Search Results (16,183)

Hybrid natural/synthetic fiber laminates were examined as a practical process to cut mass, reduce material footprint, and meet structural demands while addressing sustainability targets. Yet direct, like-for-like comparisons generated under a single process and accompanied by durability measurements were limited, leaving design choices uncertain. This study aimed to fabricate and benchmark five representative laminates—C1: flax/epoxy, C2: jute/glass/epoxy, C3: hemp/carbon/epoxy, C4: flax/glass/bio-epoxy, and C5: kenaf/basalt/polyester—under a controlled hot-press schedule with a fixed cavity and verified fiber volume fraction. Panels were characterized using ASTM D3039 tension, ASTM D790 flexure, instrumented impact, 168 h water immersion, and thermogravimetric mass retention. The results were normalized to enable direct multi-criteria comparison, and a model was calibrated to predict tensile strength. C3 delivered the highest strengths (tension ≈ 120 MPa; flexure ≈ 126 MPa), while C5 showed the greatest impact capacity (≈60 kJ/m²). End-of-test water uptake at 168 h was C1 ≈ 3.4%, C2 ≈ 2.6%, C3 ≈ 1.4%, C4 ≈ 2.1%, and C5 ≈ 2.3%. The tensile predictor was fitted to panel means, with an R² of 0.988, and maintained an R² of 0.96 under leave-one-configuration-out testing. These results indicated that carbon-containing hybrids played the most critical roles in terms of stiffness, with kenaf/basalt being most suitable for stiffness-critical components at a similar density, and flax/glass with a bio-resin maximized the sustainability score while maintaining adequate strength. Future research should focus on enhancing specific strength at high renewable content through interface treatments, and extended modeling to improve flexure and impact responses. Full article

Mosquito-borne viruses like West Nile virus (WNV) and Usutu virus (USUV) present growing public health concerns, especially with climate change and expanding vector ranges. This study describes the development and validation of a duplex Real-Time RT-PCR assay targeting β-actin (ACTB) mRNA as an endogenous control and a conserved 92 bp region shared by WNV and USUV genomes. Degenerate primers for ACTB ensure RNA extraction quality and PCR performance while enabling simultaneous detection of both viruses. A total of 1002 mosquito pools collected in Piedmont, Italy, during the 2024 vector season under the National Surveillance Plan for Arboviruses (PNA), were tested. The assay showed 100% accuracy—ACTB mRNA was detected in all pools, and six pools tested positive for WNV or USUV (three each). Diagnostic specificity was confirmed on 40 horse and bovine serum samples. Sanger sequencing confirmed ACTB identity across multiple mosquito species. The assay also demonstrated reproducibility across different operators and thermocyclers. The limit of detection (LOD) evaluation showed that the assay is capable of detecting viral RNA at very low concentrations, confirming its high analytical sensitivity. The duplex RT-PCR here developed is a reliable, sensitive, and specific tool for arbovirus surveillance, combining pathogen detection with internal quality control of RNA extraction and amplification, thus improving early warning and rapid response to mosquito-borne disease threats. Full article

This study aimed to elucidate the vasorelaxant mechanism of action for apigenin 7-glucoside (A7G) by integrating computational and ex vivo pharmacological approaches. Molecular docking simulations were conducted to predict the binding affinities and interactions of A7G with key vascular proteins, specifically human endothelial nitric oxide synthase (eNOS-PDB ID: 1M9M), and human intermediate (IKCa-PDB ID: 9ED1) and small-conductance (SKCa-PDB ID: 6CNN) Ca2+-activated K+ channels. The vasodilatory properties of A7G were subsequently evaluated in isolated mesenteric vascular beds (MVBs) from normotensive Wistar Kyoto (WKY) and spontaneously hypertensive rats (SHR). The in silico analysis indicated that A7G possesses favorable binding affinities for the 1M9M, 9ED1, and 6CNN protein targets. Pharmacological assessments demonstrated that A7G induced a dose- and endothelium-dependent reduction in perfusion pressure in MVBs from WKY and SHR rats. The vasodilatory response to A7G was completely abrogated by perfusion with a high-potassium solution or a non-selective K+ channelblocker. Furthermore, co-administration of apamin and TRAM-34, selective inhibitors of SKCa and IKCa, respectively, also abolished the vasorelaxant effects of A7G. Collectively, these findings suggest that the vascular effects of A7G in both WKY and SHR rats involve an endothelium-dependent mechanism, likely initiated by the activation of the NO/cGMP pathway, which culminates in the opening of IKCa and SKCa channels. Full article

