Search Results (37)

Ophiocordyceps sinensis represents a valuable medicinal resource. In this study, mechanisms underlying differences in chemical composition and antioxidant capacity among wild O. sinensis (GL), artificially cultivated O. sinensis (RG), and product of O. sinensis “Bailing” capsules (BL) were systematically investigated via in vitro antioxidant capacity assays and untargeted metabolomics. Results showed GL exhibited the highest total phenol (TPS) content and superior free radical scavenging activity. Additionally, superoxide dismutase (SOD) and peroxidase (POD) activities in RG were higher than those in BL. Correlation analysis of antioxidant indices demonstrated significant positive correlations between total phenols (TPS) and flavonoids (TF) with DPPH radical scavenging, ferric ion reducing antioxidant power (FRAP), hydroxyl radical scavenging rate, and superoxide anion radical scavenging rate (p < 0.01). A total of 6729 metabolites were detected, encompassing amino acids and their derivatives, lipids, and nucleotides and their derivatives, among other classes. Furthermore, metabolites exhibited distinct intergroup separation, indicating significant differences in metabolic profiles between O. sinensis and its substitute products. KEGG enrichment analysis showed that differential metabolites were mainly enriched in amino acid, lipid, and nucleotide metabolic pathways, among which the linoleic acid metabolic pathway was significantly downregulated. Key metabolites included γ-linolenic acid, 12(13)-EpOME-d, 9-HpODE, etc. Additionally, results of correlation analysis revealed that differential metabolites of lipids, nucleotides, and amino acids exhibited a significant positive correlation with antioxidant indices (p < 0.05). These findings suggest that the antioxidant capacity of O. sinensis and its substitutes may be regulated via linoleic acid metabolism, providing a theoretical basis for advancing targeted functional development of O. sinensis and its substitute products. Full article

Biologically active peptides can be obtained with various research methods, depending on the starting material, biological activity, and intended use. To use the most efficient method, it is worth combining in silico and in vitro experiments. Among the tools that can support an in silico analysis are databases such as the Antimicrobial Peptide Database (AMPD) or BIOPEP-UWM. The aim of this study was to make an in silico hydrolysis of peptides with anticancer properties selected from the AMP database, using pepsin, trypsin, and chymotrypsin. Most peptides obtained had properties inhibiting ACE and dipeptidyl peptidase IV activity. Among the resulting peptides, those with the sequence AR, CF, ER, TF, IY, ER, AW, GF, TW, SK and IM are potentially resistant to peptidase from microbial action. An analysis of the peptides’ characteristics showed that peptides with the sequence AR, EK, ER and SK are well-soluble in water and have high affinity for protein and ligand binding. Peptides with the sequence TF, IL and PF are unstable. Thermostable peptides are PGL, IL, GL, IY, VF, PL, IM and QL. The results of the study may be used to design in vitro experiments. Full article

This study presents an innovative pipeline for processing, compressing, and remotely visualizing large-scale numerical simulations of fluid dynamics in a virtual wind tunnel (VWT), leveraging virtual and augmented reality (VR/AR) for enhanced analysis and high-end visualization. The workflow addresses the challenges of handling massive databases generated using Direct Numerical Simulation (DNS) while maintaining visual fidelity and ensuring efficient rendering for user interaction. Fully immersive visualization of supersonic (Mach number 2.86) spatially developing turbulent boundary layers (SDTBLs) over strong concave and convex curvatures was achieved. The comprehensive DNS data provides insights on the transport phenomena inside turbulent boundary layers under strong deceleration or an Adverse Pressure Gradient (APG) caused by concave walls as well as strong acceleration or a Favorable Pressure Gradient (FPG) caused by convex walls under different wall thermal conditions (i.e., Cold, Adiabatic, and Hot walls). The process begins with a .vts file input from a DNS, which is visualized using ParaView software. These visualizations, representing different fluid behaviors based on a DNS with a high spatial/temporal resolution and employing millions of “numerical sensors”, are treated as individual time frames and exported in GL Transmission Format (GLTF), which is a widely used open-source file format designed for efficient transmission and loading of 3D scenes. To support the workflow, optimized Extract–Transform–Load (ETL) techniques were implemented for high-throughput data handling. Conversion of exported Graphics Library Transmission Format (GLTF) files into Graphics Library Transmission Format Binary files (typically referred to as GLB) reduced the storage by 25% and improved the load latency by 60%. This research uses Unity’s Profile Analyzer and Memory Profiler to identify performance limitations during contour rendering, focusing on the GPU and CPU efficiency. Further, immersive VR/AR analytics are achieved by connecting the processed outputs to Unity engine software and Microsoft HoloLens Gen 2 via Azure Remote Rendering cloud services, enabling real-time exploration of fluid behavior in mixed-reality environments. This pipeline constitutes a significant advancement in the scientific visualization of fluid dynamics, particularly when applied to datasets comprising hundreds of high-resolution frames. Moreover, the methodologies and insights gleaned from this approach are highly transferable, offering potential applications across various other scientific and engineering disciplines. Full article

