Search Results (8,500)

Background and Aims: Little is known about metabolic dysfunction-associated steatotic liver disease (MASLD) as a risk factor for hepatocellular carcinoma (HCC) in non-cirrhotic (HCC-NC) patients. In-house developed mouse models with defective lipid-metabolizing enzyme long-chain 3-hydroxy acyl-CoA dehydrogenase (LCHAD), coded by hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha (HADHA) gene, result in MASLD (steatosis) without cirrhosis leading to HCC-NC. The aims of the current investigations are to assess molecular markers and the associated molecular events that may lead to HCC-NC. Methods: cDNA array study of HCC patients was conducted to assess the expression of HADHA transcripts. Differentially expressed proteins identified between wild-type (WT) and heterozygous mice with no cancer (HT) from a previous study were subjected to Ingenuity Pathway Analysis (IPA). Western blotting was performed to assess the expression of proteins. Results: IPA of the differentially expressed proteins between WT and HT mice results in two biological networks (network 1 and network 2), which pointed to an important role of p53 in HCC-NC. Validation of the levels of MDM2 and p53 also highlights the role of MDM2-p53 axis in HCC-NC. All the focus molecules in network 1 and network 2 are either presented as tumor suppressor/promoter of carcinogenesis or serum markers for early HCC diagnosis. The hepatotoxicity report from IPA further identified four functional groups including liver steatosis, glutathione depletion, hepatocellular carcinoma, and liver hyperplasia/hyperproliferation. Conclusions: This study suggests that impaired fatty oxidation may play a role in the development of HCC associated with steatosis but without cirrhosis (HCC-NC). Defective LCHAD is a novel etiology for HCC. Full article

Magnetohydrodynamic (MHD) flow and heat transfer in porous media are central to many engineering applications, including heat exchangers, MHD generators, and polymer processing. This study examines the boundary layer flow and thermal behavior of an electrically conducting viscous fluid over a porous stretching tube. The model accounts for nonlinear thermal radiation, internal heat generation/absorption, and Darcy–Forchheimer drag to capture porous medium resistance. Similarity transformations reduce the governing equations to a system of coupled nonlinear ordinary differential equations, which are solved numerically using the BVP4C technique with Response Surface Methodology (RSM) and sensitivity analysis. The effects of dimensionless parameters magnetic field strength (M), Reynolds number (Re), Darcy–Forchheimer parameter (Df), Brinkman number (Br), Prandtl number (Pr), nonlinear radiation parameter (Rd), wall-to-ambient temperature ratio (rw), and heat source/sink parameter (Q) are investigated. Results show that increasing M, Df, and Q suppresses velocity and enhances temperature due to Lorentz and porous drag effects. Higher Re raises pressure but reduces near-wall velocity, while rw, Rd, and internal heating intensify thermal layers. The entropy generation analysis highlights the competing roles of viscous, magnetic, and thermal irreversibility, while the Bejan number trends distinctly indicate which mechanism dominates under different parameter conditions. The RSM findings highlight that rw and Rd consistently reduce the Nusselt number (Nu), lowering thermal efficiency. These results provide practical guidance for optimizing energy efficiency and thermal management in MHD and porous media-based systems.: Full article

Blue fescue (Festuca glauca) is a widely used ornamental grass worldwide. Drought is an important limiting factor for the growth and development of blue fescue; therefore, cultivating new strains of blue fescue with a strong drought tolerance is of great significance for its production practice. To investigate the drought tolerance mechanism of ds-1, this study subjected both ds-1 and “Festina” to a natural drought treatment and measured their physiological and biochemical indicators. A transcriptomic analysis was also conducted to explore the underlying molecular mechanisms. The results showed that, after the drought treatment, the relative water content (RWC), water use efficiency (WUE), and photosynthetic rate (Pn) of ds-1 leaves were significantly higher than those of “Festina”; in addition, the contents of H₂O₂ and O₂⁻, the relative electrical conductivity (REC), the malondialdehyde (MDA) content, the gas conductance (Gs), and the transpiration rate (Tr) were significantly lower than those of “Festina”. The peroxidase (POD) activity of ds-1 was significantly higher than that of “Festina”, while the superoxide dismutase (SOD) activity of ds-1 was significantly lower than that of “Festina”. The transcriptome data analysis showed that there were a total of 9475 differentially expressed genes (DEGs) between ds-1 and “Festina”. A Venn plot analysis showed 692 DEGs between ds-1—8d vs. “Festina”—8d and ds-1—16d vs. “Festina”—16d. A KEGG enrichment analysis showed that these 692 genes were mainly enriched in 86 pathways, including those related to the photosynthesis antenna protein, plant hormone signal transduction, MAPK signaling, starch and sucrose metabolism, and arginine and proline metabolism. Further screening identified genes that may be associated with drought stress, including PYL, PP2C, SnRK2, ABF, BRI1, JAZ, MYC2, Lhc, and MPK6. The qRT-PCR results indicated that the expression trends of the DEGs were consistent with the transcriptome sequencing results. Our research results can provide a basis for exploring candidate genes for drought tolerance in blue fescue. In addition, our research results provide valuable genetic resources for the development of drought-resistant ornamental grass varieties, which can help reduce water consumption in cities and decrease labor and capital investment. Full article