Temperature is a crucial indicator in monitoring industrial operations. Two-wire temperature transmitters, known for their precise measurements, are extensively used in sectors like crude oil extraction, refining, and fine chemicals. These transmitters can handle a maximum input voltage of 36 V and output a current signal up to 20 mA, enhancing resistance to electromagnetic interference and line noise while improving system compatibility and safety. In contrast, traditional low-dropout linear regulators (LDOs) typically have an input voltage below 6 V and suffer from limitations such as low power supply rejection ratio (PSRR), inadequate current driving capability, and significant temperature drift. This paper proposes a wide-input-range LDO with enhanced output accuracy and digital trimming, designed using the 180 nm BCD process. It incorporates dynamic mismatch compensation, digital trimming, and a strong-drive buffer, achieving a broad input voltage range and high PSRR with minimal temperature drift. The input voltage spans 6 V to 60 V, the output voltage is 1.8 V, and the PSRR reaches 124.5 dB. Across a temperature range of −40 °C to 130 °C, the maximum output voltage error is only 0.3%. This makes it highly suitable for high-precision circuit power supplies in industrial process control. Full article

The quality and safety of agricultural products are important factors in safeguarding human health and promoting sustainable agricultural development. However, for the purpose of improving the yield and quality, the misuse of pesticides often occurs, causing pesticide residues to remain in vegetables, posing threats to both the environment and human health. In order to detect and adsorb pesticide residues in vegetables, a coral-like novel magnetic porous nanomaterial (Fe@MDZ) was developed in this study as an adsorbent to adsorb thiabendazole (TBZ). Fe@MDZ has a large specific surface area (229.254 m²/g) and high saturation magnetization intensity (57.38 emu/g) with good adsorption capacity for TBZ. When the initial concentration was 2 mg/L, the adsorption capacity for TBZ was 1.23 mg/g. The static adsorption process matched the Langmuir isotherm model and was consistent with the pseudo-second-order kinetic model. In addition, the recovery of TBZ in both tomato and Chinese cabbage samples at different concentrations was above 70%. This work provides a new idea for the detection of TBZ pesticide residues in vegetables. Full article

Wildfire risk assessment requires integrating heterogeneous geospatial data to capture complex environmental dynamics. This study develops a hierarchical multimodal fusion framework combining high-resolution aerial imagery, historical fire data, topography, meteorology, and vegetation indices within Google Earth Engine. We introduce three progressive fusion levels: a single-modality baseline (NAIP-WHP), fixed-weight fusion (FIXED), and a novel geographically adaptive dynamic-weight approach (FUSED) that adjusts feature contributions based on regional characteristics like human activity intensity or aridity. Machine learning benchmarking across 49 U.S. regions reveals that Support Vector Machines (SVM) applied to the FUSED dataset achieve optimal performance, with an AUC-ROC of 92.1%, accuracy of 83.3%, and inference speed of 1.238 milliseconds per sample. This significantly outperforms the fixed-weight fusion approach, which achieved an AUC-ROC of 78.2%, and the single-modality baseline, which achieved 73.8%, representing relative improvements of 17.8% and 24.8%, respectively. The 10 m resolution risk heatmaps demonstrate operational viability, achieving an 86.27% hit rate in Carlsbad Caverns, NM. SHAP-based interpretability analysis reveals terrain dominance and context-dependent vegetation effects, aligning with wildfire ecology principles. Full article