Background: Hemoglobin (Hb) has been identified to be an independent prognostic marker for oncological outcomes in several malignancies. However, the impact of Hb levels before radical prostatectomy (RP) in localized prostate cancer remains unclear. Methods: Preoperative Hb levels were retrospectively collected from patients, who underwent RP from 2016 to 2022. Hb levels were analyzed as continuous and binary variables. For binary analysis, the cohort was divided into high-Hb (≥150 g/L) and low-Hb (<150 g/L) groups using the median as a cutoff. We used Spearman rank correlation to assess possible associations between Hb and continuous variables and logistic regression for Hb and binary variables. To assess the impact of preoperative Hb on recurrence-free survival (RFS), adjuvant treatment free survival (TFS), and metastasis-free survival (MFS), univariate and multivariate Cox regression analyses were performed. Results: A total of 567 patients were included in the analysis. Higher Hb levels, both when analyzed as a continuous variable and when divided in high and low groups, were inversely correlated with age (p < 0.001) and the International Society of Urological Pathology (ISUP) grade (p = 0.005 or p = 0.028, respectively). Patients in the high-Hb group showed a decreased risk of extraprostatic disease (≥pT3) (odds ratio [OR] 0.71, 95%-CI: 0.50–0.99, p = 0.047). In univariate cox regression analysis, high-Hb patients had a significantly longer RFS compared to the low-Hb group (hazard ratio [HR] 0.64, 95%-CI: 0.44–0.92, p = 0.015). When adjusting for age, ISUP grade, positive surgical margin, prostate specific antigen, nodal status, and ≥pT3, this effect was no longer statistically significant (HR 0.76, 95%-CI 0.56–1.22, p = 0.178). Hb was not a significant prognostic factor for TFS or MFS. Conclusions: In this large cohort, lower preoperative Hb values were associated with a more aggressive tumor grading and shorter RFS. However, we were unable to identify Hb as an independent predictor of oncological survival outcomes. Full article

This paper presents the integrated study of the funerary ara of Ofilius Ianuarius, discovered within the burial complex of Via Appia Antica 39, and explores its digital stratigraphic recontextualisation through two 3D semantic workflows. The research aims to evaluate the potential of stratigraphic 3D modelling as a tool for post-excavation analysis and transparent archaeological interpretation. Starting from a set of georeferenced photogrammetric models acquired between 2023 and 2025, the study tests two workflows: (1) an EMF-based approach using the Extended Matrix, Blender, and EMviq for stratigraphic relationship modelling and online visualisation; (2) a semantic integration method using the .gltf format and the CRMArcheo Annotation Tool developed in Blender, exported to the ATON platform. While both workflows enable accurate 3D documentation, they differ in their capacity for structured semantic enrichment and interoperability. The results highlight the value of combining reality-based models with semantically linked stratigraphic proxies and suggest future directions for linking archaeological datasets, ontologies, and interactive digital platforms. This work contributes to the ongoing effort to foster transparency, reproducibility, and accessibility in virtual archaeological reconstruction. Full article

The utilisation of 3D models in low-cost devices, such as the internet of things, virtual reality, and augmented reality, is expanding. The challenge lies in the lack of lightweight solutions for verifying the authenticity of models in the graphics library transmission format (glTF) on devices with limited resources. The glTF standard, which allows storage in glb format, is the leading standard for representing 3D assets. Despite its popularity, research on watermarking glTF models remains limited. This paper proposes a novel method for authenticating 3D models in glb format based on fragile watermarking. Additionally, an analysis was conducted to determine the impact of embedding the watermark in vertex attributes other than position on the integrity and visual quality of the model. The methodology is as follows: (1) embedding the watermark, (2) applying model modification or omitting it, and (3) verifying authenticity based on the recovered watermark. The proposed algorithm attaches a 512-bit hash-based message authentication code (HMAC) to a 3D model using the least significant bits (LSBs) modification method. The use of HMAC and LSBs has resulted in a computationally efficient algorithm that can be implemented in low-cost devices. Full article

