Search Results (6,599)

Radiomics may aid the noninvasive characterization of adrenal incidentalomas; however, reproducibility is limited by methodological heterogeneity. In this retrospective, single-center, exploratory study, we tested whether radiomic features from baseline non-enhanced computed tomography (NECT) discriminate benign from malignant/metastatic adrenal lesions and contextualized results with a PRISMA 2020 systematic review (PubMed/Scopus 2017–2025; PROSPERO CRD420251276627). Thirty-three patients (36 lesions: 12 lipid-rich adenomas, 9 lipid-poor adenomas, 6 pheochromocytomas, 7 malignant/metastatic lesions, 2 myelolipomas) were included; myelolipomas were excluded from primary comparisons. Two abdominal radiologists performed consensus 3D segmentation on NECT. Using LIFEx (v7.8.0) and IBSI definitions, 42 features were extracted and z-score standardized. LASSO selected four heterogeneity descriptors: First-order Entropy, gray-level co-occurrence matrix (GLCM) entropy, gray-level size zone matrix (GLSZM) non-uniformity, and neighboring gray tone difference matrix (NGTDM) busyness. Heterogeneity increased from lipid-rich adenomas to pheochromocytomas and malignant/metastatic lesions (Kruskal–Wallis, all p < 0.001. Pairwise separability, measured using the Vargha–Delaney A index (VDA) as a rank-based measure of separability, was highest for lipid-rich adenomas versus malignant/metastatic lesions (0.93), intermediate for lipid-poor adenomas versus pheochromocytomas (0.73), and lowest for lipid-rich versus lipid-poor adenomas (0.64). The review identified 18 eligible CT radiomics studies that consistently reported higher entropy/non-uniformity in pheochromocytomas and malignant lesions than in lipid-rich adenomas. Global heterogeneity metrics on NECT may complement conventional CT criteria in indeterminate lesions; external validation with robust reference standards is needed in larger, multicenter cohorts with harmonization. Full article

Texture feature extraction plays a crucial role in land-use and land-cover (LULC) classification for the remotely sensed images. However, when these images are quantized to a limited number of gray levels to reduce data volume or noise, conventional texture descriptors often lose discriminative power. This study investigates singular values of the gray-level co-occurrence matrix (GLCM) as novel texture features for image classification, with local binary pattern (LBP), complete LBP (CLBP) statistics, and original GLCM features proposed by Haralick et al. for comparison. Under coarse quantization, texture descriptors of LBP and its variants, which encode micro-texture, lose detail, whereas GLCM, which encodes macro-texture, retains structural co-occurrence patterns. This study thus proposes a new feature set, namely the Singular Values of the gray-level co-occurrence matrix (SVGM), for texture discrimination. Experimental analysis indicates SVGM achieves higher class separability by preserving dominant spatial structure while suppressing noise and redundancy. Quantitative evaluation using classical SVMs with multiple kernels, quantum learning models with different kernels, and neural baselines (ANN and 1D-CNN) further shows that SVGM consistently improves classification performance. Within our tested models, quantum kernel SVMs are competitive and achieve the best results on some datasets, while classical models perform best on others. Full article

This study aimed to extract oil from skipjack tuna belly (Katsuwonus pelamis) using thermomechanical extraction and supercritical CO₂ extraction (SFE-CO₂). The SFE-CO₂ process was conducted at 25 MPa and 40 °C for 30 min, 1 h, and 3 h. Thermomechanical extraction yielded 88.1% crude oil, with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) contents of 7.6% and 19.2%, respectively. In the SFE-CO₂ process, the shortest extraction time (25 MPa, 40 °C, 30 min) resulted in the highest DHA (12.6%) concentration, as well as a total polyunsaturated fatty acid (PUFA) content of 22.4%. This behavior is attributed to the shorter CO₂–matrix contact time, which favored the selective extraction of target compounds. Conversely, extending the extraction time to 3 h under the same pressure and temperature led to the highest overall yield (26.4%). These findings demonstrate that SFE-CO₂ is a promising green technology for the valorization of fish processing by-products, enabling selective recovery of high-value omega-3 fatty acids while promoting more sustainable production practices. Full article

