Search Results (9,709)

With the growing interest in personalized medicine, alternative biological matrices to blood are increasingly explored as sources of diagnostic information. Saliva has emerged as a promising diagnostic matrix due to its non-invasive collection, suitability for home sampling, and minimal requirements for personnel training. Numerous studies have demonstrated the presence of metabolites in saliva that enable disease diagnosis and monitoring. However, the influence of pre-analytical and analytical factors on salivary metabolomics outcomes remains insufficiently characterized. In this study, we investigated factors potentially affecting the number and abundance of detected metabolites in untargeted salivary metabolomics using liquid chromatography coupled with mass spectrometry (LC–MS). The impact of chromatographic column type, extraction protocol, and saliva type (stimulated versus resting) was evaluated. Additionally, the effect of swab type on analyte recovery was assessed. The use of a synthetic swab for saliva collection yielded results most comparable to those obtained without swabs, for both resting and stimulated saliva samples, indicating minimal pre-analytical interference. The greatest metabolite coverage was obtained using ACN:MeOH (1:1, v/v), with a ZIC-HILIC column for polar metabolites and a C18 column for non-polar metabolite separation. These findings demonstrate that swab type, chromatographic column, extraction solvent, and saliva type critically shape metabolite coverage in untargeted salivary metabolomics. Importantly, the distinct metabolic profiles of resting and stimulated saliva suggest that these matrices may provide complementary clinical insights, underscoring the need for saliva type selection tailored to specific diagnostic and biomarker discovery objectives. Full article

Globally, the combined pollution of fine particulate matter (PM_2.5) and ground-level ozone (O₃) poses severe challenges to public health and sustainable urban development. Recent data indicate that the annual average PM_2.5 concentration in the vast majority of cities worldwide fails to meet World Health Organization safety standards, with air pollution causing millions of premature deaths annually. As a nature-based solution, the purification efficacy of vegetation remains poorly quantified due to unclear coupling mechanisms with local meteorological conditions. This study systematically reviewed and synthesized 229 empirical studies published between 2000 and 2025 from Web of Science and China National Knowledge Infrastructure (CNKI), aiming to clarify the quantitative relationships and regulatory mechanisms of plant–meteorological synergistic purification of PM_2.5–O₃. Following double-blind independent screening (κ = 0.85) and data extraction, a quantitative minimal feasible synthesis approach was adopted due to high data heterogeneity. The results indicated the following. (1) The median canopy purification efficiency of urban vegetation for PM_2.5 was 18.2% (IQR: 12.5–30.1%, n = 17), with a median dry deposition velocity (Vd–PM) of 0.05 cm s⁻¹ (0.02–30 cm s⁻¹, n = 15). The median dry deposition velocity (Vd–O₃) for O₃ was 0.55 cm s⁻¹ (0.12–1.82 cm s⁻¹, n = 8), with non-stomatal deposition contributing approximately 35%. (2) Meteorological factors exhibit nonlinear regulation: relative humidity (RH) > 70% significantly enhances PM_2.5 adsorption, wind speeds of 1.5–3.0 m s⁻¹ are optimal for PM_2.5 deposition, and temperatures > 30 °C generally inhibit plant uptake of both pollutants (n = 7). (3) Functional traits strongly correlate with purification efficacy: species with high leaf roughness (R² = 0.8), high stomatal conductance, and low BVOC emissions (e.g., Ginkgo biloba, Platycladus orientalis) exhibit optimal synergistic purification potential. Species with high BVOC emissions (Populus przewalskii, Eucalyptus robusta) can increase daily net O₃ pollution equivalents by up to 86 g and must be strictly avoided. Based on quantitative evidence, a green space planning decision matrix indexed by climate zone and pollution type was developed, specifying vegetation configuration patterns, functional group selection, and key design parameters (canopy closure, green belt width, etc.) for different scenarios. This study provides an actionable scientific basis for precision planning and climate-adaptive management of urban green infrastructure. Full article