This paper presents an analytical investigation of the free vibration behavior of fiber metal laminate (FML) beams with three types of boundary conditions, considering the temperature-dependent properties and the interfacial slip. In the proposed model, the non-uniform temperature field is derived based on one-dimensional heat conduction theory using a transfer formulation. Subsequently, based on the two-dimensional elasticity theory, the governing equations are established. Compared with shear deformation theories, the present solution does not rely on a shear deformation assumption, enabling more accurate capture of interlaminar shear effects and higher-order vibration modes. The relationship of stresses and displacements is determined by the differential quadrature method, the state-space method and the transfer matrix method. Since the corresponding matrix is singular due to the absence of external loads, the natural frequencies are determined using the bisection method. The comparison study indicates that the present solutions are consistent with experimental results, and the errors of finite element simulation and the solution based on the first-order shear deformation theory reach 3.81% and 3.96%, respectively. At last, the effects of temperature, the effects of temperature degree, interface bonding and boundary conditions on the vibration performance of the FML beams are investigated in detail. The research results provide support for the design and analysis of FML beams under high-temperature and vibration environments in practical engineering. Full article

Background/Objectives: Galectin-3 (Gal-3), encoded by LGALS3, is a β-galactoside-binding lectin involved in diverse tumor-associated processes, including immune modulation, cell cycle regulation, and stress adaptation. Despite its known roles in cancer biology, the full extent of its molecular functions and prognostic relevance across tumor types remains incompletely understood. This study aimed to systematically investigate the transcriptomic impact of LGALS3 deletion and assess its clinical significance in cancer. Methods: We analyzed CRISPR-Cas9 knockout transcriptomic data from the SigCom LINCS database to characterize the consensus gene signature associated with LGALS3 loss using functional enrichment analyses. Pan-cancer survival analyses were conducted using TIMER2.0. Differential Gal-3 protein levels in ductal adenocarcinoma and normal pancreatic tissues were evaluated using the Human Protein Atlas. Finally, functional analyses were performed in pancreatic ductal adenocarcinoma (PDAC). Results: LGALS3 deletion across multiple cancer cell lines led to transcriptomic changes involving mitotic progression, stress responses, and axonal guidance pathways. High LGALS3 expression was significantly associated with worse overall survival in lower-grade glioma, PDAC, uveal melanoma, and kidney renal papillary cell carcinoma. LGALS3 knockout in YAPC cells recapitulated the pan-cancer findings, linking LGALS3 to cell morphogenesis and proliferation. Conclusions: These findings identify Galectin-3 as a key regulator of oncogenic programs and a potential prognostic biomarker in PDAC and other malignancies, with implications for therapeutic targeting. Full article

The coloration of shellfish significantly influences both environmental adaptability and economic value. In the Jinjiang oyster (Crassostrea ariakensis), soft-body color varies between individuals, with an orange-yellow phenotype distinct from the milky white coloration of the wild type. To elucidate the compositional differences and molecular mechanisms underlying orange-yellow (designated as CaR) versus milky white (CaW) soft-body color in C. ariakensis, we conducted comparative ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) non-targeted and transcriptomic analyses. A total of 280 differential accumulation metabolites (DAMs) and 691 differentially expressed genes (DEGs) were detected between the CaR and CaW groups. The metabolite set enrichment analysis (MSEA) revealed that DAMs were significantly enriched in pigment metabolism pathways, including tyrosine metabolism, porphyrin metabolism, and lipid metabolism. Furthermore, genes associated with melanin synthesis and carotenoids conversions or transports were upregulated in the CaR vs. CaW group. These genes included Cyp4z1, Cyp4f22, Cyp17a1, Cyp1a5, Cyp2d28a, Lrp4, Aldh, and Tyr-3, potentially driving the accumulation of pheomelanin and carotenoids. This study demonstrates the vital roles of melanin and carotenoid metabolism in Jinjiang oyster body color formation, providing key insights into the molecular mechanisms of color determination in shellfish. Full article

