Search Results (10,594)

Proper joint function has a significant impact on people’s quality of life. Joints are the point of connection between two or more bones and consist of at least three elements: joint surfaces, the joint capsule, and the joint cavity. Joint diseases are a serious social problem. Risk factors for the development of these diseases include overweight and obesity, gender, and intestinal microbiome disorders. Another factor that is considered to influence joint diseases is trace elements. Under normal conditions, elements such as iron (Fe), copper (Cu), cobalt (Co), iodine (I), manganese (Mn), zinc (Zn), silver (Ag), cadmium (Cd), mercury (Hg), lead (Pb), nickel (Ni) selenium (Se), boron (B), and silicon (Si) are part of enzymes involved in reactions that determine the proper functioning of cells, regulate redox metabolism, and determine the maturation of cells that build joint components. However, when the normal concentration of the above-mentioned elements is disturbed and toxic elements are present, dangerous joint diseases can develop. In this article, we focus on the role of trace elements in joint function. We describe the molecular mechanisms that explain their interaction with chondrocytes, osteocytes, osteoblasts, osteoclasts, and synoviocytes, as well as their proliferation, apoptosis, and extracellular matrix synthesis. We also focus on the role of these trace elements in the pathogenesis of joint diseases: rheumatoid arthritis (RA), osteoarthritis (OA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), and systemic lupus erythematosus (SLE). We describe the roles of increased or decreased concentrations of individual elements in the pathogenesis and development of joint diseases and their impact on inflammation and disease progression, referring to molecular mechanisms. We also discuss their potential application in the treatment of joint diseases. Full article

Background/Objectives: Constitutive activation of the PI3K/AKT/mTOR signaling cascade underlies the aggressive phenotype of fibroblast-like synoviocytes (FLSs) in rheumatoid arthritis (RA); however, a quantitative synthesis of in vitro data on pathway inhibition remains lacking. This systematic review and meta-analysis aimed to (i) aggregate standardized effects of pathway inhibitors on proliferation, apoptosis, migration/invasion, IL-6/IL-8 secretion, p-AKT, and LC3; (ii) assess heterogeneity and identify key moderators of variability, including stimulus type, cell source, and inhibitor class. Methods: PubMed, Europe PMC, and the Cochrane Library were searched up to 18 May 2025 (PROSPERO CRD420251058185). Twenty of 2684 screened records met eligibility. Two reviewers independently extracted data and assessed study quality with SciRAP. Standardized mean differences (Hedges g) were pooled using a Sidik–Jonkman random-effects model with Hartung–Knapp confidence intervals. Heterogeneity (τ², I²), 95% prediction intervals, and meta-regression by cell type were calculated; robustness was tested with REML-HK, leave-one-out, and Baujat diagnostics. Results: PI3K/AKT/mTOR inhibition markedly reduced proliferation (to –5.1 SD), IL-6 (–11.1 SD), and IL-8 (–6.5 SD) while increasing apoptosis (+2.7 SD). Fourteen of seventeen outcome clusters showed large effects (|g| ≥ 0.8), with low–moderate heterogeneity (I² ≤ 35% in 11 clusters). Prediction intervals crossed zero only in small k-groups; sensitivity analyses shifted pooled estimates by ≤0.05 SD. p-AKT and p-mTOR consistently reflected functional changes and emerged as reliable pharmacodynamic markers. Conclusions: Targeted blockade of PI3K/AKT/mTOR robustly suppresses the proliferative and inflammatory phenotype of RA-FLSs, reaffirming this axis as a therapeutic target. The stability of estimates across multiple analytic scenarios enhances confidence in these findings and highlights p-AKT and p-mTOR as translational response markers. The present synthesis provides a quantitative basis for personalized dual-PI3K/mTOR strategies and supports the adoption of standardized long-term preclinical protocols. Full article

