Search Results (2,597)

In this perspective, we highlight the relevance of the FA-Hippo signaling pathway and its regulation of the Yes-associated protein (YAP) and the transcriptional coactivator with a PDZ-binding domain (TAZ) as main players in the process of implants integration. The modulation and responses of YAP/TAZ triggered by substrate and ECM stiffness are of particular interest in the construction of materials used for medical implants. YAP/TAZ nuclear localization and activity respond to the substrate stiffness by several mechanisms that involve the canonical and non-canonical Hippo signaling and independently of the Hippo cascade. YAP/TAZ regulate the expression of genes involved in several mechanisms of relevance for implant integration such as the proliferation and differentiation of cell precursors and the immune response to the implant. The influence of substrate stiffness on the regulation of the immune response is not completely understood and the progress in this field can contribute to the designing of an adequate implant design. Though the use of nano-biomaterials has been proved to contribute to implant success, the relationship between grain size and stiffness of the material has not been explored in the biomedical field; filling these gaps in the knowledge of biomaterials will highly contribute to the design of biomaterials that could take advantage of the cells sensing and response to the stiffness at the implant interface. Full article

Cell adhesion molecules (CAMs) are cell-surface-localized proteins mediating interactions of cells with other cells and the extracellular matrix. CAMs influence cell behavior and survival by inducing various intracellular signaling cascades that regulate diverse cellular processes including cytoskeleton remodeling and gene expression. Here, we review the evidence demonstrating that the levels, subcellular distribution, and binding affinities of CAMs of several major families including integrins, cadherins, immunoglobulin superfamily, and selectins are regulated by intracellularly generated or extracellular reactive oxygen species (ROS). Remarkably, CAMs themselves induce ROS production in response to binding to their ligands by activating lipoxygenases or NADPH oxidases or influencing ROS generation in mitochondria. CAM-dependent ROS production is essential for CAM-mediated cell adhesion and CAM-dependent intracellular signaling. Importantly, CAMs also protect cells from the ROS-induced cell death by stimulating the synthesis of antioxidants and suppressing the cell death signaling. A better understanding of the role ROS play in controlling CAM functions and mechanisms of this control may pave the way to modulating the functions of CAMs in various disorders associated with abnormal cell adhesion. Full article

As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article

This study discloses the noncovalent immobilization of a bienzyme cascade composed of glucose oxidase (GOx) and horseradish peroxidase (HRP) onto magnetically responsive polyamide microparticles (PA MPs). Porous PA6, PA4, and PA12 MPs containing iron fillers were synthesized via activated anionic ring-opening polymerization in suspension, alongside neat PA6 MPs used as a reference. Four hybrid catalytic systems (GOx/HRP@PA) were prepared through sequential adsorption of HRP and GOx onto the various PA MP supports. The initial morphologies of the supports and the hybrid biocatalysts were characterized by SEM, followed by evaluation of the catalytic performance using a two-step glucose oxidation cascade process. Among all systems, the GOx/HRP@PA4-Fe complex exhibited the highest activity, being approximately 1.5 times greater than the native enzyme dyad, followed by the PA6-supported system with slightly inferior performance. All systems obeyed Michaelis–Menten kinetics, with the immobilized cascades displaying higher Kₘ and Vₘₐₓ values than the non-immobilized enzyme pair while maintaining comparable catalytic efficiencies, CE (CE = k_cat/Kₘ). Subsequently, the immobilized and native enzyme systems were employed for the polymerization of aniline. According to UV–VIS, complete monomer conversion was achieved within 24 h for selected catalysts, and FTIR analysis confirmed the formation of polyaniline in the emeraldine base form without the use of template molecules. These findings highlight the potential of Fe-containing polyamide microparticles as efficient supports for the sustainable, enzyme-mediated synthesis of intrinsically conductive aromatic polymers. Full article

