Search Results (3,612)

Cutaneous T-cell lymphoma (CTCL), primarily mycosis fungoides (MF) and Sézary syndrome (SS), has long been characterized as a neoplasm of mature memory T cells, based on monoclonal T-cell receptor (TCR) rearrangements and tissue-resident memory (TRM)/central memory (TCM) T-cell phenotypes. This review synthesizes converging population-genetic, multi-omic, and single-cell evidence to argue that this characterization is incomplete and that a progenitor-based model better accounts for the full spectrum of disease biology. We present evidence that initiating mutations arise in hematopoietic stem or early lymphoid progenitor survive thymic selection, and diversify after TCR assembly, resulting in branched evolution across both blood and skin. In SS, paired analyses reveal > 200 shared variants between CD34⁺ progenitors and Sézary cells, as well as signal-joint T-cell receptor excision circle (sjTREC) positivity, providing direct progenitor-level evidence. In MF, convergent signals, multiple malignant clonotypes per lesion, greater blood–skin than skin–skin clonotype overlap, and compartment-specific CNV subclones, implicate hematogenous seeding and reseeding. Population-scale lymphoid clonal hematopoiesis and lymphoid-pattern mosaic chromosomal alterations define a compatible antecedent state. Spatial single-cell atlases and trajectory analyses map site-conditioned programs in skin, including Th2-skewed cytokines, microbial responses, and UV signatures, that select and expand subclones and explain inter- and intra-patient heterogeneity. This framework reconciles mature immunophenotypes with upstream initiation and clarifies why compartment-focused therapies often reshape rather than eradicate disease. It yields testable predictions and actionable implications: trials should pair multicompartment cytoreduction with strategies that attenuate progenitor-derived reservoirs, restore immune balance, and repair skin barrier dysfunction. A progenitor-initiated, niche-adapted model provides a coherent scaffold for more durable control in CTCL. Full article

In this paper, we investigate the application of the relative entropy framework for safety assessments of steel elements with structural defects at the micro- and macro-scales. Mathematical theories developed by Bhattacharyya and by Kullback and Leibler (K-L) have been used for this purpose. This approach uses both expectations and variations, similar to the First-Order Reliability Method (FORM), but is extended to include 3rd- and 4th-order central probabilistic moments. It is necessary to use a hybrid computational technique that combines the Finite Element Method (FEM) software ABAQUS CAE 2017 with the implemented Gurson–Tvergaard–Needleman (GTN) damage model and the computer algebra system MAPLE. The iterative generalized stochastic perturbation technique has been used to determine the probabilistic moments of structural response, to utilize the Weighted Least Squares Method to approximate the structural response function, and to determine uncertainty in the stress, strain, and displacement state functions. This approach is based on relative entropy because of its universality. There is no need to assume a type of distribution of the state functions, in contrast to FORM, where a Gaussian distribution is required. This paper verifies whether relative entropy can serve as an alternative to FORM for determining reliability. The yield surface of the porous material with a random values of the void volume fraction f are also presented. Full article

Ottoman mosques represent a unique synthesis of architectural elegance and structural ingenuity, where massive masonry domes are balanced on slender supports through carefully engineered load transfer systems. These monumental buildings, constructed centuries ago without modern analytical tools, continue to challenge contemporary engineers seeking to understand their behavior under seismic loading. This study presents an integrated evaluation of the structural and geotechnical performance of the 16th-century Sultan Selim Mosque in Konya, Türkiye, one of the most prominent examples of Classical Ottoman architecture. The research combines ambient vibration testing (AVT), geotechnical investigations, and finite element modeling (FEM) to assess the existing structural condition and soil–structure interaction (SSI) effects. Dynamic identification through AVT provided the modal characteristics of the mosque, which were used to calibrate a detailed three-dimensional FEM developed in ANSYS Workbench using a macro-modeling approach. The numerical analyses showed that observed deformation patterns and stress concentrations are consistent with field damage observations, indicating that differential settlements and heterogeneous subsoil stiffness are the primary factors influencing the structural response. The findings enhance understanding of the seismic behavior of monumental masonry domed structures and offer a solid basis for the evaluation and conservation of Ottoman-era architectural heritage. Full article