A robust Folin–Ciocalteu method, coupled with an optimized ultrasonic-assisted extraction, was established for accurate quantification of total polyphenols in high-oil grape seed matrices, where lipid interference and low extraction efficiency have been persistent challenges. Samples were first defatted with n-hexane to eliminate lipid interference. Key colorimetric parameters—Folin–Ciocalteu reagent volume, Na₂CO₃ concentration, reaction temperature, and time—were systematically optimized and validated for linearity, precision, and recovery. Subsequently, using defatted grape seed powder as the raw material, a four-factor, three-level Box–Behnken design combined with response surface methodology was employed to optimize the four extraction parameters: solid-to-liquid ratio, ethanol concentration, extraction temperature, and extraction time. The optimal conditions were 0.5 mL of Folin–Ciocalteu reagent, 20% Na₂CO₃, and reaction at 30 °C for 2.0 h, yielding a linear calibration curve (R² = 0.9991) with satisfactory methodological validation. Optimal extraction (52% ethanol, 1:50 w/v, 68 °C, 21 min) achieved a total polyphenol content of 2.93 × 10⁴ mg·kg⁻¹, closely matching the predicted value (relative error = 0.34%). Analysis of seven grape seed varieties from the Hebei Province revealed significant content variation (p < 0.05), ranging from 3.24 to 7.47 × 10⁴ mg·kg⁻¹, with Rose grape seeds exhibiting the highest level. The developed method effectively overcame matrix interference from high oil content, offering a reliable, efficient tool for screening high-polyphenol grape seed varieties and supporting the development of value-added functional products. Full article

The translation of nucleic acid amplification into practical point-of-care and biosensor-integrated diagnostics is still significantly impeded by the necessity for rapid sample preparation. For this reason, a broad comparison of seven commercially available kits for DNA/RNA extraction containing their temperature-related adjustments was performed. Extracts isolated from SARS-CoV-2-positive nasopharyngeal swabs, viral stocks, as well as laboratory-prepared suspensions of clinically relevant Gram-positive and Gram-negative bacteria were evaluated by recombinase polymerase amplification (RPA) and real-time PCR. In addition, the impact of transport media for SARS-CoV-2 samples was investigated. Extraction performance varied markedly according to the kit, pathogen, sample background. For SARS-CoV-2, rapid extraction was more effective for samples collected in viral transport medium than in inactivation buffer. Across bacterial targets, performance was species dependent, highlighting substantial differences in compatibility between simplified extraction workflows and downstream amplification. Among the rapid methods tested, a simplified QuickExtract protocol (95 °C, 5 min) provided the most consistent overall results, although it did not uniformly match the reference silica-based method for all targets. In conclusion, these results demonstrate that rapid nucleic acid extraction must be thoroughly evaluated as an essential element of the entire sample-to-answer workflow, rather than being chosen as a standalone preprocessing step for point-of-care molecular diagnostics. Full article

Hepatocellular carcinoma (HCC) poses a critical threat to global health because of the scarcity of effective therapeutic approaches. Sorafenib, a first-line treatment for advanced HCC, often faces efficacy limitations due to acquired resistance. Therefore, it is urgent to explore novel and effective anti-cancer drugs and combination therapies. This study explored the anti-HCC potential of Enocyanin (Eno), a natural anthocyanin-rich extract derived from grapes, either alone or combined with sorafenib. Our findings indicated that 100 μg/mL Eno remarkably suppressed the proliferation, invasion and migration of HepG2 cells, which was related to the induction of ferroptosis characterized by increased intracellular Fe²⁺, lipid peroxidation (LPO) and Acyl-CoA synthetase long chain family member 4 (ACSL4) levels, coupled with decreased glutathione (GSH) and glutathione peroxidase 4 (GPX4). Mechanistically, Eno promoted ferroptosis which was associated with inhibition of the p62/Keap1/Nrf2/HO-1 signaling pathway. Notably, Eno (100 μg/mL) combined with sorafenib (2 μM) had a synergistic anti-tumor effect (Q = 1.47), which further enhanced the inhibition of HepG2 cell growth and metastasis, aggravated ferroptosis, and more strongly suppressed the p62/Keap1/Nrf2/HO-1 axis. In the C57BL/6 mouse subcutaneous HCC transplantation model, the combination of Eno and sorafenib showed a stronger inhibitory effect on tumor growth, reaching a 70% inhibition rate, compared to 33% with Eno alone and 55% with sorafenib alone. In summary, this study demonstrates that Eno may be a novel inducer of ferroptosis, and it has the potential to be used in the treatment of hepatocellular carcinoma. It also provides a potential combined treatment strategy for enhancing the sensitivity of sorafenib. Full article

