Search Results (920)

(1) Background: The concentration of lamotrigine, an antiepileptic drug very often used in bipolar disorder, is most often determined in the blood, with many inconveniences. An alternative may be to use saliva as a diagnostic material for this purpose. The development of a method to determine lamotrigine in saliva as a biological material significantly improves patient comfort during sampling. The developed method uses solid-phase extraction for the isolation of the drug from saliva for the first time. (2) Methods: This study aimed to develop a method to determine lamotrigine in saliva using solid-phase extraction (SPE) for isolation and liquid chromatography with a diode array detector (LC-DAD) for quantitative analysis. (3) Results: The method was validated by determining its linearity in the concentration range 10–2000 ng/mL (R² > 0.99), and the intra- and inter-day precision expressed as coefficient of variation (CV%) did not exceed 15%. (4) Conclusions: The developed method was used to determine the salivary concentration of lamotrigine in patients treated with the studied compound, confirming its usefulness in bipolar disorder (BD). Full article

In the process of plant protection for fruit trees using rotary-wing UAVs, challenges such as droplet drift, insufficient canopy penetration, and low agrochemical utilization efficiency remain prominent. Among these, the uncertainty in the spatio-temporal distribution of downwash airflow is a key factor contributing to non-uniform droplet deposition and increased drift. To address this issue, we developed a wind field numerical simulation model based on an improved hierarchical leaf density model to clarify the spatio-temporal characteristics of downwash airflow, the scale of turbulence regions, and their effects on internal canopy airflow under varying flight altitudes and different rotor speeds. Field experiments were conducted in orchards to validate the accuracy of the model. Simulation results showed that the average error between the simulated and measured wind speeds inside the canopy was 8.4%, representing a 42.11% reduction compared to the non-hierarchical model and significantly improving the prediction accuracy. The coefficient of variation (CV) was 0.26 in the middle canopy layer and 0.29 in the lower layer, indicating a decreasing trend with an increasing canopy height. We systematically analyzed the variation in turbulence region scales under different flight conditions. This study provides theoretical support for optimizing UAV operation parameters to improve droplet deposition uniformity and enhance agrochemical utilization efficiency. Full article

Background: COVID-19-associated coagulopathy (CAC) is a complex condition, with high rates of thrombosis, high levels of inflammation markers and hypercoagulation (increased levels of fibrinogen and D-Dimer), as well as extensive microthrombosis in the lungs and other organs of the deceased. It resembles, without being identical, other coagulation disorders such as sepsis-DIC (SIC/DIC), hemophagocyte syndrome (HPS) and thrombotic microangiopathy (TMA). Platelets (PLTs), key regulators of thrombosis, inflammation and immunity, are considered an important risk mediator in COVID-19 pathogenesis. Platelet index MPV/PLT ratio is reported in the literature as more specific in the prognosis of platelet-related systemic thrombogenicity. Studies of MPV/PLT ratio with regards to the severity of COVID-19 disease are limited, and there are no references regarding this ratio to the outcome of COVID-19 disease at specific time points of hospitalization. The aim of this study is to evaluate the relationship of COVID-19 mortality with the red cell distribution width–coefficient of variation (RDW-CV), platelets and MPV/PLT ratio parameters. Methods: Values of these parameters in 511 COVID-19 hospitalized patients were recorded (a) on admission, (b) as mean values of the 1st and 2nd week of hospitalization, (c) over the total duration of hospitalization, (d) as nadir and zenith values, and (e) at discharge. Results: As for mortality (survivors vs. deceased), statistical analysis with ROC curves showed that regarding the values of the parameters on admission, only the RDW-CV baseline was of prognostic value. Platelet parameters, absolute number and MPV/PLT ratio had predictive potential for the disease outcome only as 2nd week values. On the contrary, with regards to disease severity (mild/moderate versus severe/critical), only the MPV/PLT ratio on admission can be used for prognosis, and to a moderate degree. On multivariable logistic regression analysis, only the RDW-CV mean hospitalization value (RDW-CV mean) was an independent and prognostic variable for mortality. Regarding disease severity, the MPV/PLT ratio on admission and RDW-CV mean were independent and prognostic variables. Conclusions: RDW-CV, platelets and MPV/PLT ratio hematological parameters could be of predictive value for mortality and severity in COVID-19 disease, depending on the hospitalization timeline. Full article

