Search Results (12,618)

Residual inflammatory risk after acute coronary syndromes (ACSs) remains a critical contributor to atherosclerosis progression and plaque destabilization. Inflammatory biomarkers such as interleukin-1 receptor antagonist (IL-1ra), resistin, and C-reactive protein (CRP) may provide additional insights into coronary lesion complexity and vulnerability. The main aim of the study was to evaluate the association of interleukin-1 receptor antagonist (IL-1ra), resistin, and C-reactive protein (CRP) with coronary disease extent; functional significance of non-culprit lesions, assessed by fractional flow reserve (FFR); and plaque vulnerability, assessed by optical coherence tomography (OCT) in patients with acute coronary syndrome (ACS). This prospective study enrolled 93 ACS patients undergoing invasive coronary assessment for an ACS. Inflammatory biomarkers were measured at admission and 6 months post-event. Patients were stratified post hoc into tertiles by biomarker distribution. SYNTAX score, FFR, and OCT-defined thin-cap fibroatheroma (TCFA) were used to characterize lesion burden and morphology. Multivariate logistic regression was performed adjusting for conventional cardiovascular risk factors and ACS type. Higher tertiles of IL-1ra, resistin, and CRP were significantly associated with increased SYNTAX score (p < 0.05), FFR < 0.80 (68% in the highest tertile), and presence of TCFA (62% vs. 20%, p < 0.01). All biomarkers correlated with coronary disease severity. In multivariate logistic models, IL-1ra (OR 1.23 per 100 pg/mL, p = 0.03), resistin (OR 2.35 per 1 ng/mL, p = 0.001), and CRP (OR 1.11 per 0.001 ng/mL, p = 0.006) independently predicted high-risk coronary profiles. IL-1ra, resistin, and CRP are independently associated with lesion complexity, functional significance, and vulnerability in ACS. Inflammatory biomarker profiling may provide complementary anatomical and physiological assessment in future ACS risk stratification strategies. Full article

Construction sites present intrinsically hazardous conditions characterized by dynamic and complex operational environments which persistently contribute to elevated rates of occupational injuries. While conventional safety management emphasizes controls during the execution phase, addressing safety considerations during the earliest phases of a project is more effective. In this work, a Nonlinear Multifactor Safety Index (NMF-SI) is developed to quantify activity-level occupational risk for use in project planning. The index synthesizes multiple risk factors, including accident probability, task severity, exposure duration, workforce size, and contextual variables, such as weekday effects, and site conditions, like waste accumulation. Additionally, it incorporates a structured questionnaire to capture the implementation of safety measures on site. Its nonlinear formulation reflects interactions among factors, penalizes temporal clustering of high-risk tasks, and prioritizes temporal distribution and proactive planning. To produce risk-aware schedules, a hybrid optimization framework that couples a tree-based constructive heuristic with the marine predators algorithm is introduced, maximizing NMF-SI subject to project-duration, precedence, and resource constraints. In simulation, the optimized schedules achieve higher NMF-SI values and a smoother risk profile over time than baseline plans. These results translate into a quantitative, data-driven contribution to safety by design, offering a practical decision-support tool for intelligent, risk-aware construction scheduling. Full article