Hazardous compounds from used batteries pose a great threat to the environment. To prevent pollution and to recover critical materials from battery waste, efficient recycling is required. Until now, battery recycling has focused on the recovery of valuable metals from cathode materials, while organic fractions have often been neglected due to their low material value. New approaches to battery recycling are therefore necessary, where recycling methods based on supercritical carbon dioxide (SC-CO₂) extraction show great potential. In this work, a SC-CO₂ method was implemented to extract electrolyte solvents for the purification and recovery of a separator waste material (SWM) sorted out from lithium-ion battery (LIB)-based black mass. In addition, two other separation routes (ultrasonic washing and thermal treatment) were used for comparison. Based on the results from the three routes, mass balances revealed the gravimetric composition of the SWM, which includes separator, electrolyte, and electrode powder. The composition of electrolyte solvents was determined via Gas Chromatography-Mass Spectroscopy analysis. Furthermore, the polymeric separator was analyzed using Fourier Transform Infrared Spectroscopy, Thermogravimetric Analysis, and Differential Scanning Calorimetry analysis to evaluate the effects of SC-CO₂ extraction on the physicochemical properties. The recovery of electrolyte by the SC-CO₂ route is more efficient than the others, with extraction yields of 162 mg of electrolyte per gram of SWM. Moreover, no changes are observed in the analyzed properties of the polymeric separator material due to the SC-CO₂ extraction. Thus, the SC-CO₂ process proves to be a promising method for an efficient and sustainable recycling of electrolyte solvent and purifying of separator material from LIB waste. Full article

Introduction: Bacterial multidrug resistance (MDR) drives treatment with expensive, toxic, or pharmacokinetically suboptimal antibiotics. Objectives: To assess the prevalence of MDR Gram-positive cocci among isolates from cardiac implantable electronic device (CIED) infections at a Polish reference center. Methods: Data come from the “EXTRACT” registry (ClinicalTrials.gov ID NCT05775783), which covers 702 transvenous lead extraction procedures. Blood samples and intraoperative swabs were collected from participants with CIED infection. Results: From 209 cases with isolated pocket infection (PI) (107, 51.2%) or systemic infections (102, 48.8%), 263 Gram-positive cocci were cultured. They were: coagulase-negative staphylococci (CoNS) (177, 67.3%), Staphylococcus aureus (62, 23.6%), enterococci (15, 5.7%), streptococci (8, 3.0%), and others (1, 0.4%). The highest MDR rate was among CoNS (46.9%). CoNS exhibited methicillin resistance (MR-CoNS) in 55.9% with co-resistance to macrolides (73.2%), lincosamides (51.0%), fluoroquinolones (56.1%), aminoglycosides (41.4%), tetracyclines (29.6%), and co-trimoxazole (29.3%). Resistance to daptomycin (5.3%) and linezolid (2.0%) in MR-CoNS was rare. The frequency of MDR S. aureus was 8.1%. Methicillin resistance in S. aureus (MRSA, 6.5%) co-occurred with resistance to macrolides/lincosamides and fluoroquinolones (100% for both) or linezolid (25.0%). All MDR staphylococci were vancomycin-susceptible. High-level aminoglycoside resistance (HLAR) in Enterococcus faecalis (53.8%) was accompanied by levofloxacin co-resistance (66.7%). Conversely, E. faecium HLAR (50.0%) strains showed 100.0% β-lactam resistance. Vancomycin-resistant enterococci (VRE) accounted for 6.7%; the VRE E. faecium strain was tigecycline- and linezolid-susceptible. Among viridans group streptococci, β-lactam and lincosamides resistance was common (40.0% for both), with 50.0% of co-resistance. Conclusions: Epidemiological data may improve the effectiveness of empirical antibiotic therapy for CIED-related infections. Full article

Salvia transsylvanica, an endemic Romanian sage, remains understudied despite co-occurrence with validated medicinal Salvia species. In this study, lfeaves and flowers were harvested weekly during flowering (May and June) and subjected to classical hydroethanolic extraction, HPLC–DAD–ESI/MSⁿ profiling, in vitro antioxidant assays (ABTS, DPPH, FRAP), and enzyme-inhibitory screening, with multivariate analysis correlating compositional patterns with bioactivity. Rosmarinic acid dominated the phenolic profile (68.6 mg/g maximum in week 4), alongside salvianolic acids (salvianolic acid K isomers) and flavonoid glycosides (luteolin, apigenin, and hispidulin hexosides). Leaf extracts displayed higher ABTS/DPPH scavenging (higher phenolic acid content), while flowers showed superior FRAP and α-glucosidase inhibition (IC₅₀ 84–143 μg/mL, higher flavonoids), with maximal values being identified during week 4. S. transsylvanica offers complementary antioxidant profiles to commercial sages, warranting future in vivo validation for therapeutic applications. Full article