Rapid climate change has exacerbated global ecosystem degradation, leading to habitat fragmentation and landscape connectivity loss. Constructing ecological networks (EN) with resilient conduction functions and conservation priorities is crucial for maintaining regional ecological security and promoting sustainable development. However, the spatiotemporal modeling and dynamic resilience assessment of EN under the combined impacts of future climate and land use/land cover (LULC) changes remain underexplored. This study focuses on the Central Yunnan Urban Agglomeration (CYUA), China, and integrates landscape ecology with complex network theory to develop a dynamic resilience assessment framework that incorporates multi-scenario LULC projections, multi-temporal EN construction, and node-link disturbance simulations. Under the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP-RCP) scenarios, we quantified spatiotemporal variations in EN resilience and identified resilience-based conservation priority areas. The results show that: (1) Future EN patterns exhibit a westward clustering trend, with expanding habitat areas and enhanced connectivity. (2) From 2000 to 2040, EN resilience remains generally stable, but diverges significantly across scenarios—showing steady increases under SSP1-2.6 and SSP5-8.5, while slightly declining under SSP2-4.5. (3) Approximately 20% of nodes and 40% of links are identified as critical components for maintaining structural-functional resilience, and are projected to form conservation priority patterns characterized by larger habitat areas and more compact connectivity under future scenarios. The multi-scenario analysis provides differentiated strategies for EN planning and ecological conservation. This framework offers adaptive and resilient solutions for regional ecosystem management under climate change. Full article

Owing to multiple non-covalent interactions, ionic groups impart unique chemical and physical properties into polymers including ion conductivity/mobility, permeation, and intrinsic healability. Ionenes contain ionic groups in their polymer backbone, which offer great versatility in polymer design. Herein, selected aliphatic and aromatic imidazoles were synthesized, which were used as monomeric building blocks for the preparation of thermoplastic ionenes by following a Sn2 step growth reaction across organic halides. The structure and molecular weight of the polymers was characterized by Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) techniques. Once polymerized, anion-exchange reactions were carried out to replace the halides with four other counter-anions. Subsequently, the effect of the nature of the anion and the cation on the polymers’ thermal and hygroscopic properties was studied in detail by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and FTIR spectroscopy. Depending on the chemical structures of the polymeric cations and the related anions, tailored polymers with a glass transition temperature (T_g) in the range of 30 °C to 131 °C and a thermal stability varying between 170 °C and 385 °C were obtained. Full article

Silicon carbide (SiC)-coated carbon nanowalls (CNWs) have been proposed for use as implantable scaffold electrodes. Therefore, we investigated the effects of the SiC coating on CNWs and assessed the effects of the application of electrical stimulation (ES) on human mesenchymal stem cells cultured on SiC-coated CNWs. Measurements were conducted using immunofluorescence staining, proliferation assays, and quantitative reverse transcription polymerase chain reaction. Our results showed that the SiC coating increased the cell adhesion area, and the combination of the SiC coating and ES promoted cell proliferation. Furthermore, ES enhanced osteogenic differentiation on CNWs, both with and without the SiC coating. In SiC-coated samples, the increase in wall thickness of CNWs by the SiC coating promoted neural differentiation. These findings indicate that scaffold electrodes composed of SiC-coated CNWs enhance cell adhesion and proliferation; the application of ES to such electrodes promotes osteogenic differentiation, while the SiC coating itself promotes neural differentiation. Full article

Background: Passive brain–computer interface (pBCI) systems use a combination of electroencephalography (EEG) and machine learning (ML) to evaluate a user’s cognitive and physiological state, with increasing applications in both clinical and non-clinical scenarios. pBCI systems have been limited by their traditional reliance on sensor technologies that cannot easily be integrated into non-laboratory settings where pBCIs are most needed. Advances in textile-electrode-based EEG show promise in overcoming the operational limitations; however, no study has demonstrated their use in pBCIs. This study presents the first application of fully textile-based EEG for pBCIs in differentiating cognitive states. Methods: Cognitive state comparisons between eyes-open (EO) and eyes-closed (EC) conditions were conducted using publicly available data for both novel textile and traditional dry-electrode EEG. EO vs. EC differences across both EEG sensor technologies were assessed in delta, theta, alpha, and beta EEG power bands, followed by the application of a Support Vector Machine (SVM) classifier. The SVM was applied to each EEG system separately and in a combined setting, where the classifier was trained on dry EEG data and tested on textile EEG data. Results: The textile EEG system accurately captured the characteristic increase in alpha power from EO to EC (p < 0.01), but power values were lower than those of dry EEG across all frequency bands. Classification accuracies for the standalone dry and textile systems were 96% and 92%, respectively. The cross-sensor generalizability assessment resulted in a 91% classification accuracy. Conclusions: This study presents the first use of textile-based EEG for pBCI applications. Our results indicate that textile-based EEG can reliably capture changes in EEG power bands between EO and EC, and that a pBCI system utilizing non-traditional textile electrodes is both accurate and generalizable. Full article

