Search Results (4,012)

Rheumatoid arthritis (RA) remains a recalcitrant clinical challenge, as modern therapies are often hampered by adverse effects, suboptimal responses, and failure to achieve radical cure. Traditional Chinese Medicine (TCM) and Tujia ethnomedicine, with centuries of accumulated experience in managing RA (classified as “Bi Syndrome” in TCM), offer distinct theoretical frameworks and abundant therapeutic resources. TCM emphasizes syndrome differentiation-based holistic regulation, while Tujia ethnomedicine relies on indigenous medicinal plants and empirically derived therapies shaped by its unique geographical context. This review aims to accelerate the integration of traditional wisdom with contemporary pharmacology for the development of novel RA therapies. A comprehensive literature search was performed across PubMed, Web of Science, CNKI, and ethnomedical monographs to synthesize data on their theoretical underpinnings, therapeutic strategies, mechanisms of action, and clinical efficacy. TCM and Tujia ethnomedicine possess significant anti-RA effects, characterized by multi-component, multi-target synergistic mechanisms that complement modern medicine. However, they face common challenges including unclear material bases of active components, insufficient standardized clinical evidence, and inadequate quality control protocols. This review provides a critical foundation for integrating TCM/Tujia ethnomedicine with modern pharmacology, highlighting the urgent need for further research to clarify active constituents, establish standardized protocols, and validate clinical efficacy—ultimately facilitating the development of safer, more effective RA therapies. Full article

Background: Natto, a well-known fermented soybean product beneficial for bone health, remains unclear in its mechanism. Methods: This study investigated its effect on secondary osteoporosis (OP) in mice. Results: Natto significantly inhibited weight loss, bone quality deterioration, and bone morphological damage, and regulated OPG/RANKL pathway protein expression (p < 0.05) in OP mice. Analysis of 16S rRNA revealed that natto increased gut microbiota α-diversity and the abundance of Sutterella, Roseburia, and Coprococcus, while reducing harmful bacteria such as Streptococcus, Shigella, and Helicobacter. These microbial changes positively correlated with body weight, bone size, and serum osteogenic metabolism in OP mice. Serum metabolomics showed differential metabolites of the natto group enriched in PPAR signaling and primary bile acid biosynthesis. Verification by mRNA and ELISA indicated that the upregulated liver and circulating PPARα by natto may regulate downstream bile acid pathways, linking gut microbiota to multi-organ metabolic functions. Conclusions: In summary, natto may act on gut microbiota to alleviate bone loss via the “gut microbiota–bile acid–OPG/RANKL” network, targeting multiple organs including gut, liver, and bone. This provides a theoretical basis for natto dietary intervention in osteoporosis prevention through the gut–bone axis. Full article

Executing multi-UAV cooperative pursuit in complex public domains requires balancing interception efficiency with flight safety under strict micro-platform constraints. Existing planners often struggle with high computational overhead or lack kinodynamic adaptability in heterogeneous environments. To address this, we propose AC2F, a lightweight Adaptive Coarse-to-Fine hybrid framework featuring a bidirectional state-switching mechanism. The framework utilizes the Apollonius circle for efficient global guidance during the coarse phase, dynamically transitioning to a Dynamic Window Approach (DWA) upon detecting path oscillations or entering terminal capture zones. To ensure robustness, a dual-layer parameter paradigm integrates offline Bayesian optimization for globally optimal baselines with online real-time weight adaptation based on target distance. Extensive simulations show that AC2F effectively escapes local minima, such as urban-style U-shaped traps. Real-world suburban validation confirms an 86% capture rate with minimal computational overhead, demonstrating AC2F’s suitability for public domain protection and civil security. Full article