The high viscosity of biodiesel fuel, caused by the presence of saturated fatty acid esters, limits its application, particularly at low temperatures. Supercritical fluid extraction (SFE) using carbon dioxide represents a promising method for selective fractionation, enabling the removal of high-viscosity saturated components and the enrichment of the fuel with less viscous unsaturated esters. However, the rational design of such processes requires a deep understanding of the interrelationship between flow hydrodynamics, thermodynamic conditions, and mass transfer in a supercritical medium. In this work, a comprehensive computational fluid dynamics (CFD) modeling study of the fractionation process was performed for a model ethyl oleate/ethyl palmitate mixture (25.28:74.72 wt.%) in supercritical CO₂ at pressures of 11 and 14 MPa and a temperature of 40 °C. A three-dimensional model of a laboratory-scale extractor was developed using the Ansys Fluent software version 2020 R1 environment. Since the target esters are absent from the standard material database, a custom property library and compiled User-Defined Function (UDF) routines were developed. These describe the temperature dependence of density, viscosity, heat capacity, and thermal conductivity for both the individual components and their mixture using established mixing rules. The calculations employed an Eulerian multiphase model, the realizable k–ε turbulence model, and species transport equations. The modeling revealed pronounced selectivity: under the chosen thermodynamic conditions, ethyl palmitate is extracted preferentially over ethyl oleate, with this difference becoming more pronounced as pressure increases. The developed and verified CFD model deepens the fundamental understanding of hydrodynamics and mass transfer during supercritical fractionation and serves as a basis for optimizing process parameters to produce biodiesel with reduced viscosity. The regime at P = 14 MPa and t = 40 °C provides the most favorable thermodynamic and hydrodynamic conditions for the selective removal of saturated esters. Full article

Xanthoceras sorbifolium (Yellowhorn) is an underutilized, multipurpose, climate-resilient oilseed with emerging food and industrial potential. This review consolidates current knowledge on its botany, agronomy, kernel composition, extraction technologies, protein and bioactive functionality, food uses, regulatory considerations, and sustainability challenges. Yellowhorn offers high-quality oil with ≈94% unsaturated fatty acids (notably 3.5–4% nervonic acid), while defatted kernel meal contains 31–37% protein (w/w). The matrix also carries bioactives such as tocopherols in the oil (70–530 mg/kg), phytosterols (1420–2970 mg/kg), and saponins (up to 11.62%), alongside flavonoid extracts that show promising antioxidant activity (DPPH EC₅₀ ≈ 10.7 µg/mL). Extraction methods, including cold pressing, solvent systems, and supercritical CO₂, present trade-offs in yield (≈87.8%, ≈60.4–98.04%, and ≈56.5–89.63% respectively), bioactive retention, and scalability, while co-product valorization can improve economic and environmental performance. Regulatory acceptance in the U.S. will likely depend on a refined-oil, specification-driven Generally Recognized as Safe (GRAS) pathway supported by compositional and toxicological evidence. Sustainability priorities include breeding improvements and supply-chain development on marginal lands, valorization of co-products, and integration of life cycle assessment (LCA), both of which are currently under-reported for Yellowhorn. Future directions emphasize process optimization for simultaneous oil-protein recovery, selective purification of functional lipids, encapsulation for stability, and human studies to substantiate claims. Collectively, Yellowhorn represents a promising climate-ready ingredient system requiring targeted research to enable safe, scalable, and sustainable adoption. Full article

Ochratoxin A (OTA), a prevalent food contaminant, is closely linked to the development of various cancers, including clear cell renal cell carcinoma (ccRCC). However, the potential mechanisms remain to be explored. In this study, we employed network toxicology, machine learning, and molecular docking techniques to systematically investigate the potential molecular mechanisms underlying OTA-associated ccRCC. We normalized transcriptional data from two Gene Expression Omnibus (GEO) datasets and analyzed it using differential expression analysis and weighted gene co-expression network analysis (WGCNA), identifying 3224 ccRCC-associated target genes. These were intersected with 232 predicted OTA target genes, yielding a total of 56 overlapping targets. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that these targets were primarily enriched in critical biological processes, including extracellular matrix remodeling, immune microenvironment regulation, signaling pathway transduction, cellular metabolism, and protein homeostasis. Machine learning analysis identified “glmBoost + RF” (a sequential combination of feature selection and classifier) as the optimal model, from which nine key genes were extracted. SHapley Additive exPlanations (SHAP) analysis revealed five core genes (IGFBP3, ITGA5, PYGL, SLC22A8, LTB4R), with IGFBP3 and ITGA5 serving as the principal driver genes of the model. Validation of the model’s diagnostic efficacy and single-cell transcriptome analysis indicated that the core genes exhibited significant differential expression patterns, cell-type-specific expression characteristics, and high independent diagnostic efficacy. Molecular docking analyses predicted stable interactions between OTA and the core target proteins. These findings suggest potential molecular links between OTA exposure and ccRCC, providing a foundation for hypothesis generation and future experimental validation. Full article