Renewable energy sources, and wind energy in particular, constitute a central pillar of energy policy at both national and European levels. Nevertheless, the deployment of onshore wind farms is frequently associated with spatial, environmental, and social conflicts, making the evaluation of existing projects imperative. The present study aimed to assess the sustainability of existing onshore wind farms in the Region of Thessaly, with particular emphasis on their spatial planning, technical characteristics, and environmental impacts. The methodological framework consists of four distinct stages: (i) identification and spatial mapping of existing wind farms in the study area, (ii) assessment of the compliance of existing wind installations with the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD–RES), (iii) application of the Rapid Impact Assessment Matrix (RIAM) to enable a systematic and comparable evaluation of the impacts of wind installations on specific environmental and anthropogenic parameters, and (iv) estimation of project hazard and operational vulnerability through the application of Operational Risk Management (ORM). Geographic Information Systems (GISs) were employed for data processing and spatial analysis. The assessment showed that 40% of the evaluated wind farms fully comply with all eleven exclusion criteria of the SFSPSD-RES, whereas the remaining 60% show partial compliance, failing to meet between one and three criteria. RIAM results indicate that the most significant adverse impacts (−D and −C) during construction are associated with morphology/soils and the natural environment, mainly due to loss/fragmentation of vegetation and disturbance of fauna, and, in some cases, in areas of increased sensitivity. During operation, the main negative effects (−D and −C) relate to landscape and visual quality, as well as continued disturbance to the natural environment. At the same time, the operation generates important positive effects (+E) on the atmospheric environment through reduced CO₂ emissions. The ORM analysis further shows that the most important risks for most wind farms arise during construction (ORM = 2 and 3), particularly from serious worker accidents during lifting, roadworks, and foundation activities. The study demonstrates that the sustainability of existing wind installations depends on a complex set of spatial, environmental, and technical factors. The proposed framework integrates spatial compliance screening, RIAM-based environmental impact assessment, and ORM-based risk and opportunity evaluation. This connection links the importance of impacts with their operational manageability during construction and operation phases, as well as across sustainability dimensions. Consequently, the study provides a more decision-focused approach for assessing existing wind farms and supporting policy development. Full article

To investigate the characteristics and health risks of heavy metal (HM) contamination in soils of typical industrial sites during urban renewal, this study selected Pudong New District, Shanghai, as a case. Seven HMs (Cd, Pb, Cu, Zn, Ni, Hg, and As) were analyzed for their concentrations, ecological risks, spatial patterns, and potential sources. Inverse Distance Weighted (IDW) interpolation was used to assess spatial distribution, Random Forest (RF) regression to predict HM concentrations, and a two-dimensional Monte Carlo simulation to evaluate human health risks. The results showed that all HMs except As exceeded Shanghai background values in surface soils, with varying levels observed in subsoil and saturated layers. The Index of Geoaccumulation (Igeo) and Risk Index (RI) indicated low contamination and moderate ecological risk. Pearson correlation combined with Positive Matrix Factorization (PMF) identified four major sources: traffic emissions dominated by Cd and Zn, combustion-related sources dominated by Pb and Hg, industry-related inputs dominated by Cu and Ni, and a natural source dominated by As. The RF model demonstrated strong predictive accuracy for Cd, Pb, Hg, and As (R² = 0.80–0.94), and predicted values were consistent with observations. Monte Carlo results showed that non-carcinogenic risks for children and adults were within acceptable limits, while carcinogenic risks reached “notable” levels with probabilities of 62.06%, 55.65%, and 22.49% for children, adult females, and adult males, respectively. Cd and As were identified as key contributors. This work provides scientific support for soil pollution prevention and remediation during urban renewal. Full article