Bursera microphylla A. Gray (Burseraceae) is a medicinal plant native to Sonora, Mexico, with antioxidant, anti-inflammatory, and antiproliferative properties. However, the pharmacological potential of its ecotypes remains underexplored. This study evaluated the biological activity and chemical composition of ethanolic extracts from the fruit and stem of the Magdalena ecotype. Total phenolic content was quantified using the Folin–Ciocalteu method, and phenolic profiles were characterized by ESI-IT-MS. Antioxidant activity was assessed by DPPH and FRAP assays; anti-inflammatory activity was evaluated by measuring nitric oxide (NO) and tumor necrosis factor-alpha (TNF-α) levels in LPS-activated RAW 264.7 macrophages. Antiproliferative activity was tested against LS180, C-33 A, and ARPE-19 cell lines using the MTT assay. Fruit extract exhibited higher phenolic content (180.6 ± 22.0 mg GAE/g) and ferric-reducing power (FRAP = 2034.3 ± 89.7 μM Fe(II)/g), whereas the stem extract showed stronger DPPH scavenging capacity (IC₅₀ = 52.9 ± 0.02 μg/mL). For the first time, gallic acid glucoside, kaempferol rhamnoside, quercetin rhamnoside, and isorhamentin xyloside were identified in B. microphylla fruit extract. Furthermore, the fruit extract significantly reduced NO production (93.6 ± 4.6 μg/mL) and TNF-α levels (IC₅₀ = 101.5 ± 9.1 μg/mL). It also showed strong cytotoxicity against C-33 A (IC₅₀ = 0.6 ± 0.07 μg/mL) and LS180 (0.7 ± 0.01 μg/mL), with lower cytotoxicity in ARPE-19 cells (77.9 ± 4.3 μg/mL). These findings highlight the therapeutic potential of the Magdalena ecotype, likely associated with its phenolic and other bioactive metabolites that require further investigation. Full article

Dietary sodium restriction is widely recommended in heart failure (HF) management; however, its benefits and risks remain a subject of ongoing debate. While moderate sodium reduction may improve symptoms and quality of life in selected patients, excessive restriction can trigger maladaptive neurohormonal activation, worsen renal function, and increase the risk of hyponatremia, malnutrition, and cachexia. Patient response is heterogeneous, influenced by clinical risk profile, salt sensitivity, comorbidities, and age, with some high-risk patients experiencing neutral or adverse outcomes. Additional challenges arise from hidden sodium in processed foods, medications, and meals, which complicate monitoring and adherence. Effective sodium management in HF therefore requires a nuanced, individualized approach that integrates risk stratification, dietary counseling, and public health measures targeting the food industry. Future research should refine patient selection criteria and establish optimal sodium targets to balance therapeutic efficacy with safety in real-world practice. Full article

This study presents the geometric optimization of a Savonius-type VAWT with multi-element blade profiles using a full factorial design integrated with RSM. Two crucial geometric parameters, the blade twist angle ($\gamma$) and the aspect ratio ($AR$), were systematically varied to assess their influence on the power coefficient ($C_p$). Experimental measurements were performed in a controlled wind tunnel environment, and a second-order regression equation was used to model the resulting data. The optimization approach identified the combination of $\gamma$ and $AR$ that maximized $C_p$. The optimal configuration was achieved with a $\gamma$ of 30° and an $AR$ of 2.0, for which the experimentally measured power coefficient ($C_p$) reached a value of 0.2326. The results confirm that lower twist angles and higher aspect ratios enhance aerodynamic efficiency, reduce manufacturing complexity, and improve structural reliability. These findings highlight the potential of Savonius turbines as competitive solutions for small-scale energy harvesting in low-wind-speed environments. Moreover, the identified optimal configuration provides a basis for future work that focuses on scaling the design, integrating power transmission and electrical generation components, and validating performance under real operating conditions. Full article

In this study, we evaluate a phosphorus-based fire retardant (HR Prof) on Norway spruce using Simultaneous Thermal Analysis (STA: TG/DTG/DSC), Gas Chromatography–Mass Spectrometry (GC–MS), and bench-scale mass-loss measurements. Relative to the untreated reference, HR Prof re-routes decomposition toward earlier dehydration and transient char, simplifies the evolved gas mixture in the 150–250 °C range, and reduces burning intensity during 600 s of radiant exposure. Across 150/200/250 °C, identified components fell from 20/24/51 (reference) to 5/9/9 (HR Prof); no phosphorus-containing volatiles were detected in this window. Mass-loss tests showed a lower average burning rate (0.107 vs. 0.156%·s⁻¹) and a smaller cumulative loss at 600 s (64.2 ± 9.5% vs. 93.7 ± 2.1%; one-way ANOVA, p < 0.05 for percentage loss). STA was conducted in air; the transient char formed at an intermediate temperature is oxidized near ~600 °C, explaining the low final residue despite earlier charring. A count-based Poisson model corroborated the significant reduction in volatile component richness for HR Prof (p < 0.001). The cross-method correspondences—earlier condensed-phase dehydration/char → leaner volatile pool → lower and flatter burning-rate profiles—support a condensed-phase-dominated protection mechanism within the conditions studied. Full article