Background: Epimedium is a natural herb with immunomodulatory potential, but its vaccine adjuvant properties remain poorly understood. Objective: The aim of this study was to elucidate the adjuvant effects of Epimedium and the underlying molecular mechanisms. Methods: Network pharmacology was used to identify bioactive compounds and targets of Epimedium from the TCMSP database, and immunomodulation-related targets from GeneCards and OMIM. PPI networks, KEGG/GO enrichment, molecular docking, and molecular dynamics (MD) simulations were performed. In vivo, female BALB/c mice were immunized with the Staphylococcus aureus (S. aureus) vaccine subunit HI antigen, either alone or with low- or high-dose icariin (ICA). Serum antibody responses (IgG, IgG1, IgG2a, IgG2b) were measured by ELISA. Survival against lethal S. aureus USA300 challenge was monitored. Results: Network pharmacology predicted 488 targets and 13 pathways. Core targets included IL6, TP53, EGFR, CTNNB1, HIF1A, HSP90AA1, JUN, MTOR, SRC, and AKT1. KEGG/GO analysis indicated involvement of T cell receptor and NOD-like receptor signaling pathways in inflammatory responses. Molecular docking and MD simulations confirmed stable ligand-target binding. Experimental validation showed that ICA significantly enhanced HI-specific antibody responses and induced a Th2-biased humoral immune response (IgG1/IgG2a ratio > 1), which is particularly relevant for vaccines targeting extracellular pathogens such as S. aureus. ICA also improved survival after lethal bacterial challenge. Conclusions: This study identifies potential bioactive compounds, core targets, and key pathways of Epimedium as a vaccine adjuvant. Experimentally, ICA, as a representative component, enhanced HI-specific antibody responses and conferred protection against lethal S. aureus challenge. Together, these findings offer a computational–experimental basis that may guide further mechanistic investigation. Full article

Background: Inflammatory bowel disease (IBD) is frequently complicated by secondary bone loss driven by chronic inflammation and gut–bone axis dysregulation. Although dried ginger has pharmacological activities relevant to intestinal inflammation, the effects of dried ginger milk extract (DGME), a lipophilic constituent-enriched preparation, on IBD-associated bone loss (IBD-BL) remain unknown. This study evaluated the preventive and therapeutic effects of DGME on IBD-BL and explored the underlying mechanisms. Methods: Mice with DSS-induced IBD-BL were treated with DGME (250, 125, or 62.5 mg/kg) or sulfasalazine. Colitis severity, bone microarchitecture, osteoclast activity and Th17 cells were assessed by histology, micro-computed tomography, histomorphometry and flow cytometric analysis. UHPLC-Q-TOF MS, network pharmacology, 16S rRNA sequencing, fecal metabolomics, and in vitro assays were used for mechanistic investigation. Results: DGME ameliorated colitis, improved trabecular bone microarchitecture, and reduced osteoclast-related bone destruction. These effects were associated with selective suppression of pathogenic bone marrow TNF-α⁺ Th17 cells and downregulation of Il17a, Rorc, Tnfα, Ccr2, Ccr6, Cxcr4, Csf1, and Tnfsf11. Compared with aqueous extract, DGME was enriched in 19 lipophilic constituents. Multi-omics analyses showed that DGME remodeled gut microbiota and metabolite profiles, characterized by enrichment of Lactobacillus, Anaerotruncus, vanillin, and spermidine. Both vanillin and spermidine suppressed Th17 effector genes and inhibited MEK/ERK signaling in vitro. Conclusions: DGME alleviated IBD-BL by suppressing pathogenic TNF-α⁺ Th17 responses and remodeling the gut microbiota–metabolite axis. This study not only extends the therapeutic application of dried ginger from intestinal inflammation to IBD-BL, but also identifies vanillin and spermidine as candidate functional mediators linked to MEK/ERK inhibition. Full article

