kg) in soil in both years, as well as exchangeable Ca (for 200–510 mg/kg) and Mg in the first year (15–165 mg/kg). The introduction of fertilizers in rows, compared to fertilization of the entire surface, influenced the reduction in mobile Al (especially when applying NPK, from 5.89 to 7.13 mg/100 g), the increase in mineral N and K content in the soil, and the increase in Ca and Mg only when applying urea, i.e., P when applying NPK in rows. In the leaves, the application of fertilizers in rows increased the content of Ca and Mg in the first year and P and K in the second year. In the fruits, the content of all estimated elements was not in correlation with their content in leaves and the fertilizer application, which indicates the influence of other ecological and biological factors on plant nutrition. Full article

Palindromic antimicrobial peptides (PAMs) constitute versatile scaffolds for the design and optimization of anticancer agents with applications in therapy, diagnosis, and/or monitoring. In the present study, fluorolabeled peptides derived from the palindromic sequence RWQWRWQWR containing fluorescent probes, such as 2-Aminobenzoyl, 5(6)-Carboxyfluorescein, and Rhodamine B, were obtained. RP-HPLC analysis revealed that the palindromic peptide conjugated to Rhodamine B (RhB-RWQWRWQWR) exhibited the presence of isomers, likely corresponding to the open-ring and spiro-lactam forms of the fluorescent probe. This equilibrium is dependent on the peptide sequence, as the RP-HPLC analysis of dimeric peptide (RhB-RRWQWR-hF-KKLG)₂K-Ahx did not reveal the presence of isomers. The antibacterial activity of the fluorescent peptides depends on the probe attached to the sequence and the bacterial strain tested. Notably, some fluorescent peptides showed activity against reference strains as well as sensitive, resistant, and multidrug-resistant clinical isolates of E. coli, S. aureus, and E. faecalis. Fluorolabeled peptides 1-Abz (MIC = 62 µM), RhB-1 (MIC = 62 µM), and Abz-1 (MIC = 31 µM) exhibited significant activity against clinical isolates of E. coli, S. aureus, and E. faecalis, respectively. The RhB-1 (IC₅₀ = 61 µM), Abz-1 (IC₅₀ = 87 µM), and RhB-2 (IC₅₀ = 35 µM) peptides exhibited a rapid, significant, and concentration-dependent cytotoxic effect on HeLa cells, accompanied by morphological changes characteristic of apoptosis. RhB-1 (IC₅₀ = 18 µM) peptide also exhibited significant cytotoxic activity against breast cancer cells MCF-7. These conjugates remain valuable for elucidating the possible mechanisms of action of these novel anticancer peptides. Rhodamine-labeled peptides displayed cytotoxicity comparable to that of their unlabeled analogues, suggesting that cellular internalization constitutes a critical early step in their mechanism of action. These findings suggest that cell death induced by both unlabeled and fluorolabeled peptides proceeds predominantly via apoptosis and is likely contingent upon peptide internalization. Functionalization at the N-terminal end of the palindromic sequence can be evaluated to develop systems for transporting non-protein molecules into cancer cells. Full article

The strength mobilisation framework was adopted for the first time to describe the stress–strain responses for three different types of sands, including a total of 30 published drained triaxial tests—25 for Karlsruhe Fine Sand, 2 for Ottawa sands and 3 for Fontainebleau sand, under confining pressures ranging from 50 to 400 kPa. The peak shear strength ${\tau }_{peak}$ obtained from drained triaxial shearing of these sands was used to normalise shear stress. Shear strains normalised at peak strength ${\gamma }_{peak}$ and at half peak of shear strength ${\gamma }_{M=2}$ were taken as the normalised reference strains, and the results were compared. Power–law functions were then derived when the mobilised strength was between $0.2{\tau }_{peak}$ and $0.8{\tau }_{peak}$. Exponents of the power–law functions of these sands were found to be lower than in the published undrained shearing data of clays. Using ${\gamma }_{M=2}$ as the reference strain shows a slightly better power–law correlation than using ${\gamma }_{peak}$. Linear relationships between the reference strains and variables, such as relative density, relative dilatancy index, and dilatancy, are identified. Full article

Anthraquinone acid dyes are widely used in dyeing polyamide due to their good exhaustion and brightness. While ionic interactions primarily govern dye–fiber bonding, the molecular weight (Mw) of these dyes can significantly influence migration, apparent color strength, and fastness behavior. This study offers comparative insight into how the Mw of structurally similar anthraquinone acid dyes impacts their diffusion, fixation, and functional outcomes (e.g., UV protection) on polyamide 6 fabric, using Acid Blue 260 (Mw~564) and Acid Blue 127:1 (Mw~845) as representative low- and high-Mw dyes. The effects of dye concentration, pH, and temperature on color strength (K/S) were evaluated, migration index and zeta potential were measured, and UV protection factor (UPF) and FTIR analyses were used to assess fabric functionality. Results showed that the lower-Mw dye exhibited higher migration tendency, particularly at increased dye concentrations, while the higher-Mw dye demonstrated greater color strength and superior wash fastness. Additionally, improved UPF ratings were associated with higher-Mw dye due to enhanced light absorption. These findings offer practical insights for optimizing acid dye selection in polyamide coloration to balance color performance and functional attributes. Full article