Investigating the optimal planting strategies for brassica vegetables under variable climatic conditions is essential for developing sustainable production systems in northern agricultural regions. However, comprehensive knowledge about how planting timing modulates growth, physiological responses, and yield parameters across different cultivars remains limited. We investigated vegetative development, root morphology, physiological efficiency, and marketable yield in six cauliflower cultivars (‘Amazing’, ‘Cheddar’, ‘Clementine’, ‘Flame Star’, ‘Snow Crown’, and ‘Vitaverde’) subjected to four planting dates (May 1, May 15, June 1, and June 15) across two growing seasons (2023–2024), followed by detailed morphological and physiological profiling. Planting date, cultivar selection, and seasonal variation significantly influenced all measured parameters (p < 0.001), with notable interaction effects observed for fresh root weight, stomatal conductance, water use efficiency, and yield components. Early planted cultivars consistently demonstrated superior performance under variable environmental conditions, maintaining higher growth rates, enhanced root development, and improved physiological efficiency, particularly ‘Flame Star’, ‘Snow Crown’, and ‘Cheddar’, compared to late-planted treatments. Recovery of optimal plant development was most pronounced at May planting dates, with early-established crops showing better maintenance of vegetative growth patterns and enhanced yield potential, including higher curd weights (585.7 g for ‘Flame Star’) and superior marketable grades. Morphological profiling revealed distinct clustering patterns, with early-planted cultivars forming separate groups characterized by elevated root biomass, enhanced physiological parameters, and superior yield characteristics. In contrast, late-planted crops showed reduced performance, indicative of environmental stress responses. We conclude that strategic early planting significantly enhances cauliflower production resilience through comprehensive optimization of growth, physiological, and yield parameters, particularly under May establishment conditions. The differential performance responses between planting dates provide insights for timing-based management strategies, while the quantitative morphological and physiological profiles offer valuable parameters for assessing crop adaptation and commercial viability potential under variable climatic scenarios in northern agricultural systems. Full article

Background: Proliferative diabetic retinopathy (PDR) is a vision-threatening complication of diabetes characterized by retinal neovascularization. Predicting which diabetic patients will develop PDR remains challenging. Measuring mRNA expression levels may help elucidate the molecular pathways involved in PDR pathogenesis. This study investigated the expression of genes related to inflammatory and proliferative pathways in the peripheral blood of patients with PDR, compared to patients with non-proliferative diabetic retinopathy (NPDR) and healthy controls, using NanoString technology. The findings may aid in identifying potential biomarkers and therapeutic targets for early intervention. Methods: This prospective study was approved by the institutional ethics review board, and written informed consent was obtained from all participants. The study included patients with PDR (n = 9), NPDR (n = 8), and non-diabetic controls (n = 6). Total RNA was extracted from whole blood samples using the MagNA Pure Compact RNA Isolation Kit (Roche Ltd., Basel, Switzerland) and analyzed with the NanoString platform (Agentek Ltd., Yakum, Israel). Results: Expression levels of 578 genes across 15 signaling pathways, including inflammation (e.g., IL-17, TNF, and NF-κB) and cancer-related PI3K-Akt pathways, were evaluated. Sixty-six genes (11.5%) were differentially expressed (p < 0.05) between the PDR group and the NPDR and control groups. The most prominently overexpressed genes in PDR included TGFβ1, TGFβ1R, IL23R, BAX, and CFB, which were primarily involved in inflammatory and proliferative signaling. Conclusions: Gene expression profiling using NanoString technology revealed significant upregulation of genes related to inflammation and proliferation in patients with PDR. These findings suggest that beyond angiogenesis, inflammatory and proliferative pathways may play a central role in PDR development and could serve as targets for novel therapeutic strategies. Full article