The composition, architecture, and plant traits of temperate steppe communities are intricately associated with environmental factors. However, most studies primarily focus on aboveground observations, often overlooking the critical role of belowground root systems. Here we conducted a field survey at a large-regional scale to investigate the composition of temperate steppe communities and plant root traits. Cluster analysis, correspondence analysis and Pearson correlation coefficient matrix method were employed to classify vegetation associations based on plant community composition and root traits. The principal driving and limiting factors shaping plant root communities were systematically investigated. The results showed that the temperate steppe was categorized into three community subtypes: meadow steppe, typical steppe, and desert steppe, comprising five plant groups and thirteen plant associations. The RLFS analysis, based on belowground architectural and functional traits, demonstrated a spatial gradient differentiation with three ecological adaptations: tufted herbs, rhizome herbs, and non-tufted or rhizome herbs. Key environmental driving factors for meadow steppe included precipitation, soil carbon, nitrogen, and phosphorus content, while the average growing-season temperature as a limiting factor. The environmental driving factors for the typical steppe were not apparent, and the limiting factor was water. For the desert steppe, the environmental driving factors were altitude and average growing-season temperature. These findings reveal notable spatial heterogeneity and a distinct distribution pattern in community composition and vegetation classification based on belowground root traits in the Inner Mongolia steppes. Full article

Cold stress significantly impairs plant growth and development, making the study of cold resistance mechanisms a critical research focus. Oreorchis patens (Lindl.) exhibits strong cold hardiness, yet its molecular and physiological adaptations to cold stress remain unclear. This study utilized microscopy, physiological assays, and RNA sequencing to comprehensively investigate O. patens’s responses to cold stress. The results reveal that cold stress altered leaf anatomy, leading to irregular mesophyll cells, deformed chloroplasts, and variable epidermal thickness. Physiologically, SOD and POD activities peaked at 5 °C/−10 °C, while CAT activity declined; osmotic regulators (soluble sugars, proline) increased with decreasing temperatures. Compared to the reference plants (e.g., Erigeron canadensis, Allium fistulosum), O. patens exhibited lower SOD and POD but markedly higher CAT activities, alongside reduced MDA, soluble sugars, proline, and proteins, underscoring its distinctive tolerance strategy. Low temperature stress (≤10 °C/5 °C) significantly decreased the SPAD index; the net photosynthetic rate (Pn) initially increased and then approached zero within the temperature range from 30 °C/25 °C to 25 °C/20 °C; transpiration rate (Tr) and stomatal conductance (Gs) changed synchronously, accompanied by an increase in intercellular CO₂ concentration (Ci). RNA sequencing identified 1139 cold-responsive differentially expressed genes, which were primarily enriched in flavonoid/lignin biosynthesis, jasmonic acid synthesis, and ROS scavenging pathways. qRT-PCR analysis revealed the role of secondary metabolites in O. patens response to cold stress. This study was the first to discuss the physiological, biochemical, and molecular regulatory mechanisms of O. patens resistance to cold stress, which provides foundational insights into its overwintering mechanisms and informs breeding strategies for cold-hardy horticultural crops in northern China. Full article

As more machine learning models are used in sensitive fields like healthcare, finance, and smart infrastructure, protecting structured tabular data from privacy attacks is a key research challenge. Although several privacy-preserving methods have been proposed for tabular data, a comprehensive comparison of their performance and trade-offs has yet to be conducted. We introduce and empirically assess a combined defense system that integrates differential privacy, federated learning, adaptive noise injection, hybrid cryptographic encryption, and ensemble-based obfuscation. The given strategies are analyzed on the benchmark tabular datasets (ADULT, GSS, FTE), showing that the suggested methods can mitigate up to 50 percent of model inversion attacks in relation to baseline models without decreasing the model utility (F1 scores are higher than 0.85). Moreover, on these datasets, our results match or exceed the latest state-of-the-art (SOTA) in terms of privacy. We also transform each defense into essential data privacy laws worldwide (GDPR and HIPAA), suggesting the best applicable guidelines for the ethical and regulation-sensitive deployment of privacy-preserving machine learning models in sensitive spaces. Full article

