Search Results (3,319)

Objective: The purpose of this study was to determine the biological association between host-derived HSP47 and fungal-derived HSP90 in the context of vulvovaginal candidiasis (VVC) and to examine their relationships with clinical, inflammatory, and metabolic phenotypes in infected and healthy women. Methods: This study followed a six-month case–control design (February–July 2025) and was conducted at the University of Tabuk Hospital in Tabuk, Saudi Arabia. A total of 84 women aged 18–45 years were recruited, of which 42 were VVC-infected, and 42 were healthy controls. ELISA kits were used to test vaginal swabs for HSP47 and HSP90. Clinical, hematological, cytokine, and metabolic markers were also evaluated. Mann–Whitney U, Spearman correlation, and multiple linear regression tests were performed to analyze the data. Results: The levels of HSP47 and HSP90 were significantly higher among infected patients (2.29 ng/mL and 3341 ng/mL, respectively) when compared with controls (0.58 ng/mL and 1025.7 ng/mL; p < 0.001). Women who were infected were older (p = 0.02), but there were no significant differences in terms of BMI (p = 0.29). The levels of vitamin D and adiponectin were significantly decreased (p < 0.001), while pro-inflammatory cytokines (IL-6, TNF-α, IFN-γ, TGF-β, and IL-8) and WBC counts were higher compared to the control group. The hematology results were characterized by inflammation-related anemia and disturbed protein metabolism. The ROC analysis demonstrated good diagnostic performance, with an AUC of 1.0 in the case of HSP47 and 0.905 in the case of HSP90. In the case of the infected patients, the regression models were found to be weak (HSP90 R² = 0.154; HSP47 R² = 0.273), although HSP47 retained significant connections with IL-8 (p = 0.005) and IFN-γ (p = 0.028). Conclusions: High levels of HSP47 and HSP90 are observed in VVC, reflecting an epithelial stress response and fungal persistence. These HSPs have high diagnostic accuracy, which justifies their potential as biomarkers for the timely detection of VVC; they also have further implications as early biomarkers for prognostic and treatment monitoring support, despite the poor predictive models. This study has some limitations that must be addressed; in particular, the regression analyses failed to provide statistically significant predictive models, likely due to the limited sample size. In addition, the specificity of HSP90 and HSP47 for VVC in comparison with other vaginal infections was not evaluated. Full article

This study investigates the shear behavior of glass fiber-reinforced polymer (GFRP)-reinforced concrete (RC) beams to address challenges associated with their low elastic modulus, absence of yielding, and reduced stirrup efficiency in bending regions. GFRP bars are increasingly adopted as an alternative to steel due to their superior corrosion resistance, durability, and cost-effectiveness. This study focuses on the effects of stirrup type, stirrup spacing, and shear span-to-effective depth ratio on the structural performance of GFRP RC beams. Twelve full-scale beams were tested under four-point bending, incorporating three GFRP shear reinforcement configurations: fabricated closed stirrups, integrated straight bar systems, and discrete vertical bars. Experimental observations were analyzed in terms of failure modes, load-carrying capacity, energy absorption, and deformation characteristics. Results indicate that fabricated F-type stirrups provide the highest shear performance, though their effectiveness is limited by premature rupture at bending points. Site-integrated S- and T-type configurations offer practical alternatives, maintaining structural integrity while mitigating bend-related stress concentrations, but with slightly lower energy absorption and load capacity. Increasing stirrup spacing significantly reduces shear resistance and shifts failure from flexural to shear-dominated modes. Comparisons with widely used design codes and analytical models show that CSA S806-12 provisions offer the most reliable predictions, while other guidelines tend to over- or underestimate shear capacity depending on configuration and a/d ratio. The study highlights the importance of optimizing stirrup type and spacing to enhance the shear performance of GFRP RC beams. Findings provide valuable insights for improving current design methodologies, offering guidance for engineers seeking durable, corrosion-resistant alternatives to steel reinforcement in aggressive environments. This research demonstrates that innovative site-integrated stirrup configurations can bridge practical fabrication constraints without compromising overall shear performance, promoting more efficient and resilient GFRP RC structures. Full article