The dynamic field of radiopharmaceuticals is currently experiencing an explosion of growth due in part to excitement over the emerging field of theranostics (therapy and diagnostics). Radiopharmaceuticals use physiological targeting methods to deliver radionuclides with medically relevant decay properties to disease biomarkers for diagnosis and treatment, offering opportunities for early disease imaging and radiation therapy treatment in disease pathologies that are inoperable or refractory to other forms of radiotherapy. Sustaining this rapidly growing field depends heavily on the continued design and production of novel, effective radiopharmaceuticals. Effective therapeutic radiopharmaceuticals cause complex and varied cellular responses, and to choose radionuclides that maximize therapeutic response, researchers must understand radiation biology. Cellular radiation response depends heavily on factors including linear energy transfer (LET), dose, dose rate, targeted location, direct or indirect energy deposition mechanisms, the broader cellular matrix, cellular stress signaling pathways, and endogenous radiation protection mechanisms. Because of the extensive application of low-LET external beam radiation on clinical cancer treatments, biological responses to low-LET form the basis of radiation biology and are generally considered transferable to high-LET radiopharmaceuticals. However, increased focus on high-LET, radiopharmaceutical therapy-specific radiation biology is motivated by differences between low- and high-LET radiation, external beam versus radiopharmaceutical therapy-induced biological response, and the observed varied clinical responses to radiopharmaceutical therapies. This review article summarizes historical understanding of low- and high-LET radiation responses within cells, with emphasis on radiopharmaceutical-specific responses when available, and discusses current gaps in understanding in the radiation biology of radiotheranostic pharmaceuticals. Full article

A new series of eight novel etodolac-based 1,3,4-oxadiazoles was synthesized, characterized, and tested in silico in multidimensional routes, starting with etodolac, a well-known nonsteroidal anti-inflammatory medication (NSAID). In silico studies were performed prior to synthesis using the molecular docking technique in CCDC GOLD suite software (2025.3) to assess the interactions with two key targets involved in cancer pathogenesis: the crystal structure of the epidermal growth factor receptor EGFR tyrosine kinase domain (PDB ID: 4HJO) and the matrix metalloproteinase (MMP-9) complex (PDB ID: 5CUH). ADME studies were performed to assess the physicochemical properties of the synthesized molecules. Importantly, biotransformation prediction also indicated that the derivatives possess high metabolic stability, with hydroxylation of the thio-ether group as the primary predicted biotransformation route. All compounds were characterized using melting point, FT-IR, ¹H-NMR, and ¹³C-NMR spectroscopy. In vitro and/or in vivo experiments are needed to confirm this preliminary anticancer study. Full article

Open-heart surgery with cardiopulmonary bypass (CPB) is a high-risk procedure with significant morbidity and mortality. CPB, tissue injury, blood loss, endotoxemia and ischemia–reperfusion injury induce a pronounced systemic inflammatory response, leading to endothelial glycocalyx (EG) damage and vascular endothelial dysfunction. Consequently, immune cells, reactive oxygen species, and enzymes gain free access to vascular endothelial cells, resulting in their dysfunction and enhancing inflammation, vascular permeability, and microvascular impairment. EG degradation is most commonly assessed by measuring the circulating levels of its degradation products. Additionally, CPB triggers an early inflammatory response that is characterized by the secretion of interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor alpha, and IL-18, which play roles in initiating the process of EG injury. EG damage is further propagated by the sustained release of cytokines, inhibiting the regeneration of the glycocalyx layer. Heparanase and matrix metalloproteinases are enzymatic pathways involved in cytokine-mediated EG degradation after cardiac surgery, and the balance between the pro- and anti-inflammatory cytokines determines the magnitude and duration of the inflammatory response and EG impairment, which correlates with adverse clinical outcomes, including myocardial dysfunction, acute lung and kidney injury, neurological complications, and prolonged need for intensive care. Thus, identifying patients with an exaggerated cytokine response could potentially provide more personalized therapy based on the circulating biomarkers of EG shedding, and cytokine-directed preservation of EG represents a promising therapeutic strategy in vascular dysfunction prevention during and after open-heart surgery. In this review, we summarize the current knowledge on cytokine-mediated EG impairment following open-heart surgery with CPB. Full article