Marine diatoms are an important group of phytoplankton that can shape marine ecosystems and global carbon cycling. When stressed, either physiologically or by grazing, diatoms release oxidized, lipid-derived signals known as oxylipins. Diatom-derived oxylipins are proposed to serve as defense and signaling chemicals that affect multiple components of marine ecosystems. Therefore, to elucidate the diversity of diatom-derived oxylipins produced during stress, we profiled the spectrum of dissolved lipids of five diatom species in culture under silicon limitation and across growth phases using ultra-high performance liquid chromatography coupled with high-resolution accurate mass spectrometry. In this study, we present evidence that physiological changes associated with Si-limitation elicit the extracellular release of linear oxygenated fatty acids (LOFAs) across five diatom species. For diatoms like Skeletonema japonicum and Pseudo-nitzschia multiseries, silicon limitation induced a distinct lipidomic signature driven by oxylipins known to be allelopathic. While their lipoxygenases were found to be different, S. japonicum and P. multiseries had the most similar dissolved lipidomes, suggesting alternative controls on oxylipin biosynthesis. Consequently, elevated oxylipin concentrations with silicon stress, estimated up to 5.91 µM, pose implications for diatoms at sea, potentially affecting ecosystems and biogeochemistry. Full article

Early cellular alterations in abdominal aortic aneurysm (AAA) are scarcely investigated. Aortic remodeling inflammation-related suggested the CXCR2/CXCL1/IL-8 axis as a therapeutic target. This study investigates CXCR1/CXCR2 antagonism in primary human aortic endothelial (HAOEC) and smooth muscle cells (HAOSMC) conditioned with IL-8 or serum from patients with AAA (sPT). Ladarixin (10 μM Lad or 25 μM) served as an inhibitor. Readouts included RT-qPCR for CXCL1, CXCL8, CXCR2, MMP9, NFKB1, and VEGF-A; zymography for MMP9 activity confocal microscopy for F-actin and mitochondria; NADPH/NADH diaphorase histochemistry for redox activity; and ATP assay. In HAOEC, IL-8 downregulated CXCR2, increased MMP9 activity, and induced cytoskeletal and mitochondria disorganization without altering NADH/NADPH diaphorases but increasing ATP release. At concentration of 10 μM Lad rescued cell organization and gene expression. sPT upregulated CXCL8, CXCR2, and MMP9, decreased NADH/NADPH diaphorases, and altered cytoskeleton and mitochondria organization in HAOEC. At concentration of 10 μM Lad (partially) and 25 μM Lad reverted gene upregulation and mitochondria distribution; both doses increased diaphorase and released ATP. HAOSMC were scantily susceptible to IL-8 and weakly responsive to sPT, slightly upregulating CXCR2 and VEGF-A but increasing proMMP9 gelatinolysis. Ladarixin recovered proMMP9 activity and modulated CXCL1. AAA-like vascular cell alterations involve multiple inflammatory factors and are modulable by inhibition of IL-8 receptors. The results underline careful dose calibration. Full article

Hepatocellular carcinoma (HCC), the most common primary liver malignancy worldwide, is strongly associated with chronic Hepatitis B Virus (HBV) infection, a significant risk factor. The ubiquitin–proteasome system, central to protein degradation, cellular homeostasis, and cell cycle regulation, has been implicated in the pathogenesis of several cancers, including HCC. Despite this, the specific expression patterns of proteasomal subunits during HBV infection and HBV-induced HCC, as well as the association between mRNA expression of proteasomal subunits and proteasomal activity, remain poorly defined. To address this critical knowledge gap, we analyzed mRNA expression profiles of proteasomal subunits in HBV-infected humanized mouse models to uncover HBV-specific molecular alterations. Our findings revealed that the chymotrypsin-like activity (β5) subunit of the proteasome (PSMB5) is consistently overexpressed following HBV infection. Functional studies demonstrated that β5 deficiency decreases MHC I levels on the cell surface and leads to the accumulation of ubiquitinated proteins, establishing a direct link between β5 overexpression and increased proteasomal activity. Concordantly, HBV-infected patient livers—regardless of HCC status—displayed elevated β5 mRNA/protein levels and enhanced chymotrypsin-like activity. Additionally, analysis of Protein Atlas data revealed that elevated β5 mRNA expression correlates with poor clinical prognosis in HCC patients. In summary, this study highlights how HBV infection induces significant alterations in proteasome function by elevating β5 expression and activity in human and mouse livers. These findings underscore the critical role of proteasomal dysregulation in HBV-associated liver pathology and provide new insights into its involvement in HCC development. Understanding the interplay between HBV infection and proteasome dynamics offers a valuable avenue for the identification of novel therapeutic targets and biomarkers in HCC. Full article