Background/Objectives: Dysphagia is associated with an increased risk of in-hospital complications and adverse outcomes. Prognosis in frail hospitalized populations is influenced by systemic inflammation and reduced muscle mass. Calf circumference (CC) and an estimated appendicular skeletal muscle index (ASMI) can serve as indirect measures of muscle mass, while inflammatory status may be captured by C-reactive protein (CRP), albumin, and the CRP/albumin ratio. This study aimed to evaluate the prognostic value of indirect biomarkers of inflammation and muscle mass to predict prognosis in hospitalized patients with suspected dysphagia. Methods: A retrospective observational study was conducted at a tertiary hospital and included patients admitted with suspected dysphagia between April 2015 and October 2024. On admission, demographic variables (sex and age), anthropometry (weight, height, and CC), EAT-10 (Eating Assessment Tool) score, and serum laboratory parameters (CRP, albumin) were collected. ASMI was estimated using the formula −10.427 + (CC × 0.768) − (age × 0.029) + (sex × 7.523)/(height²). Outcomes were in-hospital mortality and length of hospital stay. Comparisons were performed between survivors and non-survivors, and multivariable models adjusted for age and sex were used to identify independent associations with mortality. Results: A total of 4241 patients were included (51.2% women), with a median age of 85 (Interquartile range [IQR] 14) years and a mean EAT-10 score of 15.98 (SD 7.79). In-hospital mortality was 18.13% (n = 769). Non-survivors were older (86 [IQR 11] vs. 84 [IQR 14] years; p < 0.001) and displayed a more inflammatory profile, with higher CRP (78.1 [IQR 114.28] vs. 44 [IQR 96] mg/L) and CRP/albumin ratio (27.27 [IQR 43.04] vs. 13.64 [IQR 31.77]; p < 0.001), and lower albumin (3 [IQR 0.8] vs. 3.3 [IQR 0.8] g/dL; p < 0.001). They also had lower muscle mass, with reduced CC and lower ASMI in both sexes. In multivariable analysis, a higher CRP/albumin ratio was independently associated with increased odds of death (OR 1.011; 95% CI 1.008–1.014; p < 0.001), whereas a higher ASMI was protective (OR 0.885; 95% CI 0.801–0.978; p = 0.017). Higher CRP/albumin ratios were also associated with longer hospital stays and lower albumin, CC, and ASMI values. Conclusions: In hospitalized patients with suspected dysphagia, systemic inflammation and lower muscle mass were associated with worse clinical outcomes. The CRP/albumin ratio independently predicted higher in-hospital mortality and prolonged hospitalization, whereas higher estimated ASMI was associated with lower mortality risk, supporting the combined prognostic value of inflammatory and muscle-mass indicators in this population. Full article

Hyperphosphatemia is a major complication in patients with kidney failure undergoing dialysis and is strongly associated with cardiovascular disease, vascular calcification, and increased mortality. Conventional management relies on dietary phosphate restriction, oral phosphate binders, and dialysis, yet persistent hyperphosphatemia affects a substantial proportion of patients. High-volume hemodiafiltration, combining diffusive and convective clearances, achieves greater phosphate removal than standard hemodialysis, with kinetic modeling predicting ~15–20% higher dialytic phosphate clearance (and ~0.5 mg/dL lower predialysis serum phosphate when nondialytic factors are constant). In this narrative review, we quantify the magnitude of improvement in dialytic clearance of phosphate with hemodiafiltration relative to hemodialysis and evaluate its effects on phosphate control measures. We also analyze phosphate balance in selected hemodiafiltration vs. hemodialysis comparisons and demonstrate why predialysis serum phosphate levels are sometimes only modestly lower or similar when hemodiafiltration is compared with hemodialysis. These findings are largely attributable to nondialytic factors—minor differences in phosphate binder equivalent dose, dietary phosphate ingestion, or residual kidney function—as predicted by phosphate kinetic modeling and supported by clinical trial data. Recognizing these confounders is essential for interpreting hemodiafiltration’s phosphate-lowering potential in real-world practice. Full article