The GntR is a transcriptional regulator generally known as a gluconate-operon repressor to specifically regulate the transportation and phosphorylation of gluconate. In the present study we report the cloning of the GntR-encoding gene of the industrial 2-ketogluconate (2KGA)-producer Pseudomonas plecoglossicida JUIM01, which is involved in the regulation of gluconate metabolism, along with the identification of some of its target genes and its operator sequence. GntR is a 36.36-kDa cytoplasmic and hydrophobic DNA-binding transcriptional regulator belonging to the LacI family. The knockout of gntR resulted in the significant upregulation of the transcription of the gluconate kinase gene gntK and, to a lesser extent, the permease gene gntP, as well as downregulation of genes involved in glucose uptake (oprB-1, gltB, gltF, gltG, and gltK) and those involved in 2-ketogluconate (2KGA) transport (kguT) and catabolism (kguE, kguK, and kguD). These results indicated that GntR positively regulated glucose and 2KGA transport and catabolism, while negatively affecting GntP-mediated gluconate uptake and gluconate phosphorylation by GntK. Electrophoretic mobility shift assay (EMSA) and DNase I footprinting analyses confirmed that GntR interacted with operator sequences in the divergent promoter regions of gntK and gntP, as well as in the gntR promoter region. A putative operator sequence (consensus 5′-AG-N₂-AGCGCT-N-TCT-3′) was identified. These data suggest that GntR positively regulates genes involved in glucose uptake/transport and 2KGA transport/catabolism, while repressing its own expression as well as that of genes involved in gluconate transport/catabolism. These findings not only elucidate the regulation of GntR and its target genes in P. plecoglossicida, but also provide valuable insights for optimizing industrial 2KGA production. Full article

Interoperability between digital models in the manufacturing and AEC domains is a critical issue in the building design of complex systems. Despite the adoption of well-established standards such as STEP (STandard for the Exchange of Product data, ISO 10303-21) for the industrial domain and IFC (Industry Foundation Classes, ISO 16739-1) for the construction domain, communication between these domains is still limited due to differences in conceptual models, levels of detail, and application purposes. Existing solutions for conversion between these formats are few, often proprietary, and not always suitable to ensure full semantic integration in BIM (Building Information Modeling) flows. This study proposes a methodological framework for structured conversion from STEP to IFC-SPF (STEP Physical File), based on information and geometric simplification and data enrichment. The process includes the elimination of irrelevant components, simplification of geometries, merging assemblies, and integration of data useful to the building context. The experimental implementation, carried out using the Bonsai extension for Blender, demonstrates a substantial reduction in geometric complexity and computational load, while maintaining data consistency required for integration into BIM processes. This approach emerges as a scalable, affordable, and sustainable solution for interoperability between industrial and civil models, even in professional environments lacking advanced software development skills. Full article

The biosensors based on transcription factors (TFs) are widely used in high throughput screening of metabolic overproducers. The unsatisfactory performances (narrow detection and dynamic ranges) of biosensors limit their practical application and need more improvement. In this study, using the TF LysG (sensing lysine) as an example, a biosensor optimization method was constructed by growth-coupled screening of TF random mutant libraries. The better the performance of the biosensor, the faster the strain grows under screening pressure. A LysG^{E15D, A54D, and I164V}-based biosensors were obtained, which were about 2-fold of the control in the detection and dynamic ranges. A lysine high-producer was screened effectively using the optimized biosensor with the production at 1.51 ± 0.30 g/L in flasks (2.22-fold of the original strain). This study provided a promising strategy for optimizing TF-based biosensors and was of high potential to be applied in the lysine high-producers screening process. Full article