Background: Oral leukoplakia (OL) and proliferative verrucous leukoplakia (PVL) remain challenging entities due to the absence of reliable prognostic biomarkers. All-trans retinoic acid (atRA), a pivotal modulator of epithelial differentiation and mucosal integrity, has been proposed as a candidate biomarker. This study sought to quantify plasma RA levels in patients with OL and PVL compared to healthy controls, assessing their potential clinical utility. Methods: A cohort of 40 participants was recruited, comprising 10 patients with OL, 10 with PVL, and 20 healthy controls. This nested case–control study was derived from previously characterized institutional databases of oral potentially malignant disorders. Plasma samples were analyzed for atRA concentration using high-precision mass spectrometry. Statistical comparisons were conducted to evaluate differences between groups and associations with clinical outcomes. Results: Patients with homogeneous OL exhibited significantly reduced plasma atRA concentrations (mean 2.17 ± 0.39 pg/mL) relative to both PVL patients (2.64 ± 0.56 pg/mL) and healthy controls (2.66 ± 0.92 pg/mL), with p-values of 0.009 and 0.039, respectively. No statistically significant difference was found between PVL patients and controls. Furthermore, atRA levels demonstrated no correlation with clinicopathological variables or malignant progression within the PVL cohort. Conclusions: These preliminary findings indicate that diminished plasma atRA levels may serve as a prognostic marker for homogeneous oral leukoplakia, whilst its role in PVL appears limited. However, effect estimates were imprecise, and additional studies are warranted. Full article

This study was conducted in Armenia and included 32 pregnant women with TV infection and 30 healthy controls. The vaginal virome includes viruses that infect human cells and unicellular eukaryotes such as Trichomonas vaginalis (TV). Among these are Trichomonas vaginalis viruses (TVVs), double-stranded RNA viruses from the Totiviridae family, and giant DNA viruses that replicate in protozoa. This study investigated the presence of TVVs and giant protozoan viruses in pregnant women with trichomoniasis in Armenia and explored their potential associations with adverse pregnancy outcomes. Vaginal and urethral samples were collected from 32 pregnant women with confirmed TV infection and 30 healthy pregnant controls. TVVs and giant viruses (Marseilleviridae, Mimiviridae, Phycodnaviridae) were detected using qRT-PCR. Viral RNA and DNA were extracted from clinical samples and TV cultures, followed by quantification and gene expression analysis. Selected TVVs were visualized via scanning electron microscopy. All TV-positive women carried at least one TVV strain, with 94% harboring multiple TVV types and TVV4 being the most common. TV infection was significantly associated with preterm birth and premature rupture of membranes (PPROM). Giant viruses were identified in all TV-positive cases but in only 40% of controls. Marseilleviridae gene expression was observed in TV cultures, suggesting possible interactions. These findings highlight a potential role for protozoan viruses in reproductive complications and warrant further investigation. Full article

Internal fins are commonly utilized as a passive technique to enhance natural convection, but their efficiency depends on complex interplay between fin design, material properties, and convective strength. This study presents an extensive numerical analysis of buoyancy-driven flow in square cavities containing a single horizontal fin on the hot wall. Over 9000 simulations were conducted, methodically varying the Rayleigh number (Ra = 10 to 10⁵), Prandtl number (Pr = 0.1 to 10), and fin characteristics, such as length, vertical position, thickness, and the thermal conductivity ratio (up to 1000), to assess their overall impact on thermal efficiency. Thermal enhancements compared to scenarios without fins are quantified using local and average Nusselt numbers, as well as a Nusselt number ratio (NNR). The results reveal that, contrary to conventional beliefs, long fins positioned centrally can actually decrease heat transfer by up to 11.8% at high Ra and Pr due to the disruption of thermal plumes and diminished circulation. Conversely, shorter fins located near the cavity’s top and bottom wall edges can enhance the Nusselt numbers for the hot wall by up to 8.4%, thereby positively affecting the development of thermal boundary layers. A U-shaped Nusselt number distribution related to fin placement appears at Ra ≥ 10³, where edge-aligned fins consistently outperform those positioned mid-height. The benefits of high-conductivity fins become increasingly nonlinear at larger Ra, with advantages limited to designs that minimally disrupt core convective patterns. These findings challenge established notions regarding passive thermal enhancement and provide a predictive thermogeometric framework for designing enclosures. The results can be directly applied to passive cooling systems in electronics, battery packs, solar thermal collectors, and energy-efficient buildings, where optimizing heat transfer is vital without employing active control methods. Full article