In this review, we present a general framework for the construction of Kac–Moody (KM) algebras associated to higher-dimensional manifolds. Starting from the classical case of loop algebras on a circle ${\mathbb{S}}^1$, we extend the approach to compact and non-compact group manifolds, coset spaces, and soft deformations thereof. After recalling the necessary geometric background on Riemannian manifolds, Hilbert bases, and Killing vectors, we present the construction of generalized current algebras $\mathfrak{g}\left(\mathcal{M}\right)$, their semidirect extensions with isometry algebras, and their central extensions. We show how the resulting algebras are controlled by the structure of the underlying manifold, and we illustrate the framework through explicit realizations on $SU\left(2\right)$, $SU\left(2\right)/U\left(1\right)$, and higher-dimensional spheres, highlighting their relation to Virasoro-like algebras. We also discuss the compatibility conditions for cocycles, the role of harmonic analysis, and some applications in higher-dimensional field theory and supergravity compactifications. This provides a unifying perspective on KM algebras beyond one-dimensional settings, paving the way for further exploration of their mathematical and physical implications. Full article

Stainless steel forms a native film of mixed metal oxides, and organic impurities are likely to adsorb on the surface upon exposure to ambient conditions. For many applications, oxides and impurities should be removed, and several techniques have been used for decades. An innovative method is presented in this paper. The organic impurities were oxidized using a water solution of 1 M peroxynitric acid (PNA). Stainless steel samples were immersed in the solution, and the oxidation of organic impurities was evaluated by the ultra-thin depth profiling using secondary ion mass spectrometry (SIMS). A minute of treatment with PNA caused oxidation of organic impurities and a decrease in the SIMS CN^– signal over an order of magnitude. Prolonged treatment caused the selective removal of the native iron oxide film, leaving a protective film of chromium oxide. Removal of the iron oxide film was also observed when stainless steel was treated with 1 M HNO₃. The PNA method is useful for routine cleaning of stainless steel to remove the organic contaminants from the surface and keep the passive chromium oxide film intact. It is ecologically friendly and enables rapid decomposition of the traces of organic impurities likely to be adsorbed on the metallic surfaces. Full article

Chronic hemophilic synovitis (CHS), driven by hemosiderin-laden macrophages from recurrent hemarthrosis, is a major cause of joint damage in hemophilia. Platelet-rich plasma (PRP) is a promising regenerative therapy for joint diseases. This study investigated PRP’s ability to modulate macrophage polarization from a pro-inflammatory (M1) to a pro-resolving, tissue-repairing (M2) phenotype in CHS. We analyzed synovial fluid (SF) from CHS patients (N = 22), both pre- and post-PRP treatment. Ex vivo analysis revealed a predominant M1 profile with an increased proportion of CD11⁺CD14⁺CD64^hi compared with CD206⁺ or CD163⁺ M2 macrophages in CHS SF. In vitro experiments showed that CHS SF skewed monocyte-derived macrophages toward an M1 inflammatory program, evaluated by flow cytometry, qPCR, and ELISA. However, adding PRP significantly modulated the pro-inflammatory macrophage program, promoting an M2 tissue repair profile. Furthermore, a random forest machine learning algorithm, applied to public scRNAseq data, confirmed PRP’s macrophage reprogramming effect. Functional assays also showed increased TGF-β secretion and macrophage fusion when challenged with neutrophil extracellular traps (NETs). A small patient follow-up cohort treated with intra-articular PRP showed similar results, including normalization of cellular content and reduced CD64/CD206 expression. These findings indicate that PRP treatment effectively shifts SF-associated M1 macrophages to an M2-like phenotype, highlighting its potential as a therapeutic strategy for CHS. Full article