Background: Crohn’s disease (CD) is a chronic disease perpetuated through key pro-inflammatory molecules, including tumor necrosis factor-alpha (TNFα). Angiopoietin-like protein 8 (ANGPTL8) may contribute to inflammation cascades. This study aimed to investigate how ANGPTL8 levels are influenced in patients with CD prior to and following anti-TNF therapy. Methods: Patients were divided into 3 groups. Patients with CD in clinical remission receiving IFX for at least 24 weeks (IFX-experienced group), patients scheduled to start IFX (IFX-naïve group), and healthy controls (control group). In the IFX-experienced group, ANGPTL8 levels were measured 24 h before the next maintenance IFX dose. In the IFX-naïve group, levels were measured at week 0 and week 24, and in the control group, they were measured randomly. Results: The total number of participants was 166. The numbers of IFX-experienced, IFX-naïve patients, and healthy controls were 82, 13, and 71, respectively. Mean age ranged from 27 to 33 years of age across the three groups. Eighty-four (51%) participants were female. ANGPTL8 levels were significantly higher in patients with CD (138.26 ± 8.47 pmol) compared to the healthy control group (102.52 ± 5.99 pmol, p = 0.001). Among IFX-naïve patients receiving anti-TNFα treatment, ANGPTL8 levels decreased significantly from 145.06 ± 17.93 pmol pre-treatment (week 0) to 81.78 ± 10.61 pmol post-treatment (week 24), p = 0.007. Conclusions: Our findings suggest that ANGPTL8 levels are elevated in CD and may be involved in the inflammatory process. The marked reduction in ANGPTL8 levels following anti-TNFα treatment indicates its potential as a biomarker for treatment response. Further research should focus on the exact mechanisms through which ANGPTL8 influences CD progression and its utility in clinical practice. Full article

The growing demand for reliable and secure vehicle-to-vehicle (V2V) communication in next-generation intelligent transportation systems has accelerated the adoption of reconfigurable intelligent surfaces (RIS) as a means of enhancing link quality, spectral efficiency, and physical layer security. In this paper, we investigate the problem of secrecy rate maximization in a cooperative dual-RIS-aided V2V communication network, where two cascaded RISs are deployed to collaboratively assist with secure data transmission between mobile vehicular nodes in the presence of eavesdroppers. To address the inherent complexity of time-varying wireless channels, we propose a novel evolutionary transformer-gated recurrent unit (Evo-Transformer-GRU) framework that jointly learns temporal channel patterns and optimizes the RIS reflection coefficients, beam-forming vectors, and cooperative communication strategies. Our model integrates the sequence modeling strength of GRUs with the global attention mechanism of transformer encoders, enabling the efficient representation of time-series channel behavior and long-range dependencies. To further enhance convergence and secrecy performance, we incorporate an improved gray wolf optimizer (IGWO) to adaptively regulate the model’s hyper-parameters and fine-tune the RIS phase shifts, resulting in a more stable and optimized learning process. Extensive simulations demonstrate the superiority of the proposed framework compared to existing baselines, such as transformer, bidirectional encoder representations from transformers (BERT), deep reinforcement learning (DRL), long short-term memory (LSTM), and GRU models. Specifically, our method achieves an up to 32.6% improvement in average secrecy rate and a 28.4% lower convergence time under varying channel conditions and eavesdropper locations. In addition to secrecy rate improvements, the proposed model achieved a root mean square error (RMSE) of 0.05, coefficient of determination ($R^2$) score of 0.96, and mean absolute percentage error (MAPE) of just 0.73%, outperforming all baseline methods in prediction accuracy and robustness. Furthermore, Evo-Transformer-GRU demonstrated rapid convergence within 100 epochs, the lowest variance across multiple runs. Full article

The multi-scale characteristics of remote sensing imagery have an inherent correspondence with the hierarchical structure of land cover classification systems, providing a theoretical foundation for multi-level land cover classification. However, most existing methods treat classification tasks at different semantic levels as independent processes, overlooking the semantic relationships among these levels, which leads to semantic inconsistencies and structural conflicts in classification results. We addressed this issue with a deep multi-task learning (MTL) framework, named MTL-SCH, which enables collaborative classification across multiple semantic levels. MTL-SCH employs a shared encoder combined with a feature cascade mechanism to boost information sharing and collaborative optimization between two levels. A hierarchical loss function is also embedded that explicitly models the semantic dependencies between levels, enhancing semantic consistency across levels. Two new evaluation metrics, namely Semantic Alignment Deviation (SAD) and Enhancing Semantic Alignment Deviation (ESAD), are also proposed to quantify the improvement of MTL-SCH in semantic consistency. In the experimental section, MTL-SCH is applied to different network models, including CNN, Transformer, and CNN-Transformer models. The results indicate that MTL-SCH improves classification accuracy in coarse- and fine-level segmentation tasks, significantly enhancing semantic consistency across levels and outperforming traditional flat segmentation methods. Full article