Cancer is still one of the world’s major causes of morbidity and mortality; thus, safer and more efficient treatment approaches are required. The structural variety, multitargeted mechanisms, and generally good safety profiles of plant-derived polyphenols have made them attractive anticancer medicines. Flavonoids (like quercetin), stilbenes (like resveratrol), phenolic acids and curcuminoids (like curcumin) are major classes that have shown strong anticancer action against a variety of cancers, including prostate, colorectal and breast cancers. Through targets including PI3K/Akt, MAPK, NF-κB, and p53 signaling networks, these substances influence important molecular pathways involved in tumor initiation and development, including oxidative stress, inflammation, apoptosis, cell cycle control, angiogenesis and metastasis. The clinical translation of polyphenols is still constrained by poor bioavailability, fast metabolism, low aqueous solubility and inefficient pharmacokinetic characteristics, which lead to insufficient systemic exposure and therapeutic efficacy despite strong preclinical data. Their therapeutic applicability is further complicated by variations in absorption and possible dose-related restrictions. To overcome these limitations, the anticancer efficacy of polyphenols has been enhanced via delivery technologies like polymeric nanoparticles, lipid-based carriers, nanoemulsions and phytosome complexes, which have shown improved stability, increased bioavailability and targeted delivery to tumor tissues. This review provides a comprehensive and integrative analysis of plant-derived polyphenols by linking molecular mechanisms, pharmacokinetic limitations and emerging delivery strategies within a translational framework. By bridging these interconnected domains, this review highlights the potential of polyphenols as viable candidates in next-generation cancer therapeutics and underscores the need for well-designed clinical studies to facilitate their successful integration into oncology practice. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality, with substantial heterogeneity that is not fully explained by genetic alterations alone. Emerging evidence positions metabolic reprogramming as a central driver of tumor behavior, integrating glycolysis, mitochondrial function, lipid and amino acid metabolism, and autophagy into coordinated networks that extend beyond cancer cells to the tumor microenvironment. Tumor–immune metabolic competition and metabolite-mediated signaling shape immune responses, often promoting immunosuppression and resistance to immunotherapy, particularly in microsatellite-stable (MSS) CRC. Systemic factors, including obesity, insulin resistance, and the diet–microbiota axis, further modulate tumor metabolism and immune function, reinforcing disease progression. Metabolic biomarkers reflecting these multi-level interactions, spanning tumor-intrinsic pathways, immune contexture, and host metabolism, offer promising opportunities for improved patient stratification and therapeutic targeting, although clinical validation remains limited. Current treatments, including chemotherapy, targeted agents, and immune checkpoint inhibitors, are effective in selected subgroups but are constrained by resistance mechanisms. In this review, we propose an integrative immunometabolic framework in which tumor, immune, and systemic metabolic processes co-evolve, defining CRC progression and treatment response. Targeting this interconnected network through combinatorial and metabolism-oriented strategies may enable precision therapies, particularly for immunotherapy-resistant MSS CRC. Full article

This paper presents Resilient Edge-IVA (Intelligent Video Analytics), an integrated framework designed to ensure real-time inference stability and high-speed embedding-based similarity search in resource-constrained edge computing environments. Conventional systems often face Quality of Experience (QoE) degradation caused by computational overhead and hardware-level bottlenecks. To address these challenges, this study proposes a “Whole-cycle” methodology employing a perception-driven, three-tier adaptive control algorithm. This algorithm dynamically modulates encoding parameters, such as resolution and bitrate, by utilizing real-time inference latency and CPU utilization as feedback signals. Furthermore, the framework incorporates an event-density-based Data Diet mechanism. This mechanism selectively adjusts video quality based on object detection results, preserving high-fidelity imagery for critical events while significantly reducing data volume during static intervals. The backend implements a hybrid storage architecture combining the Milvus vector database for CLIP-based high-dimensional visual embeddings with a PostgreSQL relational database for structured metadata. These systems are linked via a deterministic hash key to ensure data atomicity and facilitate high-speed, multi-dimensional embedding-based retrieval. Experimental evaluations conducted on a Raspberry Pi 5 and Hailo-8 NPU demonstrate that the proposed framework maintains a frame drop rate below 0.3% even under extreme workloads, providing a 13-fold improvement in operational stability over static configurations. The results also confirm a 54.2% reduction in total storage occupancy and a Hash Mapping Consistency (HMC) score of 0.89. These findings validate the framework’s effectiveness in reconciling real-time processing stability with storage efficiency. Building upon this baseline, future research will extend the framework to multi-class environments, targeting applications such as Intelligent Transport Systems (ITS). Full article

