Search Results (164,541)

Gout and calcium pyrophosphate crystal deposition disease (CPPD) are frequently associated with comorbid disorders, including coronary artery disease and osteoarthritis, in which ectopic calcification with basic calcium phosphate crystals commonly affects arteries and articular cartilage, respectively. Accepting the 2024 G-CAN Gold Medal, I review my research philosophy for translational etiopathogenesis investigation in gout and CPPD, atherosclerosis, responses to arterial injury, and osteoarthritis. Since molecular homeostasis points to pathophysiology and vice versa, I have followed selected molecular players and pathways to phenotypes. Typically, behind each disease target is another target. Illuminating passageways between etiopathogenic pathways is especially productive when using approaches beyond conventional “omics” to reveal the impact of specific post-translational protein modifications, and changes in protein conformation, complex assembly, and interactomes. Highlighting these concepts, I review my past studies on specific molecular pathways, and current perspectives for the following: (i) PP_i, NPP1, ANKH, and transglutaminase 2 (TG2); (ii) relationships between NPP1, ANKH, Vanin-1 Pantetheinase, and ectopic chondrogenesis; (iii) intersections between adenosine, AMPK, CXCL8 and its receptor CXCR2, the receptor for advanced glycation endproducts (RAGE) and chondrocyte hypertrophy; (iv) lubricin homeostasis and proteolysis; (v) receptor for advanced glycation endproducts (RAGE) and TG2-catalyzed post-translational calgranulin modification; (vi) complement activation and C5b-9 assembly, and the nucleotide-bound conformation of TG2. The inescapable conclusion is that these molecular pathways tightly knit crystal arthropathy with both arterial and osteoarthritis comorbidity. Full article

The neglected Chagas disease, a zoonosis caused by the Trypanosoma cruzi parasite, has limited treatment options like nifurtimox and benznidazole, known for their toxic effects and controversial efficacy. Natural products present opportunities for therapeutic alternatives, particularly in Chile, which has a rich variety of endemic flora. This study focused on the Chilean Buddleja globosa, evaluating the antioxidant activities and biological effects of its methanolic extract (MET) and BG500, an enriched iridoid fraction (6-O-methylcatalpol), against T. cruzi trypomastigotes. Although the trypanocidal activity of the extract was significantly lower than that of nifurtimox (280 ± 3.5 vs. 5.0 ± 0.5), its selectivity was comparable (selectivity index > 15). The MET and enriched fraction also induced hyperpolarization of mitochondrial membrane potential (ΔΨm). In silico docking studies suggested that T. cruzi’s Old Yellow (OYE) could be a potential target for 6-O-methylcatalpol. This work provides the first report on the potential trypanocidal activity of a B. globosa extract, highlighting the need for further studies to connect ΔΨm and OYE inhibition to the effects of 6-O-methylcatalpol. Full article

In this study, a hybrid optoelectronic synthetic aperture radar (SAR) moving target detection and imaging (OCMTI) method is introduced to address the challenges faced when processing large volumes of SAR data while focusing on key moving targets. Traditional algorithms often demand substantial computational resources, with the Fourier transform representing a widely implemented yet computationally intensive operation (typically O(N²) or O(NlogN) complexity). In contrast, optical systems can perform Fourier transforms inherently at the speed of light. The OCMTI method leverages this advantage and integrates optical and electronic processing to enable the rapid detection and selective imaging of moving targets. First, imaging parameters are dynamically configured based on the velocity range of the moving targets of interest and multiple coarse images of the entire scene are generated using an optical system. These images are then processed using a computer-aided detection system to identify candidate targets, and each target is subjected to fine imaging and parameter estimation. The refined images of detected targets are finally integrated into a single image with a suppressed background. The OCMTI method can rapidly detect moving targets, and the time complexity of moving target detection is proportional to the number of image pixels. The correct detection rate for a single image can reach 97%. The efficiency of this method in detecting and imaging moving targets is experimentally validated, which reveals it as a promising solution for time-sensitive applications. The OCMTI method bridges optical speed with electronic flexibility, thereby advancing SAR systems toward real-time, target-oriented operations. Full article