Background/Objectives: Poly(ADP-ribose) polymerase 1 (PARP1) is an important therapeutic target in DNA repair-deficient cancers, but discovery of new inhibitors remains constrained by scaffold convergence, tolerability limits, and acquired resistance. This study aimed to develop an interpretable, reliability-stratified cheminformatics workflow for PARP1 potency prioritization and structure-based follow-up. Methods: A curated ChEMBL dataset of 3339 PARP1 inhibitors was encoded using RDKit 2D descriptors and Avalon fingerprints (1143 initial features), then reduced to 132 informative variables by Random Forest-based feature selection. Five regression models were optimized, including a stacked ensemble. Model interpretation was performed using permutation feature importance and SHAP. External near-domain corroboration was assessed using a stringent PubChem similarity expansion (Tanimoto > 0.90) around sub-10 nM seed compounds, followed by comparison with retrievable experimental PARP1 activity values. Top scaffold-diverse candidates were further evaluated by complementary docking against PARP1 (PDB: 4R6E) using AutoDock Vina and cavity-guided docking through the SwissDock platform. Results: The stacked ensemble achieved the best held-out performance (test R² = 0.723; RMSE = 0.610 pIC₅₀ units), with 83.7% of test predictions within ≤0.75 pIC₅₀ units and only 2.7% exceeding 1.5 pIC₅₀ units. PubChem similarity expansion retrieved approximately 32,450 analogs, of which 3349 were predicted to have IC₅₀ ≤ 10 nM. Among 366 compounds with retrievable experimental PARP1 activity values, predicted versus experimental pIC₅₀ showed a positive association (R² = 0.124; Pearson r = 0.479), with RMSE = 0.491 and MAE = 0.330 pIC₅₀ units. Three ligands—CID 168873053, CID 175154210, and CID 172894737—showed the strongest complementary docking support and pocket-consistent poses relative to niraparib. Conclusions: This workflow provides a transparent and practically useful framework for near-domain PARP1 inhibitor prioritization. The combined QSAR, explainability, external corroboration, and docking strategy supports shortlist generation for experimental follow-up. Full article

Background/Objectives: Peroxiredoxins (Prxs) are key antioxidant enzymes involved in cellular redox homeostasis. Prx6 is a multifunctional member of the Prx family that has been reported in other organisms to possess glutathione peroxidase and phospholipase A₂ (PLA₂)-related activities. However, the structural and immunological roles of 1-Cys Prx6 in crustaceans remain poorly understood. This study aimed to identify and characterize a Prx6 gene from Penaeus vannamei (PvPrx6) and to evaluate its potential involvement in antioxidant defense. Methods: PvPrx6 cDNA was identified and analyzed using bioinformatics and AlphaFold2 modeling. Tissue distribution and transcriptional responses to lipopolysaccharide (LPS), poly(I:C), and peptidoglycan (PGN) were examined by RT-qPCR. Recombinant PvPrx6 (rPvPrx6) was expressed in Escherichia coli, and its antioxidant activity was evaluated in vitro using a metal-catalyzed oxidation (MCO) assay. Results: PvPrx6 encodes a 219-amino-acid protein containing conserved AhpC/TSA and 1-Cys Prx domains. Sequence comparison and 3D modeling revealed conserved peroxidase (Thr⁴¹, Cys⁴⁴, Arg¹²⁷) and residues (His²³, Lys²⁹, Asp¹³⁵) corresponding to the reported PLA₂-associated motif. Structural analysis suggested that Lys²⁹ occupies a position corresponding to the Ser³² residue of human Prx6, although this did not imply functional equivalence. PvPrx6 transcripts were highly expressed in the lymphoid organ and hepatopancreas and were significantly induced at 12 h following immune challenge. rPvPrx6 exhibited dose-dependent protection against hydroxyl radical-mediated DNA damage under the experimental conditions. Conclusions: Collectively, these findings suggest that PvPrx6 retains conserved structural characteristics of Prx6 proteins and may contribute to antioxidant defense in P. vannamei. However, further studies are required to validate its enzymatic activity and in vivo functional roles. Full article