Scorpion venom peptides, with their stable disulfide backbone, compact structural framework, and highly selective regulation of ion channels, have long been regarded as important molecular probes in neuropharmacology. However, recent studies have revealed their potential for regulating oxidative stress, inflammation, and neuroprotection, making them a new research frontier. In this article, we focus on scorpion venom peptides as drugs, constructing an integrated knowledge framework from structural classification to clinical translation. First, scorpion venom peptides are systematically classified based on cysteine arrangement patterns and three-dimensional folding topology, and their structure–activity relationships are summarized. Based on this, the molecular mechanisms by which scorpion venom peptides regulate ion channels are systematically analyzed. We review the emerging pharmacological activities of scorpion venom peptides. Of particular note, the representative molecule SVHRSP has shown multi-target synergistic antioxidant and neuroprotective activity in models of Parkinson’s disease. We also systematically evaluate the application of engineering strategies, including cyclisation modification, nanodelivery, recombinant expression, and AI-assisted optimization, to overcome the translational bottlenecks in the development of scorpion venom peptides. However, it should be noted that most SVHRSP-related findings have been reported by a single research group; independent replication, pharmacokinetic characterization, and human efficacy data are still lacking. Its IND approval permits clinical investigation but does not yet constitute proven therapeutic benefit in patients. By integrating molecular structure, redox regulation mechanisms, and translational medicine perspectives, this review aims at providing a theoretical basis and practical pathways for scorpion venom peptides as precision therapeutic molecules for oxidative stress-related diseases. Full article

Macrophages are highly plastic innate immune cells that adopt context-dependent phenotypes along a continuum, integrating developmental origin with local microenvironmental cues rather than conforming to discrete M1/M2 states. This review delineates the molecular circuits shaping macrophage identity—TLR/cytokine signaling, microRNA networks, metabolic rewiring, and epigenetic mechanisms including histone lactylation—and traces how circulating monocyte subsets contribute to tissue macrophage diversity. We examine macrophage plasticity across a broad disease spectrum—oncology, autoimmune and rheumatic diseases, inflammatory bowel disease, infectious diseases, metabolic disorders, and neurological conditions—showing that the pathogenic phenotype is strikingly context-dependent: for instance, M2-like tumor-associated macrophages promote immune evasion in solid tumors, whereas M1-skewed programs drive tissue damage in autoimmunity. Soluble markers (sCD163, sCD14, soluble mannose receptor) are emerging biomarkers of disease activity and prognosis. High-dimensional flow cytometry and mass cytometry (CyTOF) bridge molecular biology and clinical phenotyping, enabling integrated readouts of surface phenotype, intracellular signaling, and metabolic state. Therapeutic strategies discussed include selective tumor-associated macrophage (TAM) reprogramming, chimeric antigen receptor (CAR)-M cell therapies, and biomaterial-based platforms. Future priorities encompass spatially resolved multi-omics, epigenetic and metabolic targeting, and macrophage-centered vaccine approaches. Standardized cytometry panels will be essential for biomarker-guided stratification and context-specific interventions. Full article

Background/Objectives: Metabolic syndrome (MetS) is a pressing global health challenge comprising obesity, hyperglycemia, hypertension, and hyperlipidemia. Conventional polypharmacy often presents long-term compliance issues and side effects. Eucommia ulmoides Oliv., a traditional medicinal and edible plant rich in iridoids, lignans, flavonoids, and polysaccharides, has emerged as a promising natural intervention. This review aims to systematically summarize the bioavailability and multifaceted pharmacological mechanisms of E. ulmoides and its bioactive components in alleviating MetS. Methods: We comprehensively reviewed the recent in vitro and in vivo literature to map the functional evidence, specific signaling pathways, and gut microbiota–host interactions associated with E. ulmoides extracts and its key phytochemicals (e.g., asperuloside) against various metabolic dysfunctions. Results: Current evidence indicates that E. ulmoides operates through a “multi-component, multi-target, and multi-pathway” paradigm. For hyperlipidemia and obesity, it activates hepatic lipid metabolism (PPARα/CPT1A, FXR/CYP7A1) and mitigates oxidative stress (Nrf2/ARE). Furthermore, it dose-dependently reshapes the gut microbiota by enriching beneficial bacteria like Akkermansia and increasing butyrate production, exerting profound gut–liver axis regulation. It also ameliorates hypertension by activating the ACE2-Ang-(1–7)-Mas axis, improves insulin resistance via the AMPK/PI3K/Akt cascade, and manages hyperuricemia by modulating XOD and renal transporters. Notably, the low oral bioavailability of its glycosides highlights the crucial role of gut microbial hydrolysis in its efficacy. Conclusions: E. ulmoides holds substantial therapeutic potential as a multi-target natural supplement for MetS. However, future translational applications necessitate large-scale randomized clinical trials, multi-omics studies to further clarify host–microbiome interactions, and the development of standardized formulations to ensure clinical efficacy. Full article