Background: Cardiac-respiratory dual gating in SPECT (DG-SPECT) is an emergent technique for alleviating motion blurring artifacts in myocardial perfusion imaging (MPI) due to both cardiac and respiratory motions. Moreover, the attenuation artifact may arise from the spatial mismatch between the sequential SPECT and CT attenuation scans due to the dual gating of SPECT data and non-gating CT images. Objectives: This study adapts a four-dimensional (4D) cardiac SPECT reconstruction with post-reconstruction respiratory motion correction (4D-RMC) for dual-gated SPECT. In theory, a respiratory motion-matched attenuation correction (MAC) method is expected to yield more accurate reconstruction results than the conventional motion-averaged attenuation correction (AAC) method. However, its potential benefit is not clear in the presence of practical imaging artifacts in DG-SPECT. In this study, we aim to quantitatively investigate these two attenuation methods for SPECT MPI: 4D-RMC (MAC) and 4D-RMC (AAC). Methods: DG-SPECT imaging (eight cardiac gates and eight respiratory gates) of the NCAT phantom was simulated using SIMIND Monte Carlo simulation, with a lesion (20% reduction in uptake) introduced at four different locations of the left ventricular wall: anterior, lateral, septal, and inferior. For each respiratory gate, a joint cardiac motion-compensated 4D reconstruction was used. Then, the respiratory motion was estimated for post-reconstruction respiratory motion-compensated smoothing for all respiratory gates. The attenuation map averaged over eight respiratory gates was used for each respiratory gate in 4D-RMC (AAC) and the matched attenuation map was used for each respiratory gate in 4D-RMC (MAC). The relative root mean squared error (RMSE), structural similarity index measurement (SSIM), and a Channelized Hotelling Observer (CHO) study were employed to quantitatively evaluate different reconstruction and attenuation correction strategies. Results: Our results show that the 4D-RMC (MAC) method improves the average relative RMSE by as high as 5.42% and the average SSIM value by as high as 1.28% compared to the 4D-RMC (AAC) method. Compared to traditional 4D reconstruction without RMC (“4D (MAC)”), these metrics were improved by as high as 11.23% and 27.96%, respectively. The 4D-RMC methods outperformed 4D (without RMC) on the CHO study with the largest improvement for the anterior lesion. However, the image intensity profiles, the CHO assessment, and reconstruction images are very similar between 4D-RMC (MAC) and 4D-RMC (AAC). Conclusions: Our results indicate that the improvement of 4D-RMC (MAC) over 4D-RMC (AAC) is marginal in terms of lesion detectability and visual quality, which may be attributed to the simple NCAT phantom simulation, but otherwise suggest that AAC may be sufficient for clinical use. However, further evaluation of the MAC technique using more physiologically realistic digital phantoms that incorporate diverse patient anatomies and irregular respiratory motion is warranted to determine its potential clinical advantages for specific patient populations undergoing dual-gated SPECT myocardial perfusion imaging. Full article

Modern healthcare and engineering both rely on robust reliability models, where handling censored data effectively translates into longer-lasting devices, improved therapies, and safer environments for society. To address this, we develop a novel inferential framework for the ZLindley (ZL) distribution under the improved adaptive progressive Type-II censoring strategy. The proposed approach unifies the flexibility of the ZL model—capable of representing monotonically increasing hazards—with the efficiency of an adaptive censoring strategy that guarantees experiment termination within pre-specified limits. Both classical and Bayesian methodologies are investigated: Maximum likelihood and log-transformed likelihood estimators are derived alongside their asymptotic confidence intervals, while Bayesian estimation is conducted via gamma priors and Markov chain Monte Carlo methods, yielding Bayes point estimates, credible intervals, and highest posterior density regions. Extensive Monte Carlo simulations are employed to evaluate estimator performance in terms of bias, efficiency, coverage probability, and interval length across diverse censoring designs. Results demonstrate the superiority of Bayesian inference, particularly under informative priors, and highlight the robustness of HPD intervals over traditional asymptotic approaches. To emphasize practical utility, the methodology is applied to real-world reliability datasets from clinical trials on leukemia patients and hydrological measurements from River Styx floods, demonstrating the model’s ability to capture heterogeneity, over-dispersion, and increasing risk profiles. The empirical investigations reveal that the ZLindley distribution consistently provides a better fit than well-known competitors—including Lindley, Weibull, and Gamma models—when applied to real-world case studies from clinical leukemia trials and hydrological systems, highlighting its unmatched flexibility, robustness, and predictive utility for practical reliability modeling. Full article