Background/Objectives: Urolithin A (UA), a gut-derived metabolite of ellagitannins or ellagic acid, has recently gained attention for its potential benefits to brain health. The present research aimed to assess the antidepressant-like properties of UA in both in vitro and in vivo models and explored the molecular mechanisms underlying these effects. Methods: We investigated the antidepressant effects and mechanisms of UA in a model of corticosterone-induced damage to PC12 cells and in a model of chronic socially frustrating stress. Results: Our results demonstrate that UA treatment (5 and 10 μM) significantly alleviated cellular damage and inflammation in corticosterone (CORT)-treated PC12 cells. Furthermore, UA administration (50 and 100 mg/kg) significantly reduced immobility time in the mouse tail suspension test (TST) and forced swim test (FST), indicating its antidepressant-like activity. Additionally, treatment with UA led to the activation of the cAMP response element-binding protein (CREB)/brain-derived neurotrophic factor (BDNF) signaling cascade and triggered the activation of adenosine monophosphate-activated protein kinase (AMPK) during these processes. Importantly, pretreatment with AMPK-specific inhibitor Compound C abolished UA’s cytoprotective effects in PC12 cells, as well as its behavioral efficacy in the FST and TST, and its neurotrophic effects, highlighting the critical role of AMPK activation in mediating these effects. Furthermore, in the chronic social defeat stress (CSDS) mouse model, UA treatment (50 and 100 mg/kg) significantly alleviated depression-like behaviors, including reduced sucrose preference in the sucrose preference test, increased social avoidance behavior in the social interaction test, and anxiety-like behaviors, including diminished exploration, in the elevated plus maze test, suggesting the antidepressant-like and anxiolytic-like activities of UA. Moreover, UA treatment reversed elevated serum stress hormone levels, hippocampal inflammation, and the decreased AMPK/CREB/BDNF signaling pathway in the hippocampus of CSDS mice. Conclusions: Together, these results provide compelling evidence for UA as a viable dietary supplement or therapeutic option for managing depression. Full article

Background: Bambusaoldhamii is an important economic bamboo species. However, flowering occurred after its introduction and cultivation, resulting in damage to the economy of bamboo forests. Currently, the molecular mechanism of flowering induced by introduction stress is still unclear. This study systematically explored the key genes and regulatory pathways of flowering in Bambusaoldhamii under introduction stress through field experiments combined with transcriptome sequencing and weighted gene co-expression network analysis (WGCNA), with the aim of providing a basis for flower-resistant cultivation and molecular breeding of bamboo. Results: The study conducted transcriptome sequencing on flowering and non-flowering Bambusaoldhamii bamboo introduced from Youxi, Fujian Province for 2 years, constructed a reference transcriptome containing 213,747 Unigenes, and screened out 36,800–42,980 significantly differentially expressed genes (FDR < 0.05). The results indicated that the photosensitive gene CRY and the temperature response gene COR413-PM were significantly upregulated in the flowering group; the expression level of the heavy metal detoxification gene MT3 increased by 27.77 times, combined with the upregulation of the symbiotic signaling gene NIN. WGCNA analysis showed that the expression level of the flower meristem determination gene AP1/CAL/FUL in the flowering group was 90.38 times that of the control group. Moreover, its expression is regulated by the cascade synergy of CRY-HRE/RAP2-12-COR413-PM signals. Conclusions: This study clarifies for the first time that the stress of introducing Bambusaoldhamii species activates the triad pathways of photo-temperature signal perception (CRY/COR413-PM), heavy metal detoxification (MT3), and symbiotic regulation (NIN), collaboratively driving the AP1/CAL/FUL gene expression network and ultimately triggering the flowering process. Full article

Scene text inpainting is a significant research challenge in visual text processing, with critical applications spanning incomplete traffic sign comprehension, degraded container-code recognition, occluded vehicle license plate processing, and other incomplete scene text processing systems. In this paper, a cascaded dual-inpainting network for scene text (CDINST) is proposed. The architecture integrates two scene text inpainting models to reconstruct the text foreground: the Structure Generation Module (SGM) and Structure Reconstruction Module (SRM). The SGM primarily performs preliminary foreground text reconstruction and extracts text structures. Building upon the SGM’s guidance, the SRM subsequently enhances the foreground structure reconstruction through structure-guided refinement. The experimental results demonstrate compelling performance on the benchmark dataset, showcasing both the effectiveness of the proposed dual-inpainting network and its accuracy in incomplete scene text recognition. The proposed network achieves an average recognition accuracy improvement of 11.94% compared to baseline methods for incomplete scene text recognition tasks. Full article