Background/Objectives: To evaluate the relationships between meibomian gland dysfunction (MGD), ocular surface parameters, and matrix metalloproteinase-9 (MMP-9)-mediated inflammation in glaucoma patients, we specifically assessed the impact of prostaglandin analogue use, preservative exposure, and number of medications. Methods: This retrospective cross-sectional study included patients treated with topical antiglaucoma medications for at least six months. Meibomian gland expressibility, meibum quality, and MGD grade were assessed along with tear film break-up time (TBUT), Schirmer I test, and Oxford staining score. Tear MMP-9 levels were measured using a Point-of-Care immunoassay (InflammaDry^®) and graded on a 0 to 4 scale. Results: Elevated MMP-9 grades were significantly correlated with worsening meibum expressibility, meibum quality, and MGD grade (all p < 0.001), whereas no significant associations were found with traditional parameters such as TBUT and Schirmer I test. Prostaglandin analogue use was associated with worse meibomian gland parameters and higher MMP-9 levels compared to non-use. Patients receiving preservative-containing medications exhibited poorer meibomian gland parameters and MMP-9 levels, as well as worse corneal staining scores. An increased number of medications was associated with a stepwise deterioration in meibomian gland function and elevated MMP-9 levels. Conclusions: Prostaglandin analogue use, preservative exposure, and increased number of medications are significant factors associated with the exacerbation of MGD and ocular surface inflammation. Semi-quantitative grading of tear MMP-9 revealed a stepwise association with meibomian gland dysfunction severity that was not detected by conventional dry eye metrics, indicating that MMP-9 may be considered a potential indicator of subclinical ocular surface inflammation in glaucoma patients. Full article

Alpha-Ketoglutarate (AKG), a central intermediate of the tricarboxylic acid cycle, is a crucial metabolic and signaling molecule that connects mitochondrial function with cellular homeostasis, immunological modulation, epigenetic remodeling, and lifespan. While mitochondrial AKG maintains energy metabolism, the nuclear AKG pool influences chromatin remodeling through DNA and histone modifications, which together control hypoxia responses and shape gene expression patterns. This dual role demonstrates AKG’s significance in mediating metabolic state, gene expression, and long-term cellular adaptability. AKG modulates immunological responses, reduces reactive oxygen species (ROS), promotes the polarization of anti-inflammatory macrophages, and suppresses nuclear factor kappa B (NF-κB) activation, thereby reducing chronic inflammatory processes. AKG restricts pro-inflammatory cytokine production, increases extracellular matrix synthesis, and reduces cartilage degradation in arthritic models, suggesting potential therapeutic benefits in autoimmune diseases and joint degeneration. Additionally, AKG affects lifespan in several model organisms, where supplementation enhances metabolic resilience, lowers age-related inflammation, modifies mTOR signaling, and preserves youthful epigenetic profiles. Additionally, because endogenous AKG levels decrease with age, oral supplementation of AKG, especially with calcium and arginine, has drawn attention to its potential benefits in longevity and metabolic health. Thus, AKG is versatile and has encouraging therapeutic promise for cancer, aging, and inflammatory illnesses. However, a lack of human clinical evidence prompts further research to determine ideal dosage, tissue selectivity, and long-term safety. The goal of this review is to critically examine the current mechanistic knowledge related to AKG biosynthesis and breakdown and its future implications in maintaining cellular homeostasis and controlling chronic inflammation. Full article

The quality of vector images depends on a significant set of geometric and structural factors, which makes objective assessment a challenging task. This paper proposes a comprehensive approach to identifying and prioritizing these factors. Factor selection was performed based on expert evaluation and analysis of inter-factor relationships. A reachability matrix of factors was constructed to analyze direct and indirect relationships. Models describing relationships between the factors were developed. The rank and weight of each factor were calculated using a dependency-weighting system. An information system was developed to automate the process of prioritizing factors based on the proposed methodology. The software architecture was implemented in Python 3.13.5 using the Tkinter, NumPy, and NetworkX libraries. Experimental results confirmed that the factor «coordinate accuracy» has the highest level of significance, whereas «file format» has the smallest influence on the quality of vector images. Due to the lack of dependence on specific selected factors, the developed system is universal and suitable for prioritizing factors in any application domain. Future research will focus on integrating the developed information system into a fuzzy-logic-based system for assessing the quality of vector images. Full article