Forest structure parameters are critical for understanding and managing forest ecosystems, yet sparse forests have received limited attention in previous studies. To address this research gap, this study systematically evaluates and compares the sensitivity of active Synthetic Aperture Radar (SAR) and passive optical remote sensing to key forest structure parameters in sparse forests, including Diameter at Breast Height (DBH), Tree Height (H), Crown Width (CW), and Leaf Area Index (LAI). Using the novel computer-graphics-based radiosity model applicable to porous individual thin objects, named Radiosity Applicable to Porous Individual Objects (RAPID), we simulated 38 distinct sparse forest scenarios to generate both SAR backscatter coefficients and optical reflectance across various wavelengths, polarization modes, and incidence/observation angles. Sensitivity was assessed using the coefficient of variation (CV). The results reveal that C-band SAR in HH polarization mode demonstrates the highest sensitivity to DBH (CV = −6.73%), H (CV = −52.68%), and LAI (CV = −63.39%), while optical data in the red band show the strongest response to CW (CV = 18.83%) variations. The study further identifies optimal acquisition configurations, with SAR data achieving maximum sensitivity at smaller incidence angles and optical reflectance performing best at forward observation angles. This study addresses a critical gap by presenting the first systematic comparison of the sensitivity of multi-band SAR and VIS/NIR data to key forest structural parameters across sparsity gradients, thereby clarifying their applicability for monitoring young and middle-aged sparse forests with high carbon sequestration potential. Full article

In agricultural practice, in addition to determining the nitrogen (N_f) dose, it is necessary to effectively control its effect on currently grown crops. Meeting these conditions requires not only the use of phosphorus (P) and potassium (K), but also nutrients such as magnesium (Mg) and sulfur (S). This hypothesis was verified in a single-factor field experiment with winter wheat (WW) carried out in the 2015/2016, 2016/2017, and 2017/2018 growing seasons. The experiment consisted of seven variants: absolute control (AC), NP, NPK-MOP (K as Muriate of Potash), NPK-MOP+Ki (Kieserite), NPK-KK (K as Korn–Kali), NPK-KK+Ki, and NPK-KK+Ki+ES (Epsom Salt). The use of K as MOP increased grain yield (GY) by 6.3% compared to NP. In the NPK-KK variant, GY was 13% (+0.84 t ha⁻¹) higher compared to NP. Moreover, GYs in this fertilization variant (FV) were stable over the years (coefficient of variation, CV = 9.4%). In NPK-KK+Ki+ES, the yield increase was the highest and mounted to 17.2% compared to NP, but the variability over the years was also the highest (CV ≈ 20%). The amount of N in grain N (GN) increased progressively from 4% for NPK-MOP to 15% for NPK-KK and 25% for NPK-KK+Ki+ES in comparison to NP. The nitrogen harvest index was highly stable, achieving 72.6 ± 3.1%. All analyzed NUE indices showed a significant response to FVs. The PFP-N_f (partial factor productivity of N_f) indices increased on NPK-MOP by 5.8%, NPK-KK by 12.9%, and NPK-KK+Ki+ES by 17.9% compared to NP. The corresponding N_f recovery of N_f in wheat grain was 47.2%, 55.9%, and 64.4%, but its total recovery by wheat (grain + straw) was 67%, 74.5%, and 87.2%, respectively. In terms of the theoretical and practical value of the tested indexes, two indices, namely, NUP (nitrogen unit productivity) and NUA (nitrogen unit accumulation), proved to be the most useful. From the farmer’s production strategy, FV with K applied in the form of Korn–Kali proved to be the most stable option due to high and stable yield, regardless of weather conditions. The increase in the number of nutritional factors optimizing the action of nitrogen in winter wheat caused the phenomenon known as the “scissors effect”. This phenomenon manifested itself in a progressive increase in nitrogen unit productivity (NUP) combined with a regressive trend in unit nitrogen accumulation (NUA) in the grain versus the balance of soil available Mg (Mg_b). The studies clearly showed that obtaining grain that met the milling requirements was recorded only for NUA above 22 kg N t⁻¹ grain. This was possible only with the most intensive Mg treatment (NPK-KK+Ki and NPK-KK+Ki+ES). The study clearly showed that three of the six FVs fully met the three basic conditions for sustainable crop production: (i) stabilization and even an increase in grain yield; (ii) a decrease in the mass of inorganic N in the soil at harvest, potentially susceptible to leaching; and (iii) stabilization of the soil fertility of P, K, and Mg. Full article