Background/Objectives: The aim of our research was to understand how excipients, unit operations, and process parameters impact processability and resulting properties, performance, and stability of tablets containing bovine lactoferrin, a cohesive biomacromolecule. Methods: Microcrystalline cellulose (MCC), croscarmellose (xCMC), lactose (LAC), hydroxypropyl methylcellulose (HPMC), and sodium stearyl fumarate (SSF) were used to produce various tablet formulations containing lactoferrin across a concentration range of 5 to 45%, targeting immediate- or controlled release performance. Tablets were made either by direct compression or via dry granulation followed by tableting. In addition to release performance, tablet attributes were characterized for tensile strength, friability, weight uniformity, and content uniformity. Results: Acceptable tablet tensile strength, friability, and performance were obtained for lactoferrin concentrations ranging from 15 to 45%, using a variety of excipients and manufacturing approaches. In several cases, dry granulation improved content uniformity. Excipient choice and tablet compression force impacted drug release, particularly when MCC alone was used as dry binder for immediate release. Dry granulation impacted tablet tensile properties, but did not significantly impact release performance. Lactoferrin–excipient compatibility was demonstrated for up to 2 years in ambient laboratory conditions. Conclusions: The study demonstrates that robust tablets can be produced using excipients and processes amenable to scale-up for industrial production. Consistent, stable, and suitably performing tablets were successfully produced using a variety of excipients, processing approaches, and across a broad concentration range with this cohesive biomacromolecule active pharmaceutical ingredient (API). Both immediate- and controlled release performance modes were possible. Full article

To address the problem of point-cloud registration accuracy degradation or even failure in traditional Voxelized GICP(VGICP) under bad initial pose due to improper voxel resolution settings, this paper proposes an Adaptive Resolution VGICP (AR-VGICP) algorithm. The algorithm first automatically estimates the initial voxel resolution based on the absolute deviations between source points outside the target voxel grid and their nearest neighbors in the target cloud, using the Median Absolute Deviation (MAD) method, and performs initial registration. Subsequently, the voxel resolution is dynamically updated according to the average nearest neighbor distance between the transformed source points and the target points, enabling progressive refined registration. The resolution update process terminates until the resolution change rate falls below a predefined threshold or the updated resolution does not exceed the density-adaptive resolution. Experimental results on both simulated and real-world datasets demonstrate that AR-VGICP achieves a 100% registration success rate, while VGICP fails in some cases due to small voxel resolution. On the KITTI dataset, AR-VGICP reduces translation error by 9.4% and rotation error by 14.8% compared to VGICP with a fixed 1 m voxel resolution, while increasing computation time by only 3%. Results from UAV LiDAR experiments show that, in residential area data, AR-VGICP achieves a maximum reduction of 33.4% in translation error and 21.4% in rotation error compared to VGICP (1.0 m). These results demonstrate that AR-VGICP attains a higher registration success rate when the initial pose between point-cloud pairs is bad, and delivers superior point-cloud registration accuracy in urban scenarios compared to VGICP. Full article

Pervious concrete is challenged by the inherent trade-off between permeability and mechanical strength. This study presents a systematic optimization of its mix design to achieve a balance between these properties. Single-factor experiments and an L₉(3³) orthogonal array test were employed to evaluate the effects of target porosity (14–26%), water–cement ratio (0.26–0.34), sand rate (0–10%), and VMA dosage (0–0.02%). Additionally, Spearman rank correlation analysis and nonlinear regression fitting were utilized to develop quantitative relationships correlating the measured porosity to material performance. The results revealed that increasing target porosity enhances permeability but reduces compressive and splitting tensile strengths. The optimal water-to-cement ratio (w/c) was found to be 0.32, balancing both permeability and strength. An appropriate sand content of 6% improved mechanical properties, while a VMA dosage of 0.01% effectively enhanced bonding strength and workability. The orthogonal experiment identified the optimal mix ratio as a w/c ratio of 0.3, VMA dosage of 0.12%, target porosity of 14%, and sand content of 7%, achieving a compressive strength at 28-days of 43.5 MPa and a permeability coefficient of 2.57 mm·s⁻¹. Empirical relationships for the permeability coefficient and mechanical properties as functions of the measured porosity were derived, demonstrating a positive exponential correlation between the measured porosity and the permeability coefficient, and a negative correlation with compressive and splitting tensile strengths. This research provides a systematic framework for designing high-performance pervious concrete with balanced permeability and mechanical properties, offering valuable insights for its development and application in green infrastructure projects. Full article