Background/Objectives: Metformin (Met) is a potent antidiabetic drug that also exhibits anticancer, antioxidant, and organ-protective properties. Luteolin (Lut), a naturally occurring flavonoid found in many plant species, possesses anticancer, antioxidant, and anti-inflammatory effects. Since both compounds affect cellular metabolism and oxidative balance, the analysis of metabolites produced in living cells provides insight into biochemical alterations occurring in cancer cells and enables monitoring of treatment response. Methods: In this study, Met (1–20 mM) and Lut (1–100 µM) were tested in vitro, both individually and in combination, to evaluate their effects on cell viability, free radical levels, and metabolite profile alterations in cancer and normal cell lines (MDA-MB-231, SW620, and V79). Cell viability was assessed using the MTT assay at two time points (24 h and 48 h), while reactive oxygen species (ROS) levels were measured after hydrogen peroxide stimulation (100 µM H₂O₂) using the DCF-DA assay. Metabolomic changes induced by Met and Lut were analyzed by ¹H NMR spectroscopy. Results: The analysis showed that Lut reduced the viability of MDA-MB-231 cells at both time points, whereas Met decreased viability only after prolonged incubation. Met did not inhibit the proliferation of SW620 colorectal cancer cells, while Lut reduced viability at higher concentrations (100 µM after 24 h, and 50–100 µM after 48 h). Conclusions: The combination of metformin and luteolin demonstrated additive effects in reducing cell viability and oxidative stress compared with single-compound treatments. Normal V79 fibroblasts responded to both Met and Lut, individually and in combination. Both compounds exhibited moderate antioxidant properties in cells exposed to 100 µM H₂O₂. Lut (25 µM) reduced free radical levels in MDA-MB-231 cells, whereas Met (2.5 mM) did so in SW620 cells. The combination of both compounds increased ROS levels in SW620 cells subjected to oxidative stress. Overall, co-treatment with metformin and luteolin altered metabolic pathways and induced changes in intra- and extracellular metabolite levels across all tested cell lines. The observed additive effects suggest that the combined use of metformin and luteolin may enhance anticancer and antioxidant responses, warranting further in vivo studies to confirm these interactions. Full article

Adequate ridge width and thermal control are critical for predictable implant site preparation. This in vitro study compared conventional osteotomy (CO), osseodensification (OD), and OsseoShaper (OS) protocols in standardized polyurethane foam blocks simulating narrow D2 ridges. A total of 18 osteotomies (n = 6 per group) were prepared under protocol-specific irrigation. Ridge width was measured at 3, 6, and 9 mm apical to the crest before and after osteotomy using a digital caliper, and expansion (ΔW) was calculated. Intraoperative thermal changes (ΔT) were recorded in real time with an infrared thermal camera. OD achieved consistent expansion at all depths (p < 0.05), while OS produced significant widening at the 3 and 6 mm levels; CO yielded only a minor but significant gain at the 3 mm level. At the intergroup level, OS showed significantly greater crestal expansion than CO at 3 mm (p = 0.006). All protocols generated comparable thermal changes (mean ΔT 7.4–8.2 °C), remaining well below the critical 47 °C threshold. Within the limitations of this in vitro model, OD and OS enhanced ridge expansion compared with CO, particularly at the crestal level, where expansion is most critical. All protocols maintained thermally safe profiles, supporting their clinical applicability. Full article