Enhancing agricultural economic resilience (AER) is essential for global food security. As a key policy tool for stabilizing agricultural production, policy-based agricultural insurance lacks rigorous causal evidence on its impact on resilience. In this study, AER is operationalized as a composite index capturing resistance and recovery capacities across pressure, state, and response dimensions. Using 2012–2023 provincial panel data from China (31 provinces × 12 years = 372 observations), we measure AER via the entropy method and identify policy effects using a staggered multi-timepoint difference-in-differences (DID) model. We find that policy-based staple crop insurance significantly increases AER by approximately 2.5 percentage points, primarily by promoting agricultural technological innovation (ATI) and regional industrial structure upgrading (RIS). The improvement effects are more pronounced in central and western regions, non-major staple-crop producing areas, and regions with higher natural risks. Robustness is confirmed via event study, alternative weighting schemes (PCA and equal weighting), and placebo tests. This study provides reliable causal evidence for the resilience-enhancing effect of agricultural insurance and clarifies its internal transmission mechanisms, offering empirical support for the optimization of agricultural risk governance policies. Limitations include the use of provincial-level aggregate data and the lack of analysis of spatial spillover effects between regions. Our findings suggest that differentiated policy implementation can support more sustainable and targeted agricultural risk governance. Full article

Neuroblastoma (NB), the most common extracranial solid tumor of childhood, exemplifies one of the most formidable paradigms of tumor immune evasion (TIME) in pediatric oncology. Despite significant advances in multimodal therapy and the clinical integration of immunotherapeutic strategies, high-risk NB (HR-NB) remains largely refractory to durable immune control. This failure reflects not an absence of immune engagement, but the presence of a highly evolved and developmentally wired immune escape architecture. In this review, we synthesize emerging insights from single-cell, multi-omics, and functional studies to define how developmental lineage, cellular plasticity, metabolic rewiring, epigenetic regulation, and therapy-induced adaptation converge to engineer immune blindness in NB. We discuss how NB’s neural crest origin establishes a baseline of low immunogenicity, which is subsequently reinforced through coordinated suppression of antigen presentation, dominance of immune checkpoint signaling, and profound dysfunction of cytotoxic T and natural killer cells within an immunosuppressive tumor microenvironment. Central to this process is tumor-intrinsic plasticity, whereby lineage instability and dedifferentiation, exacerbated by therapeutic pressure, embed immune silence as a stable tumor state. We highlight evidence positioning RD3 as a master upstream regulator linking cellular identity to immune visibility, governing antigen presentation, innate immune sensing, checkpoint expression, and cytotoxic lymphocyte engagement. Beyond tumor-intrinsic mechanisms, we examine the roles of immunosuppressive myeloid populations, tumor-derived exosomes, metabolic stress, hypoxia, and ferroptosis-associated pathways in reinforcing immune paralysis. Finally, we outline emerging therapeutic strategies aimed at dismantling this architecture, including combinatorial checkpoint blockade, metabolic and epigenetic reprogramming, exosome-targeted interventions, and next-generation immune engineering platforms. Together, this review reframes TIME in NB as a programmable, developmentally rooted process and provides a mechanistic roadmap for restoring immune competence and therapeutic susceptibility in HR disease. Full article

Type 1 Diabetes (T1D) is a complex autoimmune disorder characterized by immune-mediated destruction of pancreatic β cells, driven by genetic susceptibility and modulated by environmental factors, notably the gut microbiome. Dysbiosis, manifested as reduced microbial diversity, perturbations in the Firmicutes/Bacteroidetes ratio, and compromised short-chain fatty acid production, contributes to T1D pathogenesis through mechanisms involving immune system dysregulation and heightened intestinal permeability. Emerging evidence indicates a relationship between the gut and oral microbiomes, as well as the potential influence of the virome and mycobiome. This narrative review synthesizes the current literature on the intricate interplay between the gut microbial ecosystem, the host immune response, and the development of T1D, highlighting the potential for targeted microbiome-based interventions to ameliorate disease progression. A more nuanced understanding of these multi-kingdom interactions is essential for developing precise therapeutic strategies to prevent or delay T1D onset and to improve patient outcomes through restoration of immune tolerance and gut homeostasis. Full article