This paper develops an intelligent Enhanced Starfish Optimization (ESFO) algorithm for optimizing a secure wireless communication infrastructure. The Starfish Optimization (SFO) algorithm is inspired by starfish biology, using the integrated modeling of the arm-based exploration, preying, and regeneration behaviors of starfish. To further enhance the exploitation capability of the standard Starfish Optimization (SFO), the proposed Enhanced Starfish Optimization (ESFO) integrates a fitness-based interacting mechanism within the exploitation phase. This innovative modification improves local search accuracy, preserves population diversity, and mitigates premature convergence without introducing additional control parameters. Moreover, the proposed Enhanced Starfish Optimization (ESFO) is designed for secure wireless transmission, which is considered one of the main topics in next-generation wireless network infrastructure. The investigated network addresses the use of Simultaneously Transmitting and Reflecting RIS (STAR-RIS) in the security of the physical layer. This implemented STAR-RIS has a coupled phase shift to create reflected and transmission links, unlike traditional Reconfigurable Intelligent Surface (RIS). In this regard, we create a safe beamforming architecture that optimizes both Base Station (BS) precoding vectors and STAR-RIS transmission/reflection coefficients. In order to validate the efficiency of the proposed Enhanced Starfish Optimization (ESFO) algorithm, it is compared to several benchmark optimizers such as standard Starfish Optimization (SFO), Dhole Optimizer (DO), Neural Network Algorithm (NNA), Crocodile Ambush Optimization Algorithm (CAOA), and white shark Optimizer (WSO). These comparisons include several scenarios based on the transmitted power threshold which is varied in the range of 20 to 70 dBm with step of 5 dBm. The simulation results show that the proposed Enhanced Star Fish Optimization (ESFO) algorithm consistently outperforms existing benchmark approaches. This study supports future intelligent communication infrastructures in terms of secrecy and achievable rates over a range of transmit power levels. In particular, ESFO improves performance by up to 20–25% while converging 40–50% faster than traditional optimization algorithms, demonstrating its usefulness and resilience in STAR-RIS-assisted secure communication systems. The suggested ESFO-enabled architecture outperforms standard RIS-based systems in terms of secrecy capacity, according to numerical studies, and low-resolution STAR-RIS phase-shifters are sufficient to ensure robust secrecy performance. Full article

This study focuses on the use of Physics-Informed Neural Networks (PINNs) to solve the 1D Advection–Diffusion–Reaction (ADR) equation. The performance of the PINN model is evaluated in comparison with the classical Crank–Nicolson Finite Difference Method (CNFDM) and validated against analytical solutions to assess improvements in accuracy, robustness, and flexibility. Quantitative analysis reveals that the PINN achieved a high level of accuracy with absolute errors ranging from approximately $2.13\times {10}^{-4}$ to $1.17\times {10}^{-3}$ across the spatial domain. The study utilizes a neural network architecture with two hidden layers of 80 neurons each, optimized through a two-stage training process involving Adam and L-BFGS optimizers. This work contributes to the growing field of physics-informed machine learning by demonstrating the strengths and quantitative reliability of the PINN technique for solving complex partial differential equations in transport phenomena. Full article