The increasing frequency and severity of forest fires, driven by climate change and intensified human activities, pose substantial threats to ecological security and sustainable development. However, most assessments remain centered on occurrence risk, lack a resilience-oriented perspective and comprehensive indicator systems, and therefore offer limited guidance for building system resilience. This study developed a forest fire resilience (FFR) assessment framework with 25 indicators in three levels and six domains across four resilience dimensions. Balancing expert judgment and data, we obtained indicator weights by integrating the Analytic Hierarchy Process (AHP) and the Criteria Importance Through Intercriteria Correlation (CRITIC) via a game-theoretic scheme. The analysis revealed that, among the level-2 indicators, climate factors, infrastructure, and vegetation characteristics exert the greatest influence on FFR. At the level-3 indicator scale, monthly minimum relative humidity, fine fuel load per unit area, and the deployment of smart monitoring systems were critical. Among the four resilience dimensions, absorption capacity plays the predominant role in shaping disaster response. Building on these findings, the study proposes targeted strategies to enhance FFR and applies the assessment framework to twelve administrative divisions of Baise City, China, highlighting marked spatial variability in resilience levels. The results offer valuable theoretical insights and practical guidance for strengthening FFR. Full article

This study aimed to develop a novel biomaterial for neural tissue regeneration by combining chitosan (CS), a natural polymer, with graphene oxide (GO) at concentrations of 3%, 6%, and 9%. The homogeneity, conductivity, three-dimensional characteristics, and ability to support cell viability of the composite materials were systematically evaluated. Fourier-Transform Infrared (FTIR) spectroscopy confirmed the successful incorporation of GO into the CS matrix, while UV-Vis and photoluminescence (PL) spectrometry revealed modifications in the optical properties with increasing GO content. Thermogravimetric analysis (TG-DSC) demonstrated improved thermal stability of the composites, and swelling tests indicated enhanced water absorption capacity. Although some agglomerates were observed, the homogeneity was reasonable at both macroscopic and microscopic level (optical visualization–FTIR and electron microscopy). The composite films exhibited promising physical and electrochemical properties, highlighting their potential for neural tissue engineering applications. Their biological activity was assessed by culturing neuronal cells on the CS-GO scaffolds. Results from MTT, LDH, and LIVE/DEAD assays demonstrated excellent cell viability, moderate-to-good cell attachment, and the promotion of intercellular network formation. Among the tested formulations, the CS-GO 6% scaffold showed the most favorable biological response, with a significant increase in SH-SY5Y cell viability after 7 days (p < 0.05) compared to the CS control. LIVE/DEAD imaging confirmed enhanced cell attachment and elongated morphology, while the LDH assay indicated minimal cytotoxicity. Notably, a critical threshold was identified between 6% and 9% GO, where conductivity increased by approximately 52-fold. Future studies should focus on optimizing the composite parameters, loading them with specific biologically active agents and thus targeting specific neuronal applications. Full article

Non-Hodgkin B-cell lymphomas are a heterogeneous group of lymphoid malignancies with variable biological behavior, clinical presentation and treatment response. While chemoimmunotherapy remains the cornerstone of their management, growing evidence implicates the gut microbiota as a critical modulator of both lymphomagenesis and therapeutic efficacy. Gut microbiota dysbiosis, characterized by reduced microbial diversity and pathogenic taxonomic shifts, has been observed also in newly diagnosed patients and not just after therapy. This microbial imbalance contributes to mucosal barrier disruption, systemic inflammation, and altered immune responses, affecting treatment outcomes and toxicity profiles. Antibiotic exposure, especially broad-spectrum agents, exacerbates dysbiosis and has been associated with inferior responses to immunochemotherapy and CAR T-cell therapy. Conversely, certain commensal taxa, like Faecalibacterium prausnitzii and Lactobacillus johnsonii, may exert protective effects by preserving mucosal homeostasis and promoting antitumor immunity. Targeted interventions, including prudent antibiotic stewardship, prebiotics, probiotics, dietary modulation, and fecal microbiota transplantation, are under investigation to restore eubiosis and improve clinical outcomes. Preliminary clinical trials suggest a strong correlation between baseline microbiome composition and therapeutic response. Further mechanistic studies and randomized trials are warranted to define the causal role of the microbiome in non-Hodgkin B-cell lymphomas pathophysiology and to develop personalized microbiome-modulating strategies as adjuncts to standard treatment. Full article