Genes of metabolic pathways are individually or collectively regulated, often via unclear mechanisms. The anthocyanin pathway, well known for its regulation by the MYB/bHLH/WDR (MBW) complex but less well understood in its connections to MYC2, BBX21, SPL9, PIF3, and HY5, is investigated here for its direct links to the regulators. We show that MYC2 can activate the structural genes of the anthocyanin pathway but also suppress them (except F3′H) in both Arabidopsis and Oryza when a local MBW complex is present. BBX21 or SPL9 can activate all or part of the structural genes, respectively, but the effects can be largely overwritten by the local MBW complex. HY5 primarily influences expressions of the early genes (CHS, CHI, and F3H). TF-TF relationships can be complex here: PIF3, BBX21, or SPL9 can mildly activate MYC2; MYC2 physically interacts with the bHLH (GL3) of the MBW complex and/or competes with strong actions of BBX21 to lessen a stimulus to the anthocyanin pathway. The dual role of MYC2 in regulating the anthocyanin pathway and a similar role of BBX21 in regulating BAN reveal a network-level mechanism, in which pathways are modulated locally and competing interactions between modulators may tone down strong environmental signals before they reach the network. Full article

Remote sensing images are very vulnerable to cloud interference during the imaging process. Cloud occlusion, especially thick cloud occlusion, significantly reduces the imaging quality of remote sensing images, which in turn affects a variety of subsequent tasks using the remote sensing images. The remote sensing images miss ground information due to thick cloud occlusion. The thick cloud removal method based on a temporality global–local structure is initially suggested as a solution to this problem. This method includes two stages: the global multi-temporal feature fusion (GMFF) stage and the local single-temporal information restoration (LSIR) stage. It adopts the fusion feature of global multi-temporal to restore the thick cloud occlusion information of local single temporal images. Then, the featured global–local structure is created in both two stages, fusing the global feature capture ability of Transformer with the local feature extraction ability of CNN, with the goal of effectively retaining the detailed information of the remote sensing images. Finally, the local feature extraction (LFE) module and global–local feature extraction (GLFE) module is designed according to the global–local characteristics, and the different module details are designed in this two stages. Experimental results indicate that the proposed method performs significantly better than the compared methods in the established data set for the task of multi-temporal thick cloud removal. In the four scenes, when compared to the best method CMSN, the peak signal-to-noise ratio (PSNR) index improved by 2.675, 5.2255, and 4.9823 dB in the first, second, and third temporal images, respectively. The average improvement of these three temporal images is 9.65%. In the first, second, and third temporal images, the correlation coefficient (CC) index improved by 0.016, 0.0658, and 0.0145, respectively, and the average improvement for the three temporal images is 3.35%. Structural similarity (SSIM) and root mean square (RMSE) are improved 0.33% and 34.29%, respectively. Consequently, in the field of multi-temporal cloud removal, the proposed method enhances the utilization of multi-temporal information and achieves better effectiveness of thick cloud restoration. Full article

In the context of web augmented reality (AR), 3D rendering that maintains visual quality and frame rate requirements remains a challenge. The lack of a dedicated and efficient 3D format often results in the degraded visual quality of the original data and compromises the user experience. This paper examines the integration of web-streamable view-dependent representations of large-sized and high-resolution 3D models in web AR applications. The developed cross-platform prototype exploits the batched multi-resolution structures of the Nexus.js library as a dedicated lightweight web AR format and tests it against common formats and compression techniques. Built with AR.js and Three.js open-source libraries, it allows the overlay of the multi-resolution models by interactively adjusting the position, rotation and scale parameters. The proposed method includes real-time view-dependent rendering, geometric instancing and 3D pose regression for two types of AR: natural feature tracking (NFT) and location-based positioning for large and textured 3D overlays. The prototype achieves up to a 46% speedup in rendering time compared to optimized glTF models, while a 34 M vertices 3D model is visible in less than 4 s without degraded visual quality in slow 3D networks. The evaluation under various scenes and devices offers insights into how a multi-resolution scheme can be adopted in web AR for high-quality visualization and real-time performance. Full article