Background/Objectives: Vitamin B12 deficiency is a common but often underdiagnosed complication in patients with type 2 diabetes (T2D) undergoing long-term metformin therapy. Accurate early prediction could enable targeted screening and timely intervention. This study aimed to develop and interpret a machine learning model for predicting vitamin B12 deficiency in metformin-treated patients with T2D, using eXtreme Gradient Boosting (XGBoost). Methods: A retrospective cross-sectional study was conducted at a single endocrinology centre (La Rabta University Hospital, Tunis, Tunisia). Patients with T2D treated with metformin for at least three years were included (n = 257); those with conditions independently affecting vitamin B12 metabolism were excluded. Vitamin B12 deficiency was defined as a serum B12 level below 150 pmol/L or a borderline level (150–221 pmol/L) with concurrent hyperhomocysteinemia (>15 μmol/L). XGBoost was selected after comparison with Logistic Regression (L2), Random Forest, and Support Vector Machine on the same 5-fold stratified cross-validated pipeline. Hyperparameters were optimized via Bayesian search (100 iterations × 5-fold stratified cross-validation), with the Matthews correlation coefficient (MCC) as the primary optimization metric to account for class imbalance. Model interpretability was achieved using SHapley Additive exPlanations (SHAP). Discrimination and calibration were assessed on an independent test set using bootstrap 95% confidence intervals (2000 resamples). Results: Of 257 patients, 95 (37.0%) presented with vitamin B12 deficiency. On the independent test set (n = 52), the optimized XGBoost model achieved an ROC-AUC of 0.671 [95% CI: 0.514–0.818], sensitivity of 0.737 [95% CI: 0.533–0.938], specificity of 0.545 [95% CI: 0.375–0.710], MCC of 0.273 [95% CI: 0.018–0.517], and a Brier Score of 0.259. SHAP analysis identified HbA1c, microalbuminuria, autonomic neuropathy, BMI, DN4 score, and fasting glucose as the most influential predictors. Nonlinear SHAP interaction plots revealed an increased predicted risk in patients with low HbA1c combined with a high cumulative metformin dose. Conclusions: The XGBoost–SHAP framework provided interpretable predictions of vitamin B12 deficiency in patients with T2D on metformin, identifying key clinical profiles for targeted screening. External multi-centre validation is required before clinical deployment. Full article

The Ahmed model significantly simplifies general vehicle geometry and has been employed extensively as a reference model for drag mechanism analysis. Platooning is a driving strategy that can reduce aerodynamic drag through intervehicle aerodynamic interactions. In this study, numerical analyses were performed under two-, three-, and four-vehicle platoon-driving conditions of the Ahmed model at various speeds and intervehicle distances. A RANS-based shear stress transport k–ω turbulence model was used to predict the drag coefficient ($C_d$) changes. A comparison with previously studied experimental data demonstrated high reliability, with a relative error of 0.6–5.0%. CFD analysis results showed that the drag reduction was significantly greater at shorter intervehicle distances, and that increasing the number of vehicles in a platoon reduced the fuel consumption. Furthermore, the intervehicle fluid interactions weakened and the $C_d$ values became more similar with an increasing intervehicle distance. On this basis, a $C_d$ correlation was proposed in terms of the speed and intervehicle distance. Our quantitative evaluation of the aerodynamic interactions between multiple vehicles during platoon driving and the analysis of $C_d$ correlations that are applicable to real-world conditions can improve fuel efficiency and reduce carbon emissions in real-world transportation systems. Full article

Texture feature extraction plays a crucial role in land-use and land-cover (LULC) classification for the remotely sensed images. However, when these images are quantized to a limited number of gray levels to reduce data volume or noise, conventional texture descriptors often lose discriminative power. This study investigates singular values of the gray-level co-occurrence matrix (GLCM) as novel texture features for image classification, with local binary pattern (LBP), complete LBP (CLBP) statistics, and original GLCM features proposed by Haralick et al. for comparison. Under coarse quantization, texture descriptors of LBP and its variants, which encode micro-texture, lose detail, whereas GLCM, which encodes macro-texture, retains structural co-occurrence patterns. This study thus proposes a new feature set, namely the Singular Values of the gray-level co-occurrence matrix (SVGM), for texture discrimination. Experimental analysis indicates SVGM achieves higher class separability by preserving dominant spatial structure while suppressing noise and redundancy. Quantitative evaluation using classical SVMs with multiple kernels, quantum learning models with different kernels, and neural baselines (ANN and 1D-CNN) further shows that SVGM consistently improves classification performance. Within our tested models, quantum kernel SVMs are competitive and achieve the best results on some datasets, while classical models perform best on others. Full article

This data descriptor provides a standardized and reproducible subsystem-level representation of the NREL wind turbine gearbox condition monitoring benchmarking dataset. The released records are derived from Healthy (H1–H10) and Damaged (D1–D10) measurement files and include subsystem-level standardized indices (KHI_HS, KHI_IMS, KHI_PL) together with a calibrated 0–1 Gearbox Health Index (GHI). The indices are generated using a fully specified and deterministic feature extraction and aggregation workflow based on established vibration indicators and healthy-referenced normalization. The Zenodo deposit contains machine-readable CSV tables intended to support transparent benchmarking across supervised classification and anomaly detection studies. The proposed GHI is introduced as an interpretable and reproducible reference baseline rather than an optimized diagnostic model. Technical validation demonstrates condition-level separability within the analyzed dataset while emphasizing the descriptive nature of the index. By releasing structured derived records and a documented regeneration procedure, this work enables an implementation-independent comparison of gearbox condition monitoring approaches and supports reproducible evaluation of alternative health index formulations. Full article