Reversine is a small-molecule Aurora kinase inhibitor known for its pro-apoptotic effects and potential to remodel chromatin architecture. Although its impact on mitotic regulation is established, its effects on telomere dynamics and nuclear organization in chronic myeloid leukemia (CML) remain unclear. This study aimed to investigate the effects of reversine on telomere architecture, genomic instability, and apoptosis in CML cell lines (K-562 and MEG-01). Reversine was applied at increasing concentrations, and cytotoxicity was assessed using caspase-3/7 activation assays. Quantitative PCR was used to measure AURKA and AURKB mRNA expressions. Three-dimensional telomere architecture was analyzed with TeloView^® v1.03 software after Q-FISH labeling to quantify telomere number, signal intensity, aggregation, nuclear volume, and a/c ratio. Reversine induced a dose- and time-dependent apoptotic response in both cell lines and significantly downregulated AURKA and AURKB expressions. Three-dimensional telomere analysis revealed a marked reduction in telomere number and aggregates, signal intensity, and nuclear volume. While reduced signal intensity may indicate telomere shortening, the concurrent decrease in aggregation and altered spatial parameters suggests telomeric reorganization rather than progressive instability. These features reflect structural nuclear remodeling and early apoptotic commitment. Differences between K-562 and MEG-01 responses underscore potential heterogeneity in telomere maintenance mechanisms. Reversine modulates genomic stability in CML cells through dual mechanisms involving Aurora kinase inhibition and telomere architecture remodeling. The integration of 3D telomere profiling highlights reversine’s potential as a therapeutic agent targeting nuclear disorganization and mitotic dysregulation in leukemia. Full article

University students face rising mental health pressures, making restorative environmental perception (REP) in campus forests critical for psychological recovery. While environmental factors are recognized contributors, Socio-Ecological Systems (SES) theory emphasizes that environmental and social processes are interdependent. Within this context, informal social interaction (ISI)—low-effort encounters such as greetings or small talk—represent a key social dimension that may complement environmental restoration by fostering comfort and embedded affordances. However, most studies examine these factors separately, often using coarse measures that overlook heterogeneity in restorative mechanisms. This study investigates how environmental-exposure and social–environmental context dimensions jointly shape REP in campus forests, focusing on distributional patterns beyond average effects. Using a Public Participation Geographic Information Systems (PPGIS) approach, 30 students photographed 1294 tree-dominant scenes on a forest-rich campus. Environmental features were quantified via semantic segmentation, and ISI was rated alongside REP. Quantile regression estimated effects across the REP distribution. Three distributional patterns emerged. First, blue exposure and ISI acted as reliable resources, consistently enhancing REP with distinct profiles. Second, green exposure functioned as a threshold-dependent resource, with mid-quantile attenuation but amplified contributions in highly restorative scenes. Third, anthropogenic and demographic factors created conditional barriers with distribution-specific effects. Findings demonstrate that campus forest restoration operates through differentiated socio-ecological mechanisms rather than uniform pathways, informing strategies for equitable, restoration-optimized management. More broadly, the distributional framework offers transferable insights for urban forests as socio-ecological infrastructures supporting both human well-being and ecological resilience. Full article

Vertical line source irrigation is a localized water-saving technique suitable for deep-rooted crops, but the geometric structure of the wetted bulb lacks a systematic analytical modeling method. This study established a simplified three-dimensional (3D) analytical model to predict the wetted volume under vertical line source irrigation conditions. First, the model determined boundary points based on an empirical wetting-front equation and fitted the wetting profile with ellipse–parabola functions to derive analytical expressions for area and volume. Then, using aeolian sandy soil as the research object, the model predicted that during 0–250 min of irrigation, the wetted pattern area increased from 80.0 cm² to 5050.6 cm², and the wetted volume increased from 251.3 cm³ to 208,014.4 cm³. At 250 min, the lower, middle, and upper volume components accounted for 67.3%, 24.2%, and 8.4%, respectively. Finally, the model was validated using loam soil, and the results showed good agreement between the calculated and measured values. The model requires only simple input and enables fast computation. It effectively characterizes the three-dimensional spatiotemporal variation of the wetted bulb and provides a theoretical reference for the design of pipe spacing and irrigation quota. Full article