Pertussis is a highly contagious respiratory infection caused by Bordetella pertussis and remains a persistent global health challenge despite widespread vaccination. This review aims to analyze the immune pathogenesis of B. pertussis infection and to identify key immunological limitations of current acellular pertussis vaccines that contribute to ongoing transmission. A narrative review of the literature was conducted, focusing on mechanisms of host–pathogen interaction, immune evasion, and vaccine-induced immunity. Evidence indicates that although acellular vaccines effectively reduce disease severity, they fail to prevent nasopharyngeal colonization and transmission, largely due to insufficient induction of mucosal immunity, T helper 1 (Th1) and T helper 17 (Th17) responses, and airway tissue-resident memory T cells. In contrast, natural infection induces broader immune responses, including secretory IgA production and robust cellular immunity, which are associated with improved bacterial clearance. Emerging next-generation vaccine strategies, including mucosal, outer membrane vesicle-based, and live-attenuated platforms, demonstrate enhanced ability to reduce bacterial colonization in preclinical and clinical models. In conclusion, effective control of pertussis transmission will require vaccine approaches that replicate infection-induced immunity at the respiratory mucosa, emphasizing the need for redesigned immunization strategies. Full article

Objective: To evaluate the relationship between legume intake and incident hyperuricemia among Chinese adults using large-scale prospective cohort data. Methods: Baseline and follow-up information from the Shanghai Suburban Adult Cohort and Biobank (SSACB) were used to assess diet and hyperuricemia incidence [serum uric acid (SUA) ≥ 420 μmol/L in males and ≥ 360 μmol/L in females]. A Food Frequency Questionnaire (FFQ) covering 29 food categories quantified food consumption during the previous 12 months. Legume intake was calculated by multiplying the reported consumption of each item by (1 − water content), and participants were classified into tertiles with the lowest third (Q1) as the reference. Cox proportional-hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs), and restricted cubic splines (RCSs) with three knots (10th, 50th, and 90th percentiles) visualized the dose–response relation. Results: Among 43,371 participants, 1456 new cases of hyperuricemia were documented over 225,002.40 person-years (incidence density 6.47/1000 person-years; 95% CI 6.14–6.80). Incidence density decreased with higher legume intake: each 1 g/day increment was associated with a 2% lower risk (HR 0.98; 95% CI 0.97–0.99; p < 0.05). Compared with Q1, the highest tertile (Q3) showed a 26% risk reduction in the fully adjusted model (HR 0.74; 95% CI 0.64–0.86; p < 0.05). RCS revealed a significant nonlinear relationship (p-overall < 0.001, p-nonlinear = 0.0013), with the significant benefit in risk observed at 6–28 g/day. Conclusions: Legume intake is nonlinearly and inversely associated with hyperuricemia risk among Shanghai suburban adults. Given that the current low median intake, comprehensive strategies are needed to rationally adjust the dietary structure, improve legume intake, and provide sustainable development strategies for effective prevention and control of hyperuricemia. Full article

Posidonia oceanica meadows are among the most valuable coastal ecosystems in the Mediterranean Sea, providing key ecological functions and socio-economic benefits. Despite conservation efforts, these meadows declined markedly throughout the late 20th century due to cumulative human pressures, although their condition has stabilised more recently under protection, and natural recolonization has even begun in some areas. In this context, active restoration through transplantation has expanded considerably, particularly in response to recent policy initiatives, and is now contributing to the recovery of these ecosystems. However, long-term monitoring to assess active restoration success remains scarce. This study revisits one of the earliest P. oceanica transplantation interventions, initiated in 1996 in front of the tourist harbour of Rapallo (NW Mediterranean), and evaluates its status after nearly 30 years. Surveys conducted in 2019 and 2024 confirmed the persistence of the transplanted meadow. The restored area increased from approximately 20 m² at establishment to 26.9 m² in 2024, and shoot density reached values comparable to well-developed natural meadows in the region. The observed long-term structural stability highlights the need to assess restoration outcomes over decadal timescales. This case study also suggests that fine-scale site conditions, including hydrodynamic shelter and adequate light availability, can strongly influence long-term restoration success. Full article