Barrel tools are increasingly used in high-precision machining of free-form surfaces. However, limited studies evaluate their performance specifically on spherical geometries, where tool–surface contact characteristics differ significantly. Understanding how tool geometry and process parameters influence surface quality and cutting forces in such cases remains underexplored. This study evaluates how barrel cutter radius and varying machining parameters affect cutting forces and surface roughness when milling internal and external spherical surfaces. Machining tests were conducted on structural steel 1.1191 using two barrel cutters with different curvature radii (85 mm and 250 mm) on a 5-axis CNC machine. Feed per tooth and radial depth of cut were systematically varied. Cutting forces were measured using a dynamometer, and surface roughness was assessed using the Rz parameter, which is more sensitive to peak deviations than Ra. Novelty lies in isolating spherical surface shapes (internal vs. external) under identical path trajectories and systematically correlating tool geometry to force and surface metrics. The larger curvature tool (250 mm) consistently generated up to twice the cutting force of the smaller radius tool under equivalent conditions. External surfaces showed higher Rz values than internal ones due to less favorable contact geometry. Radial depth of the cut had a linear influence on force magnitude, while feed rate had a limited effect except at higher depths. Smaller-radius barrel tools and internal geometries are preferable for minimizing cutting forces and achieving better surface quality when machining spherical components. The aim of this paper is to determine the actual force load and surface quality when using specific cutting conditions for internal and external spherical machined surfaces. Full article

Background: Despite therapeutic advances, morbidity and mortality remain high in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), primarily due to increased cardiovascular risk. Objectives: Our study aimed to evaluate the cardiovascular risk profile and biomarker dynamics in patients with RA and PsA treated with Janus kinase inhibitors (JAKis). To our knowledge, this is the first study assessing Lp(a) levels in this context. Methods: This prospective, observational study assessed 48 adult patients. The follow-up period was 12 months. Traditional cardiovascular risk factors and biological markers, including lipid profile, lipoprotein(a) [Lp(a)], and uric acid (UA), were assessed at baseline and follow-up. Correlations between JAKi therapy, lipid profile changes, and cardiovascular risk factors were investigated. Cox regression analysis was used to identify predictors of non-major cardiovascular events. Results: A strong positive correlation was observed between baseline and 12-month Lp(a) levels (r = 0.926), despite minor statistical shifts. No major cardiovascular events occurred during follow-up; however, 47.9% of patients experienced non-major cardiovascular events (e.g., uncontrolled arterial hypertension, exertional angina, and new-onset arrhythmias). Active smoking [hazard ratio (HR) 9.853, p = 0.005], obesity (HR 3.7460, p = 0.050), and arterial hypertension (HR 1.219, p = 0.021) were independent predictors of these events. UA (HR 1.515, p = 0.040) and total cholesterol (TC) (HR 1.019, p = 0.034) were significant biochemical predictors as well. Elevated baseline Lp(a) combined with these factors was associated with an increased event rate, particularly after age 60. Conclusions: Traditional cardiovascular risk factors remain highly prevalent and predictive, underscoring the need for comprehensive cardiovascular risk management. Lp(a) remained stable and may serve as a complementary biomarker for risk stratification in JAKi-treated patients. Full article

In this work, the utility of multimodal vision–language models (VLMs) for visual product understanding in e-commerce is investigated, focusing on two complementary models: ColQwen2 (vidore/colqwen2-v1.0) and ColPali (vidore/colpali-v1.2-hf). These models are integrated into two architectures and evaluated across various product interpretation tasks, including image-grounded question answering, brand recognition and visual retrieval based on natural language prompts. ColQwen2, built on the Qwen2-VL backbone with LoRA-based adapter hot-swapping, demonstrates strong performance, allowing end-to-end image querying and text response synthesis. It excels at identifying attributes such as brand, color or usage based solely on product images and responds fluently to user questions. In contrast, ColPali, which utilizes the PaliGemma backbone, is optimized for explainability. It delivers detailed visual-token alignment maps that reveal how specific regions of an image contribute to retrieval decisions, offering transparency ideal for diagnostics or educational applications. Through comparative experiments using footwear imagery, it is demonstrated that ColQwen2 is highly effective in generating accurate responses to product-related questions, while ColPali provides fine-grained visual explanations that reinforce trust and model accountability. Full article