This study aimed to investigate the effects of different environmental factors (temperature, pH, and NaCl) and food matrices (skimmed milk powder, lecithin, and sucrose) on the antibacterial activity of theaflavins (TFs) against Staphylococcus aureus (S. aureus) and Salmonella paratyphi B (S. paratyphi B). TFs showed a larger diameter of inhibition zone (DIZ, 12.58 ± 0.09 mm–16.36 ± 0.12 mm) value against S. aureus than that of S. paratyphi B (12.42 ± 0.43 mm–15.81 ± 0.24 mm) at the same concentration (2–10 mg/mL). When temperatures were 25–121 °C, the DIZ of TFs against both S. aureus and S. paratyphi B was not significantly different. As pH increased from 2 to 10, their DIZ values decreased significantly from 16.78 ± 0.23 mm to 13.43 ± 0.08 mm and 15.63 ± 0.42 mm to 12.18 ± 0.14 mm, respectively. Their DIZ values increased slightly as the NaCl concentration increased from 0.2 mol/L to 0.8 mol/L, while their DIZ values decreased significantly for skimmed milk powder concentrations in the range of 20–120 g/L. Regarding the concentrations of lecithin and sucrose were 2–12 g/L and 10–60 g/L, their DIZ values showed no significant change against S. paratyphi B, but an increased trend for S. aureus. Under the above different environmental factors and food matrices, TFs maintained excellent antibacterial activity against S. aureus and S. paratyphi B, providing a theoretical guidance for applying TFs as novel antibacterial additives in the food industry. Full article

Ferroptosis is a regulated form of cell death that involves iron-dependent lipid peroxidation. Ferroptosis-related genes (FRGs) play an essential role in the tumorigenesis of gastric cancer (GC), which is one of the most common and lethal cancers worldwide. Understanding the prognostic significance of FRGs in GC can shed light on GC treatment and diagnosis. In this study, we proposed a new gene co-expression network analysis method, namely EP-WGCNA. This method used Euclidean and Pearson weighted distance (EP_dis) to construct a weighted gene co-expression network instead of the Pearson’s correlation coefficient used in the original WGCNA method. The aim was to better capture the interactions and functional associations among genes. We used EP-WGCNA to identify the FRGs related to GC phenotype and applied bioinformatics methods to select the FRGs associated with the prognosis (P-FRGs) of GC patients. Firstly, we screened the FRGs that were differentially expressed based on the TCGA and GTEx databases. Then, we selected the P-FRGs using EP-WGCNA, Cox regression, and Kaplan–Meier analysis. The prognostic model based on P-FRGs-Cox (ALB, BNIP3, DPEP1, GLS2, MEG3, PDK4, TF, and TSC22D3) was constructed on the TCGA-GTEx dataset. According to the median risk score, all patients in the TCGA training dataset and GSE84426 testing dataset were classified into a high- or low-risk group. GC patients in the low-risk group showed higher survival probability than those in the high-risk group. The time-dependent receiver operating characteristic (timeROC) showed that EP-WGCNA-Cox predicted 0.77 in the training set and 0.64 in the testing set for the 5-year survival rate of GC patients, which was better than traditional WGCNA-Cox (P-WGCNA-Cox). In addition, we validated that the P-FRGs were significantly differentially expressed in the adjacent non-tumor gastric tissues and tumor tissues by immunohistochemical staining from the Human Protein Atlas (HPA) database. We also found that the P-FRGs were enriched in tumorigenic pathways by enrichment analysis. In conclusion, our study demonstrated that EP-WGCNA can mine the key FRGs related to the phenotype of GC and is superior to the P-WGCNA. The EP-WGCNA-Cox model based on P-FRGs is reliable in predicting the survival rate of GC patients and can provide potential biomarkers and therapeutic targets for GC. Full article

Traditional sourdough is obtained using a mixture of flour and water stored at room temperature until acidification. Therefore, adding lactic acid bacteria (LAB) can improve the quality and safety of sourdough bread. Faced with this problem, four drying techniques—freeze-drying, spray-drying, low-temperature drying, and drying at low humidity—have been applied. Our goals were to isolate LAB strains with antifungal potential against Aspergillus and Penicillium fungi. The antifungal capacity was evaluated with agar diffusion, co-culture in overlay agar, and a microdilution susceptibility assay. In addition, the antifungal compounds generated in sourdough were analyzed. As a result, dried sourdoughs were prepared with Lactiplantibacillus plantarum TN10, Lactiplantibacillus plantarum TF2, Pediococcus pentosaceus TF8, Pediococcus acidilactici TE4, and Pediococcus pentosaceus TI6. The minimum fungicidal concentrations ranged from 25 g/L versus P. verrucosum and 100 g/L against A. flavus. A total of 27 volatile organic compounds were produced. Moreover, the lactic acid content reached 26 g/kg of dry product, and the phenyllactic concentration was significantly higher than the control. The P. pentosaceus TI6 exhibited a higher antifungal capacity in vitro and demonstrated a higher production of antifungal compounds compared to the other strains; therefore, further studies will evaluate the impact of this sourdough in bread manufacture. Full article