Material Extrusion for Metals (MEX/M) has emerged as a cost-effective and versatile Additive Manufacturing technology (AM) for producing complex metal components. Despite its potential, parts realized via MEX/M suffer from significant limitations, primarily poor surface quality due to the intrinsic layer-wise effect from the printing deposition and selected printing conditions. Furthermore, the multi-step nature of the MEX/M process, particularly the sintering stage, can exacerbate roughness along with the printing orientation, thereby affecting part performance and limiting potential applications. In addition to surface defects, MEX parts are characterized by a high content of porosity when compared to other metal AM technologies like Powder Bed Fusion laser-based (PBF-LB) and Directed Energy Deposition laser-based (DED-LB). These defects, both on the surface and within the parts, can compromise the mechanical properties and overall quality of the final parts. In this context, the scientific community has increasingly recognized post-treatment processes as essential for simultaneously improving surface quality and enhancing bulk material properties. This review according to the PRISMA 2020 guidelines provides a comprehensive analysis of the most critical post-treatment processes applied to MEX/M parts. By critically reviewing the state of the art, this paper discusses how these treatments can effectively mitigate outer and inner defects, reduce porosity, and significantly improve mechanical performance, ultimately enabling the broader industrial adoption of MEX/M technology. Full article

Background/Objectives: Ovarian cancer is a heterogeneous malignancy with molecular subtypes that strongly influence prognosis and therapy. High-dimensional mRNA data can capture this biological diversity, but its complexity and noise limit robust subtype characterization. Furthermore, current classification approaches often fail to reflect subtype-specific transcriptional programs, underscoring the need for computational strategies that reduce dimensionality and identify discriminative molecular features. Methods: We designed a multi-stage feature selection and network analysis framework tailored for high-dimensional transcriptomic data. Starting with ~65,000 mRNA features, we applied unsupervised variance-based filtering and correlation pruning to eliminate low-information genes and reduce redundancy. The applied supervised Select-K Best filtering further refined the feature space. To enhance robustness, we implemented a hybrid selection strategy combining recursive feature elimination (RFE) with random forests and LASSO regression to identify discriminative mRNA features. Finally, these features were then used to construct a gene co-expression similarity network. Results: This pipeline reduced approximately 65,000 gene features to a subset of 83 discriminative transcripts, which were then used for network construction to reveal subtype-specific biology. The analysis identified four distinct groups. One group exhibited classical high-grade serous features defined by TP53 mutations and homologous recombination deficiency, while another was enriched for PI3K/AKT and ARID1A-associated signaling consistent with clear cell and endometrioid-like biology. A third group displayed drug resistance-associated transcriptional programs with receptor tyrosine kinase activation, and the fourth demonstrated a hybrid profile bridging serous and endometrioid expression modules. Conclusions: This pilot study shows that combining unsupervised and supervised feature selection with network modeling enables robust stratification of ovarian cancer subtypes. Full article

This study presents the OGS-YOLOv8 model for coffee bean maturity identification, designed to enhance accuracy in identifying coffee beans at different maturity stages in complicated contexts, utilizing an upgraded version of YOLOv8. Initially, the ODConv (full-dimensional dynamic convolution) substitutes the convolutional layers in the backbone and neck networks to augment the network’s capacity to capture attributes of coffee bean images. Second, we replace the C2f layer in the neck networks with the CSGSPC (Convolutional Split Group-Shuffle Partial Convolution) module to reduce the computational load of the model. Lastly, to improve bounding box regression accuracy by concentrating on challenging samples, we substitute the Inner-FocalerIoU function for the CIoU loss function. According to experimental results, OGS-YOLO v8 outperforms the original model by 7.4%, achieving a detection accuracy of 73.7% for coffee bean maturity. Reaching 76% at mAP@0.5, it represents a 3.2% increase over the initial model. Furthermore, GFLOPs dropped 26.8%, from 8.2 to 6.0. For applications like coffee bean maturity monitoring and intelligent harvesting, OGS-YOLOv8 offers strong technical support and reference by striking a good balance between high detection accuracy and low computational cost. Full article