Soil respiration (Rt), consisting of heterotrophic (Rh) and autotrophic respiration (Ra), plays a vital role in terrestrial carbon cycling and is sensitive to soil temperature and moisture. In dryland agriculture, plastic film mulching (PM) is widely used to regulate soil hydrothermal conditions, but its effects on Rt components and their temperature sensitivity (Q₁₀) across regions remain unclear. A two-year field study was conducted at two rain-fed maize sites: Anding (warmer, semi-arid) and Yuzhong (colder, drier). PM significantly increased Rt, Rh, and Ra, especially Ra, due to enhanced root biomass and improved microclimate. Yield increased by 33.6–165%. Peak respiration occurred earlier in Anding, aligned with maize growth and soil temperature. PM reduced Q₁₀ of Rt and Ra in Anding, but only Ra in Yuzhong. Rh Q₁₀ remained stable, indicating microbial respiration was less sensitive to temperature changes. Structural equation modeling revealed that Rt and Ra were mainly driven by soil temperature and root biomass, while Rh was more influenced by microbial biomass carbon (MBC) and dissolved organic carbon (DOC). Despite increased CO₂ emissions, PM improved carbon emission efficiency (CEE), particularly in Yuzhong (+67%). The application of PM is recommended to enhance yield while optimizing carbon efficiency in dryland farming systems. Full article

Endometriosis is a benign and often underdiagnosed condition that affects women of reproductive age, typically between 18 and 45 years. It can cause infertility and pain, including radicular pain and low back pain (LBP). The aim of this case report is to emphasize the importance of making a differential diagnosis when facing LBP and radicular symptoms. We report the case of a 17-year-old female patient, R.A., presented with a significant LBP (NPRS 8/10) radiating from her lumbar spine to her right buttock and occasionally to both legs, accompanied by weakness. She revealed exacerbation of pain during menstruation, despite being under hormonal contraceptive treatment. After three physiotherapy sessions that included education, manual therapy and exercise, the patient’s pain persisted so her physiotherapist recommended an evaluation in the emergency department, where standard radiography did not reveal any significant findings. Physiotherapy continued until the fifth session, when the patient agreed to undergo evaluation at a specialized endometriosis centre. Further investigations revealed endometriotic tissue on the uterosacral ligament, leading to hormonal therapy adjustment, with which pain gradually decreased to a manageable level (NPRS 2/10). This case report highlights the importance of an early differential diagnosis in patients with LBP, as endometriosis can present not only in older women but also in younger patients, including those already on oral contraceptives. Therefore, to mitigate the risk of pattern recognition bias, clinicians must maintain a high index of suspicion for endometriosis, even in atypical or unlikely clinical presentations. Full article

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder primarily targeting joints, leading to pain, swelling, and stiffness. RA results from the body’s own immune system attacking its own tissues. Currently, there are various treatments available for RA including disease-modifying antirheumatic drugs (DMARDs) and NSAIDs. Leflunomide (LEF) is a USFDA-approved synthetic DMARD which is being widely prescribed for the management of RA; however, it faces several challenges such as prolonged drug elimination, hepatotoxicity, and others. LEF exerts its therapeutic effects by inhibiting dihydroorotate dehydrogenase (DHODH), thereby suppressing pyrimidine synthesis and modulating immune responses. Emerging nanotechnology-based therapies help in encountering the current challenges faced in LEF delivery to RA patients. This review enlists the LEF’s pharmacokinetics, mechanism of action, and clinical efficacy in RA management. A comparative analysis with methotrexate, biologics, and other targeted therapies, highlighting its role in monotherapy and combination regimens and the safety concerns, including hepatotoxicity, gastrointestinal effects, and teratogenicity, is discussed alongside recommended monitoring strategies. Additionally, emerging trends in novel formulations and drug delivery approaches are explored to enhance efficacy and minimize adverse effects. Overall, LEF remains a perfect remedy for RA patients, specifically individuals contraindicated with drugs like methotrexate. The therapeutic applicability of LEF could be enhanced by developing more customized treatments and advanced drug delivery approaches. Full article