In order to break through the difficulties with a very-low-frequency (VLF) miniaturized antenna with small power capacity and low radiation efficiency, this paper proposes a high-radiation-field-strength magnetic loop antenna based on a nanocrystalline alloy magnetic core. A high-permeability nanocrystalline toroidal core (μ_r = 50,000, B_s = 1.2 T) is used to optimize the thickness-to-diameter ratio (t = 0.08) and increase the effective permeability to 11,000. The Leeds wires, characterized by their substantial carrying capacity, are manufactured through a toroidal winding process. This method results in a 68% reduction in leakage compared to traditional radial winding techniques and enhances magnetic induction strength by a factor of 1.5. Additionally, this approach effectively minimizes losses, thereby facilitating support for kilowatt-level power inputs. A cascaded LC resonant network (resonant capacitance 2.3 μF) and ferrite balun transformer (power capacity 3.37 kW) realize a 20-times amplification of the input current. A series connection of a high-voltage isolation capacitor blocks DC bias noise, guaranteeing the stable transmission of 1200 W power, which is 6 times higher than the power capacity of traditional ring antenna. At 7.8 kHz frequency, the magnetic field strength at 120 m reaches 47.32 dBμA/m, and, if 0.16 pT is used as the threshold, the communication distance can reach 1446 m, which is significantly better than the traditional solution. This design marks the first instance of achieving kilowatt-class VLF effective radiation in a compact 51 cm-diameter magnetic loop antenna, offering a highly efficient solution for applications such as mine communication and geological exploration. Full article

With the rapid expansion of Internet of Things (IoT) and edge computing applications, efficient video transmission under constrained bandwidth and limited computational resources has become increasingly critical. In such environments, perception-based video coding plays a vital role in maintaining acceptable visual quality while minimizing bit rate and processing overhead. Although newer video coding standards have emerged, H.264/AVC remains the dominant compression format in many deployed systems, particularly in commercial CCTV surveillance, due to its compatibility, stability, and widespread hardware support. Motivated by these practical demands, this paper proposes a perception-based video coding algorithm specifically tailored for low-bit-rate H.264/AVC applications. By targeting regions most relevant to the human visual system, the proposed method enhances perceptual quality while optimizing resource usage, making it particularly suitable for embedded systems and bandwidth-limited communication channels. In general, regions containing human faces and those exhibiting significant motion are of primary importance for human perception and should receive higher bit allocation to preserve visual quality. To this end, macroblocks (MBs) containing human faces are detected using the Viola–Jones algorithm, which leverages AdaBoost for feature selection and a cascade of classifiers for fast and accurate detection. This approach is favored over deep learning-based models due to its low computational complexity and real-time capability, making it ideal for latency- and resource-constrained IoT and edge environments. Motion-intensive macroblocks were identified by comparing their motion intensity against the average motion level of preceding reference frames. Based on these criteria, a dynamic quantization parameter (QP) adjustment strategy was applied to assign finer quantization to perceptually important regions of interest (ROIs) in low-bit-rate scenarios. The experimental results show that the proposed method achieves superior subjective visual quality and objective Peak Signal-to-Noise Ratio (PSNR) compared to the standard JM software and other state-of-the-art algorithms under the same bit rate constraints. Moreover, the approach introduces only a marginal increase in computational complexity, highlighting its efficiency. Overall, the proposed algorithm offers an effective balance between visual quality and computational performance, making it well suited for video transmission in bandwidth-constrained, resource-limited IoT and edge computing environments. Full article