In response to the subjective issues, inconsistent quality standards, high labor intensity and low sorting efficiency during the drying process of green pepper, an improved YOLOv11 algorithm was proposed for quality detection. A multi-scale edge enhancement module (MEEM) is introduced into the backbone network, replacing the original basic C3K2 module with C3K2-MEEM to enhance the extraction of detailed features in images of dried green Sichuan pepper and prevent missed detections, false detections, and boundary confusion. The LRSA module is integrated into the 10th layer of the backbone network to improve the clarity of the tumor-like texture of the Sichuan pepper and reduce the influence of impurities, automatically allocating attention based on feature similarity to preserve local information. In the neck layer, the DPCF module is added to the FPN+PAN feature fusion stage to achieve multi-scale feature collaboration, meeting the detection requirements of dried green Sichuan pepper. The results show that the accuracy recall rate, mean average precision, and model size of the improved MLD-YOLOv11 algorithm are 92.1%, 96.6%, 95.6%, and 11.06 MB, respectively. Compared with the training results of the original YOLOv11 model, the average accuracy of the improved model has increased by 2.2 percentage points, and GFLOPs have definitely decreased by 2 G, with parameter reduction of approximately 3.10%. Compared with other mainstream models, the MLD-YOLOv11 model has significant advantages in terms of mean average precision, model size, and floating point operations per second, making it more suitable for industrial applications and providing an efficient, accurate, and lightweight solution for the quality detection of dried green Sichuan pepper. Full article

The emergence of multidrug-resistant Pseudomonas strains poses a serious threat to public health. Essential oil components, such as thymol (TH), exhibit potent antibacterial activity. However, the effects of continuous sublethal TH exposure and resulting changes to antibiotic susceptibility remain poorly understood. Here, we investigated a multi-resistant Pseudomonas psychrophila strain after TH adaptation using an integrated transcriptomic and metabolomic approach. Treatment with TH caused a significant decrease in MIC values for aminoglycosides (streptomycin, gentamicin, kanamycin) and tetracycline and increased susceptibility to five other antibiotics. Multi-omics analyses revealed coordinated changes in fatty acid metabolism (FabI downregulation and accumulation of unsaturated fatty acids), lipid A biosynthesis (LpxC downregulation), peptidoglycan synthesis (Mur genes downregulated, accompanied by increased spermine levels), and stress response pathways (such as GABA, GadA, maltose, and MalK). These results suggest that metabolic alterations and envelope remodeling potentially affect cell wall integrity and growth, which could, in turn, contribute to increased antibiotic susceptibility and re-sensitization. Overall, our findings highlight the potential of TH-mediated sensitization as a complementary strategy to restore antibiotic efficacy. Full article