Hyperspectral imagery (HSI) offers rich spectral signatures and fine-grained spatial structures for remote sensing, but practical HSI classification is often constrained by scarce labels and complex geometric disturbances, including translation, rotation, scaling, and shear. Existing deep models are typically developed under Euclidean assumptions and rely on data-hungry training pipelines, which makes them brittle in the few-shot regime. To address this challenge, we propose EMNet, a Lie-group-based Equivariant Manifold Network for few-shot HSI classification that explicitly encodes geometric invariance and improves discriminative accuracy. EMNet couples an SE(2)-based Equivariance-Guided Module (EGM) to enforce equivariance to translations and rotations with an affine Lie-group-based Characteristic Filtering Convolution (CFC) that models scaling and shearing on the feature manifold while adaptively suppressing redundant responses. Extensive experiments on WHU-Hi-HongHu, Houston2013, and Indian Pines demonstrate state-of-the-art performance with competitive complexity, achieving OAs of 95.77% (50 samples/class), 97.37% (50 samples/class), and 96.09% (5% labeled samples), respectively, and yielding up to +3.34% OA, +6.01% AA, and +4.14% Kappa over the strong DGPF-RENet baseline. Under a stricter 25-samples-per-class protocol with 10 repeated random hold-out splits, EMNet consistently improves the mean accuracy while exhibiting lower variance, indicating better stability to sampling uncertainty. On the city-scale Xiongan New Area dataset with extreme long-tail imbalance (1580 × 3750 pixels, 256 bands, and 5.925 M labeled pixels), EMNet further boosts OA from 85.89% to 93.77% under the 1% labeled-sample protocol, highlighting robust generalization for large-area mapping. Beyond point estimates, we report mean ± SD/SE across repeated splits and provide rigorous statistical validation by computing Yule’s Q statistic for class-wise behavior similarity, performing the Friedman test with Nemenyi post hoc comparisons for multi-method ranking significance, and presenting 95% confidence intervals together with Cohen’s d effect sizes to quantify practical improvement. Full article

Lower-limb rehabilitation exoskeletons must balance biomechanical compatibility, structural safety, and low mass to enable practical, repeatable gait assistance. This paper proposes a planar pantograph-derived exoskeleton leg driven by a Chebyshev Lambda linkage and develops an integrated workflow from mechanism synthesis to manufacturable optimization and experimental verification. A mannequin-coupled multibody model was built in MSC ADAMS to evaluate joint kinematics, end-point (foot) trajectories, and joint reaction forces under multiple scenarios (fixed-frame, ramp, stair ascent, and inclined-plane walking). The extracted joint loads were transferred to a parametric finite element model in ANSYS Workbench 2019, where response surface surrogates and a multi-objective genetic algorithm (MOGA) were used to minimize mass under stiffness and strength constraints. For the optimized load-bearing link, the selected minimum-mass design reached a component mass of 0.542 kg while respecting the imposed structural limits, i.e., a maximum total deformation below 0.2 mm and a maximum equivalent (von Mises) stress below 50 MPa (e.g., ~0.188 mm deformation and ~39 MPa stress in the optimal candidate). A rapid prototype was manufactured by 3D printing and experimentally evaluated using CONTEMPLAS high-speed video tracking, providing measured X_M(t) and Y_M(t) trajectories and joint-angle histories for quantitative comparison with simulations via RMSE metrics. Full article