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is characterized by the predominance of optic neuritis, myelitis, acute disseminated encephalomyelitis (ADEM), and cortical encephalitis, and can be diagnosed by the presence of pathogenic immunoglobulin G (IgG) antibodies targeting the extracellular domain of MOG in the serum and cerebrospinal fluid (CSF). Initially considered a variant of multiple sclerosis (MS) or neuromyelitis optica spectrum disorder (NMOSD), it is now widely recognized as a separate entity, supported by converging evidence from serological, pathological, and clinical studies. Patients with MOGAD often exhibit better recovery from acute attacks; however, their clinical and pathological features vary based on the immunological role of MOG-IgG via antibody- or complement-mediated perivenous demyelinating pathology, in addition to MOG-specific cellular immunity, resulting in heterogeneous demyelinated lesions from vanishing benign forms to tissue necrosis, even though MOGAD is not a mild disease. The key is the immunological mechanism of devastating lesion coalescence and long-term degenerating mechanisms, which may still accrue, particularly in the relapsing, progressing, and aggressive clinical course of encephalomyelitis. The warning features of the severe clinical forms are: (1) fulminant acute multifocal lesions or multiphasic ADEM transitioning to diffuse (Schilder-type) or tumefactive lesions; (2) cortical or subcortical lesions related to brain atrophy and/or refractory epilepsy (Rasmussen-type); (3) longitudinally extended spinal cord lesions severely affected with residual symptoms. In addition, it is cautious for patients refractory to acute stage early 1st treatment including intravenous methylprednisolone treatment and apheresis with residual symptoms and relapse activity with immunoglobulin and other 2nd line treatments including B cell depletion therapy. Persistent MOG-IgG high titration, intrathecal production of MOG-IgG, and suggestive markers of higher disease activity, such as cerebrospinal fluid interleukin-6 and complement C5b-9, could be identified as promising markers of higher disease activity, worsening of disability, and poor prognosis, and used to identify signs of escalating treatment strategies. It is promising of currently ongoing investigational antibodies against anti-interleukin-6 receptor and the neonatal Fc receptor. Moreover, due to possible refractory issues such as the intrathecal production of autoantibody and the involvement of complement in the worsening of the lesion, further developments of other mechanisms of action such as chimeric antigen receptor T-cell (CAR-T) and anti-complement therapies are warranted in the future. Full article

Tea tree seeds are highly sensitive to dehydration and cannot be stored for extended periods, making surface defect detection crucial for preserving their germination rate and overall quality. To address this challenge, we propose Cgc-YOLO, an enhanced YOLO-based model specifically designed to detect small-scale and complex surface defects in tea seeds. A high-resolution imaging system was employed to construct a dataset encompassing five common types of tea tree seeds, capturing diverse defect patterns. Cgc-YOLO incorporates two key improvements: (1) GhostBlock, derived from GhostNetV2, embedded in the Backbone to enhance computational efficiency and long-range feature extraction; and (2) the CPCA attention mechanism, integrated into the Neck, to improve sensitivity to local textures and boundary details, thereby boosting segmentation and localization accuracy. Experimental results demonstrate that Cgc-YOLO achieves 97.6% mAP50 and 94.9% mAP50–95, surpassing YOLO11 by 2.3% and 3.1%, respectively. Furthermore, the model retains a compact size of only 8.5 MB, delivering an excellent balance between accuracy and efficiency. This study presents a robust and lightweight solution for nondestructive detection of tea seed defects, contributing to intelligent seed screening and storage quality assurance. Full article