Dissolved oxygen (DO) is a primary environmental regulator of shrimp physiology and behavior in intensive aquaculture systems. Whether shrimp acoustic emissions quantitatively reflect oxygen-driven behavioral modulation under operational pond conditions, however, remains uncertain due to the difficulty of isolating biologically relevant signals from complex soundscapes. In this study, passive acoustic monitoring was conducted in commercial outdoor ponds culturing Litopenaeus vannamei. A periodic-coding non-negative matrix factorization approach was applied to separate putative shrimp-associated acoustic components from broadband background noise and to obtain stable time–frequency representations of acoustic activity. Temporal variations in the extracted acoustic intensity were compared with simultaneously measured DO concentrations. Rather than relying on global correlation, phase-specific analyses revealed that the putative shrimp-associated acoustic component exhibited consistent positive associations with DO dynamics during both rising and declining phases, whereas background noise showed only weak and non-coherent relationships with DO. These results indicate that the observed acoustic–oxygen relationship is non-stationary and context-dependent. Given the observational nature of the study and potential confounding influences (e.g., aeration and other environmental factors), these findings, which are based on observations from a single pond over a limited recording period (62.85 h) under specific operational conditions, should be interpreted with caution and regarded as a proof-of-concept rather than evidence of general applicability. Nevertheless, the results are consistent with the hypothesis that population-level acoustic activity may reflect environmentally modulated behavioral responses. This highlights the potential of soundscape-based approaches as non-invasive tools for supporting aquaculture monitoring, while emphasizing the need for further validation under controlled and multi-site conditions. Full article

In water injection development of tight oil reservoirs (TORs), the complex fracture network formed by hydraulic fracturing and water injection induction is the key factor determining the development effectiveness. Accurate inversion of water injection-induced fracture parameters holds significant importance for enhancing reservoir development outcomes. This paper innovatively proposes a parameter inversion framework that integrates the Embedded Discrete Fracture Model (EDFM) with intelligent optimization algorithms. EDFM efficiently characterizes complex unstructured fracture systems while maintaining mass conservation between the matrix and fractures; intelligent optimization algorithms automatically invert parameters such as fracture half-length, orientation, and conductivity. First, a three-dimensional geological model of the TOR is constructed, utilizing EDFM to handle the impact of fractures on the seepage field. Based on considerations of fracture geometry, conductivity, and stress sensitivity, a coupled fluid dynamics model for fractures and matrix is developed. Subsequently, an objective function is built based on water injection production dynamic data, and the Projection-Iterative-Methods-based Optimizer (PIMO) algorithm is employed to achieve efficient inversion of fracture parameters. Taking a TOR in the Ordos Basin as an example for verification, through synthetic model validation, this method significantly improves the accuracy and efficiency of history matching, with inversion results reliably guiding numerical simulation predictions. The results demonstrate that this method can effectively enhance the precision of fracture parameter identification, offering clear advantages in inversion speed and accuracy over traditional trial-and-error approaches. This study provides new insights for modeling induced fractures in TORs and optimizing water injection development strategies. Full article

The purpose of this study is to determine the most suitable Destination Management Organization (DMO) model for the sustainable development of the Rize destination. Approached from the perspective of Complex Adaptive Systems (CAS), the research is of strategic importance in order to overcome systemic entropy threats, such as coordination deficiencies and unplanned growth, faced by the destination through a scientific model. Methodologically, a sequential exploratory mixed method integrating qualitative and quantitative methods was adopted. In the qualitative phase, system bottlenecks were identified through interviews with 15 strategic stakeholders; in the quantitative phase, Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) analyses were applied with 271 participants. Key findings indicate that the most critical factors disrupting the system’s homeostatic balance are weak inter-institutional coordination and inadequate infrastructure. AHP results confirm that market diversification, sustainable planning, and quality standards are priority activities. The final analysis conducted using the QFD decision matrix identified the PPCP (Public–Private–Community Partnership) model, which synchronizes public oversight with private sector innovation and integrates community-based feedback mechanisms, as the most effective structure for enabling resource integration and value co-creation among actors. The model’s adaptive architecture further accommodates emergent stakeholder dynamics, including the growing role of tourists as co-creators of destination experiences through digital platforms. The study contributes to the literature by offering a rational decision support mechanism for complex system management through AHP-QFD integration and proposes a three-phase evaluation framework to ensure results-oriented governance adaptation. Full article