Background/Objectives: Psoriatic disease is a systemic inflammatory condition associated with increased cardiometabolic risk, but the impact of contemporary systemic therapies and narrowband ultraviolet B (NB-UVB) phototherapy on vascular and systemic inflammatory markers remains incompletely characterized. We aimed to systematically synthesize prospective evidence on treatment-associated changes in vascular inflammation and systemic inflammatory biomarkers in adults with moderate-to-severe psoriatic disease. Specifically, we evaluated changes assessed by 18F-FDG PET/CT imaging and circulating biomarkers following biologic therapies or NB-UVB phototherapy. Methods: We systematically searched MEDLINE, Embase, Web of Science, Scopus, and CENTRAL from inception to 31 January 2026 for prospective interventional and observational studies in adults with psoriasis or psoriatic arthritis treated with biologic agents targeting TNF-α, IL-12/23, IL-17, or IL-23, or with NB-UVB phototherapy. Eligible studies were required to report serial assessments of vascular inflammation by 18F-FDG PET/CT (typically aortic target-to-background ratio) and/or systemic inflammatory markers (high-sensitivity C-reactive protein, interleukin-6, TNF-α, GlycA, or hematologic indices such as the neutrophil-to-lymphocyte ratio) over at least 8 weeks of follow-up. We imposed no language restrictions and included only full-text, peer-reviewed prospective studies. Risk of bias was evaluated using RoB 2 for randomized trials and ROBINS-I for nonrandomized studies. Random-effects meta-analyses were prespecified for outcomes reported by at least two clinically comparable studies; however, because of substantial heterogeneity in reporting and methodology, effect estimates were summarized using a structured narrative synthesis. Results: Thirteen prospective studies (n ≈ 900 adults, published 2015–2025) met inclusion criteria, including four studies with serial 18F-FDG PET/CT imaging and one additional PET/CT study providing baseline observational data on vascular inflammation, as well as eight biomarker-focused prospective cohorts. Across randomized mechanistic trials and observational studies, biologic therapies reduced aortic target-to-background ratio by approximately 6–12% over 12–24 weeks (e.g., mean change from 2.42 to 2.18 with TNF-α inhibition and from 2.51 to 2.20 with IL-17 blockade), and no study reported worsening of PET-derived vascular indices under effective systemic treatment. Biologic and other systemic therapies produced concordant reductions in hs-CRP (typically by 30–50%), IL-6, TNF-α, GlycA, and blood-count-derived indices including neutrophil-to-lymphocyte ratio, with biomarker improvements frequently paralleling reductions in cutaneous disease activity and cardiometabolic risk markers. Two NB-UVB cohorts demonstrated significant hs-CRP reductions of roughly 20–30% and modulation of vitamin D-related inflammatory proteins, suggesting systemic anti-inflammatory effects, although these changes appeared less pronounced than with biologic therapy and were not accompanied by vascular imaging. Conclusions: Contemporary systemic psoriasis therapies, particularly biologic agents targeting the IL-23/Th17 axis and TNF-α, are associated with consistent reductions in aortic vascular inflammation and broad improvements in systemic inflammatory biomarkers, whereas NB-UVB phototherapy confers more modest but measurable systemic anti-inflammatory effects, although the current evidence does not allow differentiation between individual biologic classes in terms of magnitude of effect. Although reductions in vascular and systemic inflammatory markers were observed across therapies targeting TNF-α, IL-12/23, IL-17, and IL-23, the small number of mechanistic imaging studies and absence of head-to-head comparisons do not allow robust differentiation between biologic classes or support a uniform class effect. The convergence of imaging and biomarker data reinforces psoriasis as a clinically relevant model of inflammation-driven atherosclerosis and supports the concept that effective control of psoriatic inflammation may contribute to cardiovascular risk modification, highlighting the need for integrated cardiovascular risk assessment in routine care. However, the imaging evidence base remains limited to four small mechanistic PET/CT studies with relatively short follow-up, which constrains the strength and generalizability of conclusions regarding vascular inflammation. Larger, adequately powered, event-driven prospective trials with standardized imaging and biomarker endpoints are needed to determine whether these vascular and systemic anti-inflammatory effects translate into reduced cardiovascular events in psoriatic disease; because of methodological and reporting heterogeneity across the 13 included studies, these conclusions are based on a structured narrative synthesis rather than a formal quantitative meta-analysis. PROSPERO registration number: CRD420261296646. Full article