Vision Transformers (ViTs) have achieved strong performance in computer vision, but their adversarial robustness remains underexplored. Existing ViT-oriented attacks mainly rely on iterative optimization, leading to high generation cost and limited transferability. Moreover, most generative attacks target a single class, making them inefficient for multi-target scenarios. To address these issues, we propose Attention-Guided Multi-Target Generative Adversarial Attack (AMGAA). AMGAA leverages ViT self-attention to guide target feature fusion and adaptively selects important source patches for perturbation generation. It jointly optimizes adversarial, attention constraint, and total variation losses to improve targeted attack success while preserving visual naturalness. Experiments on CIFAR-10 and ImageNet show that AMGAA achieves average attack success rates (ASRs) of 43.2% and 39.0% in ImageNet single-target transfer attacks and CIFAR-10 multi-target attacks, respectively. Compared with the generative attack methods evaluated in our experiments, AMGAA improves ASR by 5.7 percentage points in the multi-target setting and by 8.1 percentage points in unknown-class generalization. AMGAA also obtains a low LPIPS of 0.018, indicating good visual imperceptibility. Ablation studies confirm the effectiveness of its key components. Full article

Drawing on moral cleansing theory, this study adopts an actor-centered perspective to examine how ingratiation relates to employees’ moral rumination and subsequent coworker-directed cooperative behavior, thereby offering insights to help organizations to understand and guide such behaviors. Using a multi-wave survey design, this study collected data from 272 employees to examine a theoretical model investigating how employee ingratiation influences coworker-directed cooperative behavior through moral rumination, while also examining the moderating role of employee moral identity. The results indicate that employee ingratiation positively influences moral rumination, which in turn enhances coworker-directed cooperative behavior. Furthermore, the indirect effect of ingratiation on coworker-directed cooperative behavior via moral rumination is strengthened among employees with high moral identity. This study advances the literature by shifting the focus from targets and observers to actors themselves, examining how ingratiation shapes actors’ own moral perception and subsequent behavior. It further contributes by introducing moral rumination as a mediating mechanism and exploring the moderating effect of moral identity, as well as offering new insights into ingratiation in organizational contexts. Full article

Background: Acute myocardial infarction (AMI) remains the most lethal critical emergency worldwide. Although Angong Niuhuang Pill (ANP) is an established rescue medicine that has demonstrated outstanding therapeutic potential for cardiovascular diseases, its modern molecular mechanism has never been systematically elucidated because of its chemical complexity and unidentified targets. Methods: This study utilizes a multi-layer analytical pipeline of AI mining, network pharmacology, transcriptomics, and experimental confirmation. The components of ANP were comprehensively identified by UHPLC-Q Exactive Orbitrap HRMS. The TranSiGen algorithm was utilized to deeply mine the data and rank the components according to their relevance to AMI. The top 20 components were selected as prior weights and introduced into network pharmacology for analysis. Subsequently, a mouse model of AMI was established by ligating the left coronary artery. Cardiac function in the mice was evaluated by echocardiography and serum biochemical indicators. The pathological changes in the heart tissue were assessed by hematoxylin-eosin (H&E) and Masson staining. Cardiac transcriptome sequencing was performed, and pathway enrichment was analyzed by KEGG. The key pathways were verified by qPCR and immunofluorescence, achieving cross-validation between AI prediction and experimental findings. Results: The identification of ANP resulted in the detection of a total of 73 compounds, and the TranSiGen algorithm was employed to prioritize these compounds, yielding a ranked list of the top 20 candidates. Functional evaluation using echocardiography, serum biochemical markers, and histopathological examination demonstrated that ANP significantly ameliorated cardiac function in mice following myocardial infarction. Integration of network pharmacology and transcriptomic enrichment identified convergent axes of IL-17 signaling and mitochondrial quality control, which were subsequently experimentally validated as mechanisms by which ANP ameliorated cardiac injury. Experimental validation confirmed that ANP downregulated protein expression of IL-17A and TNF-α, normalized PINK1 and LC3-II/LC3-I marker profiles, with concomitant p62 reduction, thereby providing comprehensive molecular evidence at both transcriptional and translational levels to support the AI-driven predictions. Conclusions: This study identified IL-17 signaling and mitochondrial quality control as pathway axes associated with ANP-mediated cardioprotection against AMI, supported by AI-driven compound screening, transcriptome-network cross-validation, and experimental confirmation. This analytical framework may be adaptable to other complex TCM formulas for mechanism exploration and clinical translation. Full article