The incidence of Hashimoto’s disease (HD) increases with age and in people who have other autoimmune diseases. It is characterized by lymphocytic infiltration, fibrosis, and atrophy of the thyroid parenchyma with the simultaneous presence of thyroid peroxidase antibodies (ATPO) and/or thyroglobulin antibodies (ATG). Eicosanoids are formed via the cyclooxygenase (COX), lipoxygenase (LOX), and monooxygenase (CYP450) pathways with arachidonic acid (ARA), resulting in the production of epoxyeicosatrienoic acids (EETs) or hydroxyeicosatetraenoic acids (HETEs). These eicosanoids can act in an autocrine or paracrine manner on target cells. This study aimed to examine whether a gluten-free diet (GFD) can modulate the enzymatic pathways of the pro-inflammatory ARA cascade. The study material consisted of serum samples from Caucasian female patients with HD aged 18–55 years. Participants were enrolled in the study based on the presence of an ultrasound characteristic of HD, and elevated serum levels of anti-thyroid peroxidase antibodies and anti-thyroglobulin antibodies. Patients with confirmed celiac disease did not participate in the study. A total of 78 samples were analyzed, with 39 collected after 3 months of following a GFD. Eicosanoids (thromboxane B2, prostaglandin E2, leukotriene B4, and 16R-hydroxy-5Z,8Z,11Z,14Z-eicosatetraenoic acid (16-RS HETE)) were extracted using high-performance liquid chromatography. The contribution of leukotriene (LTB) was analyzed in the LOX pathway, prostaglandins (PGE2) and thromboxane (TXB2) were selected for the involvement of the COX pathway, and 16RS HETE was used for the CYP450 pathway. All parameters were analyzed before and after a 3-month dietary intervention that included a gluten-free diet. In the obtained results, only one mediator, leukotriene B4, was significant (p < 0.05). The mean level on the initial visit was 0.202 ± 0.11 (SD), while it was 0.421 ± 0.27 (SD) on the subsequent visit, indicating a significant increase in its level after implementing a GFD. Although there was a trend in the CYP 450 pathway of decreased 16-RS HETE, the presented correlations show that thromboxane B4 and 16RS-HETE were positively correlated with the body mass and body fat mass of the examined patients. There was a trend in the CYP 450 pathway of decreased 16-RS HETE after GFD. Thromboxane B4 and 16RS-HETE levels before GFD were positively correlated with the body mass and body fat mass of the examined patients. A gluten-free diet in HD does not suppress the synthetic pathways of LOX, COX, or cytochrome P450 (CYP450). The level of adipose tissue has a greater impact on the inflammatory processes in HD than a gluten-free diet. This study does not confirm the suppressive effect of a gluten-free diet on the pro-inflammatory arachidonic acid cascade in any of the three analyzed mediator synthesis LOX, COX, CYP450 pathways. Full article

5-Hydroxymethylfurfural (HMF) is a versatile platform molecule with the potential to replace many fossil fuel derivatives. It can be obtained through the dehydration of carbohydrates. In this study, we present a simple and cost-effective microwave-assisted method for producing HMF. This method involves the use of readily available sucrose as a substrate and glucose-derived bifunctional hydrochars as carbocatalysts. These catalysts were produced via hydrothermal carbonisation using thiourea and urea as nitrogen and sulphur sources, respectively, to introduce Brønsted acidic and basic sites into the materials. Using a microwave reactor, we found that the S, N-doped hydrochars were active in sucrose dehydration in water. Catalytic results showed that HMF yield depended on the balance between acidic and basic sites as well as the types of S and N species present on the surfaces of these hydrochars. The best-performing catalyst achieved an encouraging HMF yield of 37%. The potential of N, S-co-doped biochar as a green solid catalyst for various biorefinery processes was demonstrated. A simple kinetic model was developed to elucidate the kinetics of the main reaction pathways of this cascade process, showing a very good fit with the experimental results. The calculated rate constants revealed that reactions with a 5% sucrose loading exhibited significantly higher fructose dehydration rates and produced fewer side products than reactions using a more diluted substrate. No isomerisation of glucose into fructose was observed in an air atmosphere. On the contrary, a limited rate of isomerisation of glucose into fructose was recorded in an oxygen atmosphere. Therefore, efforts should focus on achieving a high glucose-to-fructose isomerisation rate (an intermediate reaction step) to improve HMF selectivity by reducing humin formation. Full article

Intrinsically disordered regions (IDRs), defined as protein segments lacking stable tertiary structures, are ubiquitously present in the human proteome and enriched with disease-associated mutations. IDRs harbor molecular recognition features (MoRFs) and post-translational modification sites (e.g., phosphorylation), enabling dynamic intermolecular interactions through conformational plasticity. Furthermore, IDRs drive liquid–liquid phase separation (LLPS) of biomacromolecules via multivalent interactions such as electrostatic attraction and pi–pi interactions, generating biomolecular condensates that are essential throughout the cellular lifecycle. These condensates separate intracellular space, forming a physical barrier to avoid interference between other molecules, thereby improving reaction specificity and efficiency. As a dynamically equilibrated process, LLPS formation and maintenance are regulated by multiple factors, endowing the condensates with rapid responsiveness to environmental cues and functional versatility in modulating diverse signaling cascades. Consequently, disruption of LLPS homeostasis can derail its associated biological processes, ultimately contributing to disease pathogenesis. Moreover, precisely because liquid–liquid phase separation (LLPS) is co-regulated by multiple factors, it may provide novel insights into the pathogenic mechanisms of disorders such as autism spectrum disorder (ASD), which result from the cumulative effects of multiple etiological factors. Full article