Rice lipoxygenase 3 (OsLOX3) is a lipid hydroperoxidase found in rice embryos. Previous studies have reported that OsLOX3 is associated with seed quality and stress resistance, however, its relationship with grain shape and weight remains unknown. In this study, the first exon of OsLOX3 gene was edited in the indica rice variety GDR998 using CRISPR/Cas9 technology. Two homozygous mutants, Oslox3-1 (single-base deletion) and Oslox3-2 (single-base insertion) were identified among eight positive mutant plants from the T2 generation. The agronomic evaluation of genotypic OsLOX3 mutants showed significant increase in grain length, grain length-to-width ratio, 1000-grain weight, plant height, panicle length, and yield per plant compared with the wild type GDR998. The number of effective panicles and total grains per panicle did not significantly change. Further germination tests of seeds after three years of natural aging revealed that, compared with the control GDR998, the germination percentages of the mutants Oslox3-1 and Oslox3-2 increased significantly by 41.1% and 45.6%, respectively. These findings indicate that the knockout of OsLOX3 simultaneously improve grain weight and seed vigor, providing valuable germplasm resources for rice breeding targeting high-yield, improved seed longevity and rice quality. Full article

Colorectal cancer is one of the most common malignancies worldwide, with liver metastasis being one of its primary metastatic patterns and a significant cause of death. For most patients with unresectable colorectal cancer liver metastasis, a comprehensive treatment strategy that includes chemotherapy and targeted therapy is the primary therapeutic strategy. However, significant breakthroughs in immune therapy for liver metastasis have yet to be achieved. In this article, we summarize the characteristics of the immune microenvironment in colorectal cancer liver metastases and the mechanisms of immune resistance. Additionally, we compile recent clinical trial results on immune combination strategies and biomarker studies and discuss the prospects for applying immune checkpoint inhibitors in the treatment of colorectal cancer liver metastasis. Full article

This study aims to guide the management and service of highways towards a more efficient and intelligent direction, and also provides intelligent and green data support for achieving sustainable development goals. The forecasting of traffic flow at highway stations serves as the cornerstone for spatiotemporal analysis and is vital for effective highway management and control. Despite considerable advancements in data-driven traffic flow prediction, the majority of existing models fail to differentiate between directions. Specifically, entrance flow prediction has applications in dynamic route guidance, disseminating real-time traffic conditions, and offering optimal entrance selection suggestions. Meanwhile, exit flow prediction is instrumental for congestion and accident alerts, as well as for road network optimization decisions. In light of these needs, this study introduces an enhanced heterogeneous spatiotemporal graph network model tailored for predicting highway station traffic flow. To accurately capture the dynamic impact of upstream toll stations on the target station’s flow, we devise an influence probability matrix. This matrix, in conjunction with the covariance matrix across toll stations, updated graph structure data, and integrated external weather conditions, allows the attention mechanism to assign varied combination weights to the target toll station from temporal, spatial, and external standpoints, thereby augmenting prediction accuracy. We undertook a case study utilizing traffic flow data from the Chengdu-Chengyu station on the Sichuan Highway to gauge the efficacy of our proposed model. The experimental outcomes indicate that our model surpasses other baseline models in performance metrics. This study provides valuable insights for highway management and control, as well as for reducing traffic congestion. Furthermore, this research highlights the importance of using data-driven approaches to reduce carbon emissions associated with transportation, enhance resource allocation at toll plazas, and promote sustainable highway transportation systems. Full article

To address the challenges of dispersing aerial targets such as bird flocks at civilian airports and drones conducting low-altitude surveillance in critical areas, including ports and convention centers, this paper proposes a hybrid Artificial Potential Field-Particle Swarm Optimization (APF–PSO) algorithm. The proposed solution integrates the real-time collision-avoidance capability of the artificial potential field method with the global network-optimization characteristics of the particle swarm algorithm to maximize protective coverage. Simulation results demonstrate that the hybrid algorithm achieves optimal performance in dispersion of aerial targets based on protective coverage under safety constraints, confirming its superior performance. The key innovations lie in implementing a dynamic repulsion field with exponential gain for emergency maneuvers, introducing a vertical avoidance module to resolve deadlock issues, and establishing a novel decoupled cooperative paradigm for scalable aerial protection networks. Full article