Thyroid cancer is the most common malignancy of the endocrine system and represents a biologically heterogeneous disease driven by the interplay between endocrine regulation, oncogenic signaling pathways, and tumor microenvironment dynamics. Although most follicular cell-derived thyroid cancers follow an indolent clinical course, a subset progresses toward aggressive, therapy-refractory phenotypes, underscoring the need for refined molecular understanding and improved biomarkers. This review comprehensively examines the molecular determinants of thyroid cancer progression, with particular emphasis on Thyroid Hormone (TH) signaling, the Mitogen-Activated Protein Kinase (MAPK) and Phosphoinositide 3-Kinase (PI3K)/AKT pathways, and the emerging role of microRNAs (miRNAs). We discuss how oncogenic alterations, most notably the ^V600EBRAF mutation, act as central drivers of tumor initiation and aggressiveness by sustaining MAPK/ERK signaling, promoting dedifferentiation, metabolic reprogramming, immune evasion, and resistance to targeted therapies. The cooperative role of PI3K/AKT signaling in reinforcing survival, invasion, and treatment resistance is highlighted, emphasizing the network-level integration of oncogenic pathways rather than linear dependency on single drivers. In parallel, thyroid hormones exert context-dependent effects on tumor biology through both genomic actions mediated by nuclear thyroid hormone receptors and non-genomic mechanisms initiated at the integrin αvβ3 receptor, linking endocrine status to cancer progression and therapeutic response. Finally, we review the expanding evidence supporting miRNAs as critical regulators of thyroid carcinogenesis and as promising diagnostic, prognostic, and predictive biomarkers. The clinical validation of miRNA-based panels and circulating miRNAs offers new opportunities to improve preoperative risk stratification, reduce overtreatment, and guide personalized therapeutic strategies. Collectively, these insights support a multidimensional framework for understanding thyroid cancer progression and highlight future directions for precision oncology. Full article

Extreme hydrological events fundamentally alter sediment transport dynamics across grain, reach, and watershed scales, rendering classical equilibrium-based transport formulations inadequate. This review synthesizes recent advances in multiscale sediment transport modeling under highly unsteady and high-magnitude forcing conditions. At the grain scale, particle-resolved simulations demonstrate that sediment entrainment is governed by turbulence intermittency and transient force exceedance rather than mean bed shear stress thresholds, particularly when the hydrograph rise timescale (T_h) becomes comparable to particle response times (T_p). At the reach scale, non-equilibrium transport emerges when the unsteadiness ratio T_h/T_a∼O(1), where T_a is the sediment adaptation timescale representing the time required for sediment flux to adjust toward transport capacity. Under these conditions, pronounced hysteresis between discharge and sediment flux is observed, requiring relaxation-based transport formulations instead of instantaneous equilibrium laws. At the watershed scale, the sediment delivery ratio (SDR), defined as the ratio of sediment yield at the basin outlet to total hillslope erosion, becomes highly time-dependent. Extreme precipitation events can activate hillslope-channel connectivity, increasing SDR by orders of magnitude relative to baseline conditions. A unified dimensionless scaling framework is presented based on mobility intensity (θ/θ_c, where θ is the Shields parameter and θ_c is its critical value for incipient motion), unsteadiness ratio (T_h/T_a), and morphodynamic coupling (T_f/T_m, where T_f is the hydraulic advection timescale and T_m is the morphodynamic adjustment timescale). This framework enables classification of sediment transport regimes ranging from quasi-equilibrium to cascade-dominated states. The synthesis demonstrates that predictive uncertainty increases nonlinearly across scales due to timescale compression, threshold activation, and feedback between flow hydraulics and evolving morphology. Recent developments in hybrid physics-AI approaches show promise in improving predictive capability by enabling dynamic transport closures, surrogate modeling of computationally expensive microscale processes, and data assimilation for real-time forecasting. However, these approaches remain limited by extrapolation uncertainty and the need to enforce physical constraints. Overall, this review concludes that regime-aware multiscale coupling, combined with uncertainty quantification and adaptive modeling strategies, is essential for robust sediment hazard prediction and climate-resilient infrastructure design under intensifying hydrological extremes. Full article