This article presents a methodological framework for automating clinical data processing workflows using Generative Artificial Intelligence (AI) as an interactive co-developer. We demonstrate how Large Language Models (LLMs), specifically ChatGPT and Claude, can assist researchers in designing, implementing, and deploying complete ETL (Extract, Transform, Load) pipelines without requiring advanced programming or DevOps expertise. Using a dataset of 102 participants from a nonverbal expression study as a proof-of-concept, we show how AI-assisted automation transforms FaceReader video analysis outputs during the Cyberball paradigm into structured, analysis-ready datasets through containerized workflows orchestrated via Docker and n8n. The resulting framework successfully processes all 102 datasets, generating machine learning outputs to validate pipeline execution stability (rather than clinical predictivity), and deploys interactive visualization dashboards, tasks that would normally require significant manual effort and technical specialization expertise. This work establishes a replicable methodology for integrating Generative AI into research data management workflows, with implications for accelerating scientific discovery across behavioral and medical research domains. Full article

Chronic exposure to even low levels of pesticides is a serious public health issue, mainly due to the role of oxidative stress in damaging the liver and promoting cancer. This has driven interest in finding natural, plant-based antioxidants that can counteract this kind of chemical injury. In this study, we tested whether a methanol extract from the leaves of Pteropyrum scoparium (PSE) could protect the liver against oxidative harm caused by four common pesticides: acetochlor, deltamethrin, thiamethoxam, and rotenone. Chemical analysis showed that the extract contains high levels of phenolics (345.1 ± 7.6 mg GAE/g) and flavonoids (17.3 ± 1.3 mg CAE/g). GC–MS profiling revealed a diverse set of compounds, including fat-soluble antioxidants like squalene, α-tocopherol, and γ-sitosterol, and water-soluble phenolics like pyrogallol and catechol, suggesting PSE is equipped with a multi-layered antioxidant defence. In the animal experiment, rats were given each pesticide for 30 days, with or without PSE. All four pesticides caused clear oxidative stress in the liver: glutathione (GSH), total antioxidant capacity (TAC), antioxidant enzymes activities dropped, while markers of lipid damage (MDA) and free radical activity (DPPH) rose. Co-administration of PSE significantly restored GSH, TAC and antioxidant enzymes levels and reduced MDA and residual DPPH values compared to pesticide-only groups; these parameters were statistically comparable to the controls (p > 0.05), indicating a substantial recovery of hepatic redox balance. Histopathological examination of liver tissues confirmed these findings, as pesticide treatment caused visible liver injury; deltamethrin and thiamethoxam led to congestion in central veins, while rotenone and acetochlor triggered clusters of inflammatory Kupffer cells. In animals that also received PSE, liver structure remained largely normal, with much less congestion and inflammation. These results show that the combination of antioxidant constituents in PSE might contribute to hepatoprotection through redox modulation and preservation of endogenous antioxidant balance, as suggested by the observed biochemical and histological improvements. Full article

Rapid urbanization and global growth have made sustainable infrastructure a dire necessity. In hot arid regions, rising heat index levels intensify cooling demand and accelerate construction activity. Reducing emissions from concrete is critical to mitigate climate change. This study integrates BIM in Revit with EC3 to quantify GWP and total use of renewable/non-renewable primary resources at the product stage. A residential building is used to evaluate variations in environmental performance across multiple material scenarios (carbon intensive, energy transition, and green scenarios). Results reveal substantial differences in embodied carbon across scenarios. The carbon intensive scenario accounts for a total GWP of 649 tCO₂e, while the green scenario reduces emissions to 381 tCO₂e, which represents a reduction of 42%. Walls and floors are identified as the dominant contributors to embodied carbon due to high concrete volumes, with raw material extraction accounting for the largest share of emissions. Substituting conventional concrete walls with lightweight concrete walls reduces the total GWP by 28%. In addition, planed timber exhibits near zero emissions due to biogenic carbon storage and shows the highest renewable primary energy use among assessed materials. The proposed framework provides a practical approach for evaluating embodied carbon emissions and supports informed material selection for more sustainable building design. Full article