Measles remains a significant public health threat despite widespread vaccination, with recent resurgences driven by vaccine hesitancy and coverage gaps. Existing mathematical models often fail to capture the substantial temporal heterogeneity in incubation periods, vaccine-induced protection, and recovery processes that characterize measles transmission. We develop and analyze an SVEIR epidemic model incorporating four independent distributed time delays with exponential survival factors, capturing the realistic variability in these epidemiological processes. The model features compartment-specific mortality rates, disease-induced mortality, and imperfect vaccination with failure probability $\theta$. Using next-generation matrix methods adapted for delay kernels, we derive the delay-dependent reproduction number ${\mathcal{R}}_0^d$ and prove, via systematic construction of Volterra-type Lyapunov functionals, that it constitutes a sharp threshold: the disease-free equilibrium is globally asymptotically stable when ${\mathcal{R}}_0^d\le 1$, while a unique endemic equilibrium emerges and is globally stable when ${\mathcal{R}}_0^d>1$. Normalized forward sensitivity analysis reveals that the transmission rate $\beta$ and recruitment rate $\Lambda$ exhibit maximal positive elasticity, while the vaccination rate p, vaccine failure probability $\theta$, and incubation delay ${\tau }_3$ possess the largest negative elasticities. Critically, ${\tau }_3$ exerts exponential influence via $e^{-n_3{\tau }_3}$, making interventions that delay infectiousness—such as post-exposure prophylaxis—unusually potent. We derive an explicit expression for the critical delay ${\tau }_3^{\mathrm{cr}}$ at which ${\mathcal{R}}_0^d=1$, demonstrating that prolonging the effective incubation period sufficiently can shift the system from endemic persistence to extinction. Numerical simulations using Dirac delta kernels confirm all theoretical predictions. These findings provide three actionable insights for public health: (1) maintaining high vaccination coverage among new birth cohorts remains paramount; (2) improving vaccine quality (reducing $\theta$) yields substantial returns; and (3) the incubation delay represents a quantifiable, measurable target for evaluating the population-level impact of time-sensitive interventions. The framework is broadly applicable to infectious diseases characterized by significant temporal heterogeneity. Full article

Cancer remains a leading cause of morbidity and mortality globally, with current therapies often limited by toxicity, drug resistance, and reduced efficacy in advanced stages. Medicinal plants represent important sources of bioactive compounds (BACs) with anticancer and chemopreventive potential; however, their successful application is strongly influenced by extraction strategies that determine phytochemical recovery and downstream biological activity. This review evaluates solvent-based extraction techniques used to extract BACs from medicinal plants with reported anticancer properties, synthesizing peer-reviewed articles from PubMed and Google Scholar published between 2020 and 2025. Solvent-based methods, including Soxhlet and maceration, were most widely applied due to their operational simplicity and the preservation of structurally diverse metabolites while percolation, decoction, infusion, and hydro-distillation were sparsely utilized. Extraction strategy and solvent polarity emerged as primary factors shaping phytochemical profiles, with phenolics, flavonoids, alkaloids, and terpenoids identified as dominant classes. Reported half maximal inhibitory concentration (IC₅₀) ranged from highly potent (0.12 µg/mL) to weak (30,000 µg/mL), reflecting variability driven by extraction parameters and plant matrix complexity. Anticancer mechanisms commonly involved apoptosis induction, cell-cycle arrest, reactive oxygen species-mediated cytotoxicity, and inhibition of proliferative signaling pathways across breast, cervical, colon, lung, liver, and prostate cancer models. Although solvent-based extraction approaches remain widely used, their context-dependent nature and lack of standardization limit reproducibility. Overall, anticancer and chemotherapeutic efficacy is primarily governed by BAC composition, while extraction methods act as upstream modulators. Future progress requires phytochemical-informed, standardized workflows supported by hybrid extraction systems, AI-assisted optimization, and advanced bioavailability and delivery systems to enable reproducible and clinically relevant translation of plant-derived chemotherapeutics. Full article