Arthritis and arthrosis are prevalent joint diseases that cause pain and disability, and their early diagnosis is crucial for preventing irreversible damage. Conventional diagnostic methods such as X-ray, ultrasound, and MRI have limitations in early detection, prompting interest in alternative techniques. This work presents the design and clinical evaluation of a prototype device for non-invasive early diagnosis of arthritis (inflammatory joint disease) and arthrosis (osteoarthritis) using infrared thermography and deep neural networks. The portable prototype integrates a Raspberry Pi 4 microcomputer, an infrared thermal camera, and a touchscreen interface, all housed in a 3D-printed PLA enclosure. A custom Flask-based application enables two operational modes: (1) thermal image acquisition for training data collection, and (2) automated diagnosis using a pre-trained ResNet50 deep learning model. A clinical study was conducted at a university clinic in a temperature-controlled environment with 100 subjects (70% with arthritic conditions and 30% healthy). Thermal images of both hands (four images per hand) were captured for each participant, and all patients provided informed consent. The ResNet50 model was trained to classify three classes (healthy, arthritis, and arthrosis) from these images. Results show that the system can effectively distinguish healthy individuals from those with joint pathologies, achieving an overall test accuracy of approximately 64%. The model identified healthy hands with high confidence (100% sensitivity for the healthy class), but it struggled to differentiate between arthritis and arthrosis, often misclassifying one as the other. The prototype’s multiclass ROC (Receiver Operating Characteristic) analysis further showed excellent discrimination between healthy vs. diseased groups (AUC, Area Under the Curve ~1.00), but lower performance between arthrosis and arthritis classes (AUC ~0.60–0.68). Despite these challenges, the device demonstrates the feasibility of AI-assisted thermographic screening: it is completely non-invasive, radiation-free, and low-cost, providing results in real-time. In the discussion, we compare this thermography-based approach with conventional diagnostic modalities and highlight its advantages, such as early detection of physiological changes, portability, and patient comfort. While not intended to replace established methods, this technology can serve as an early warning and triage tool in clinical settings. In conclusion, the proposed prototype represents an innovative application of infrared thermography and deep learning for joint disease screening. With further improvements in classification accuracy and broader validation, such systems could significantly augment current clinical practice by enabling rapid and non-invasive early diagnosis of arthritis and arthrosis. Full article

Bulbine species (Asphodelaceae) are routinely used in many African communities to treat various dermatological disorders, including wounds, due to their relative accessibility, affordability, safety records, and reported efficacies. However, these reported biological activities lack robust empirical evidence and well-validated cellular mechanisms for plausible applications. Hence, this review was aimed at investigating the bioactive compounds of Bulbine species linked to their cellular wound healing attributes, their toxicity, and cytotoxicity. A detailed literature search was conducted using Web of Science, Google scholar, and PubMed, followed by Scopus and VOSviewer (version 1.6.20) bibliographic analyses. Bulbine frutescens (L.) Willd. and Bulbine natalensis Baker safely mediate tissue healing and coagulation cascade as adaptogens and cytotoxic agents. The wound healing activities of the Bulbine species were linked to the synergistic wound healing or tissue repair properties of bioactive compounds (such as saponins, terpenoids, luteolin, and apigenin) via the expression of collagen type-I, alpha-2 (COL1A2) gene, collagen III, increase in the wound tensile strength, and anti-cytokine interleukin-10 (IL-10) mRNA. Bulbine species were also reported to contain specialised biomarker compounds (such as naphthoquinones, bulbine-emodin, and aloe-emodin) which mediate the activation of hydroxyproline, Aryl Hydrocarbon Receptor, transforming growth factor beta—β1 (TGFβ1), and the suppressor of mothers against decapentaplegic proteins (SMAD), which ultimately induce tissue granulation, myofibroblast differentiation, re-epithelialization, higher protein complexes, and scar tissue formations. These findings give credence to the wound healing therapeutic potential of Bulbine species. However, additional clinical studies are necessary to further ascertain the reported efficacies of Bulbine species’ bioactive principles, their overall safety, and the underlying cellular mechanisms involved in the wound healing process and carcinogenesis. Full article