Background/Objectives: Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline and chronic neuroinflammation. Increasing evidence suggests that the imbalance between pro-inflammatory Th17 cells and anti-inflammatory regulatory T (Treg) cells plays a critical role in AD pathogenesis. However, a comprehensive synthesis of how natural compounds modulate Th17/Treg balance in AD remains lacking. This review aims to summarize current preclinical evidence on Th17/Treg dysregulation and evaluate the immunomodulatory potential of natural compounds in AD. Methods: This review focuses on preclinical evidence derived from experimental AD models and related inflammatory models to evaluate how natural compounds modulate Th17/Treg balance, neuroinflammation, and cognitive function, with an emphasis on underlying molecular and immunometabolic mechanisms. Results: Th17/Treg imbalance contributes significantly to AD-associated neuroinflammation and disease progression. Representative natural compounds, including paeoniflorin, quercetin, and ganoderic acid A, have demonstrated the ability to rebalance Th17/Treg responses, suppress neuroinflammation, and improve neuronal survival in experimental models. These compounds are highlighted due to their relatively stronger evidence in AD-related models and more clearly defined immunomodulatory mechanisms. These effects are partially mediated through modulation of key signaling pathways and immunometabolic reprogramming. Conclusions: Targeting Th17/Treg balance with natural compounds represents a promising multi-target immunomodulatory strategy for AD. However, most current evidence is derived from preclinical or non-AD models, and clinical validation remains limited. Future studies should prioritize AD-specific models and translational research to evaluate therapeutic potential in humans. Full article

Background: Respiratory syncytial virus (RSV) is a leading cause of severe lower respiratory tract infections in infants, seniors, and immunocompromised individuals, contributing substantially to the global disease burden. Given the limited preventive options available, developing an effective and safe vaccine remains a public health priority. Methods: An mRNA vaccine encoding the RSV PreF protein was designed and prepared. Antigen properties were evaluated in silico, and the coding sequence was optimized using NLP algorithms. The stability and translational efficiency of the mRNA constructs were verified through in vitro and in vivo assays, followed by immunogenicity evaluation of the formulated mRNA vaccines in a BALB/c mouse model. Results: The optimized mRNA showed predicted improvements in structural stability and a lower free energy state, which were associated with increased translational efficacy in vitro. Correct antigen conformation and retention of key epitopes were confirmed by intracellular staining followed by flow cytometry. A balanced Th1-biased immune response was induced in mice, characterized by high levels of neutralizing antibodies and antigen-specific T-cell immunity, along with enhanced memory T-cell proliferation and differentiation, indicating long-term immunological memory. Conclusions: A novel RSV PreF mRNA vaccine was successfully developed via optimization of protein structure and mRNA sequence. Superior immunogenicity was demonstrated in the BALB/c mouse model, together with promising potential in terms of vaccine safety and immunological persistence. These findings represent a promising step forward in the pursuit of an effective RSV vaccine and suggest the potential of the developed mRNA vaccine to induce substantial immune responses that may correlate with protection in future challenge studies. Full article

IoT-based smart greenhouse sensing, real-time signal conditioning and abnormality detection are still predominantly executed at gateway or cloud levels, limiting responsiveness and increasing vulnerability to noise-induced false alarms. This study proposes and experimentally validates a mobile-edge signal processing and abnormality detection framework executed entirely within an Android-based smartphone application, eliminating dependence on continuous cloud-side analytics. Environmental data from 27 wireless sensor nodes measuring temperature, relative humidity, CO₂ concentration, and light intensity were processed in real time using a sliding-window moving-average filter (N = 6) implemented with O(1) computational complexity. Abnormal conditions were determined via thresholding combined with temporal majority voting validation to suppress transient violations. Performance was also evaluated with direct threshold-based detection on raw signals to assess the effect of mobile-side filtering and temporal majority validation on abnormal sample counts, event fragmentation, and detection consistency. Mobile application side signal conditioning reduced short-term variance by 35–55% while maintaining an effective delay below two sampling intervals. Event-level analysis demonstrated substantial consolidation of noise-induced detections, reducing abnormal event frequency by up to 69% and increasing median event duration from 5 to 38 min for temperature, with negligible detection bias (±1.1%). End-to-end processing latency remained bounded under sustained multi-node streaming, with median delays of 1.0–1.6 s and 95th-percentile delays below 4.0 s. These results demonstrate that lightweight mobile-edge signal conditioning can significantly enhance detection robust-ness, reduce false alarms, and achieve low-latency environmental monitoring in green-houses. The proposed framework provides scalable and computationally efficient architecture for real-time abnormality detection in precision agriculture systems. Full article