This study presents the first investigation into the application of ultrasonic vibration-assisted electrical discharge machining (UV-EDM) using graphite electrodes for external cylindrical surface machining—an essential surface in the production of tablet punches and sheet metal-forming dies. A custom ultrasonic horn was designed and fabricated using 90CrSi material to operate effectively at a resonant frequency of 20 kHz, ensuring stable vibration transmission throughout the machining process. A Box–Behnken experimental design was employed to explore the effects of five process parameters—vibration amplitude (A), pulse-on time (Ton), pulse-off time (Toff), discharge current (Ip), and servo voltage (SV)—on two key performance indicators: material removal rate (MRR) and surface roughness (Ra). The optimization process was conducted in two stages: single-objective analysis to maximize MRR while ensuring Ra < 4 µm, followed by a hybrid multi-objective approach combining NSGA-II and the Analytic Hierarchy Process (AHP). The optimal solution achieved a high MRR of 9.28 g/h while maintaining Ra below the critical surface finish threshold, thus meeting the practical requirements for punch surface quality. The findings confirm the effectiveness of the proposed horn design and hybrid optimization strategy, offering a new direction for enhancing productivity and surface integrity in cylindrical EDM applications using graphite electrodes. Full article

Recent advancements in deep learning have significantly enhanced brain tumor segmentation from MRI data, providing valuable support for clinical diagnosis and treatment planning. However, challenges persist in effectively integrating prior medical knowledge, capturing global multimodal features, and accurately delineating tumor boundaries. To address these challenges, the Hybrid Network for Multimodal Brain Tumor Segmentation (HN-MBTS) is proposed, which incorporates prior medical knowledge to refine feature extraction and boundary precision. Key innovations include the Two-Branch, Two-Model Attention (TB-TMA) module for efficient multimodal feature fusion, the Linear Attention Mamba (LAM) module for robust multi-scale feature modeling, and the Residual Attention (RA) module for enhanced boundary refinement. Experimental results demonstrate that this method significantly outperforms existing approaches. On the BraT2020 and BraT2023 datasets, the method achieved average Dice scores of 87.66% and 88.07%, respectively. These results confirm the superior segmentation accuracy and efficiency of the approach, highlighting its potential to provide valuable assistance in clinical settings. Full article

This study investigates the propagation characteristics and field distribution of photonic crystals composed of epsilon-near-zero (ENZ) materials and metal cylinders. The research reveals that the cutoff frequency of the photonic crystal formed by combining metal cylinders with an ENZ background is independent of the volume fraction of the metal cylinders and exhibits a stop-band profile within the measured frequency range. This unique behavior is attributed to the scattering of long-wavelength light when the wavelength approaches the effective wavelength range of the ENZ material. Taking advantage of this feature, the study selectively filters specific wavelength ranges from the mid-frequency band by varying the ratio of cylinder radius to lattice constant (R/a). Decreasing the R/a ratio enables the design of waveguide devices that operate over a broader guided wavelength range within the intermediate-frequency band. The findings emphasize the importance of the interaction between light and ENZ materials in shaping the transmission characteristics of photonic crystal structures. Full article

This work focuses on the possibilities of generating synthetic data for machine learning in hazard prediction in area-based speed monitoring systems. The purpose of the research conducted was to develop a methodology for generating realistic synthetic data to support the design of a continuous vehicle speed monitoring system to minimize the risk of traffic accidents caused by speeding. The SUMO traffic simulator was used to model driver behavior in the analyzed area and within a given road network. Data from OpenStreetMap and field measurements from over a dozen speed detectors were integrated. Preliminary tests were carried out to record vehicle speeds. Based on these data, several simulation scenarios were run and compared to real-world observations using average speed, the percentage of speed limit violations, root mean square error (RMSE), and percentage compliance. A new metric, the Combined Speed Accuracy Score (CSAS), has been introduced to assess the consistency of simulation results with real-world data. For this study, a basic hazard prediction model was developed using LoRaWAN sensor network data and environmental contextual variables, including time, weather, location, and accident history. The research results in a method for evaluating and selecting the simulation scenario that best represents reality and drivers’ propensities to exceed speed limits. The results and findings demonstrate that it is possible to produce synthetic data with a level of agreement exceeding 90% with real data. Thus, it was shown that it is possible to generate synthetic data for machine learning in hazard prediction for area-based speed control systems using traffic simulators. Full article