Background/Objectives: The aim of this study is to compare the parameters of the corneal endothelium in a group of patients with well-controlled type 2 diabetes (study group) to those of patients who do not have type 2 diabetes (control group). Methods: The study aims to compare the corneal endothelium parameters of 80 eyes (80 patients) with well-controlled type 2 diabetes to 80 eyes (80 patients) without type 2 diabetes. The endothelial cell density (ECD), percentage of hexagonal cells (%HEX), coefficient of variation in cell size (CV), and central corneal thickness (CCT) were recorded using a non-contact specular microscope (Nidek CEM-530, Nidek Co., Ltd., Gamagori, Japan). Best-corrected visual acuity (BCVA) and intraocular pressure (IOP) were also measured. Results: The groups were matched for age and sex. A significantly lower ECD value was observed in the group of patients with type 2 diabetes (2480.76 cells/mm² ± 303.48) compared to the control group (2629.64 cells/mm² ± 304.73) (p = 0.002). BCVA was also significantly lower in the study group (0.44 ± 0.18) compared to the control group (0.50 ± 0.19) (p = 0.049). No statistically significant differences were found between the groups in terms of IOP, CV, %HEX, and CCT. Conclusions: Patients with well-controlled type 2 diabetes exhibit a lower ECD compared to individuals without diabetes, even in the absence of advanced diabetic complications. These subtle changes may have clinical implications for preoperative evaluation and long-term management in diabetic patients. The other morphological parameters of the corneal endothelium remain comparable between the groups. Full article

Perca schrenkii populations are experiencing significant declines, yet comprehensive morphological studies are still lacking. Understanding the relationship between morphological traits and body weight is crucial for conservation and breeding programs. We analyzed 13 morphological traits in 100 P. schrenkii specimens from Hamsigou Reservoir using correlation analysis, path analysis, and principal component analysis (PCA). Body weight exhibited the highest variability (CV = 39.76%). Strong correlations were observed between body weight and body length (R = 0.942), total length, and body width. A four-variable regression model explained 94.1% of body weight variation, with body length showing the strongest direct effect (path coefficient = 0.623). The first three principal components accounted for 76.687% of the total variance. Our findings demonstrate that BL, BW, BD, and ES can effectively predict body weight, providing valuable insights for the conservation and selective breeding of P. schrenkii. Full article

A comprehensive analysis of the evolution of rainfall characteristics in Catalonia, NE Spain, was conducted using monthly data from 72 rain gauges over the period 1950–2022. A moving-window approach was applied at annual, seasonal, and monthly scales, calculating mean values, coefficients of variation (CV), and trends across 43 overlapping 31-year periods. To assess trends in these moving statistics, a modified Mann–Kendall test was applied to both the 31-year means and CVs. Results revealed a significant 10% decrease in annual rainfall, with summer showing the most pronounced decline, as nearly 90% of stations exhibited negative trends, while the CV showed negative trends in coastal areas and mostly positive trends inland. At the monthly scale, February, March, June, August, and December exhibited negative trends at more than 50% of stations, with rainfall reductions ranging from 20% to 30%. Additionally, the temporal evolution of Mann–Kendall trend coefficients within each 31-year moving window displayed a fourth-degree polynomial pattern, with a periodicity of 30–35 years at annual and seasonal scales, and for some months. Finally, at the annual scale and in two centennial series, the 80-year oscillations found were inversely correlated with the large-scale climate indices North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation (AMO). Full article

Landslide is one of the most damaging natural hazards, causing extensive damage to the infrastructure and threatening human life. Although advances have been made in landslide susceptibility assessment by objective explainable machine learning, the interpretability robustness of traditional single landslide susceptibility model is still low. The proposed interpretable hybrid model in this study overcomes these challenges and aims to enhance the stability of landslide susceptibility interpretability. The model integrates three base machine learning models—LightGBM, XGBoost, and Random Forest—using a heterogeneous category strategy, thereby enhancing the robustness of model interpretability. The hybrid model is interpreted using SHAP (Shapley Additive Explanations) values, which quantify feature contributions. A 10-fold cross-validation with the coefficient of variation (CV) metric reveals that the hybrid model outperforms individual base models in terms of interpretive robustness, yielding a lower CV value of 0.175 compared to 0.208 for LightGBM, 0.240 for XGBoost, and 0.207 for the Random Forest model. Although predictive accuracy remains comparable to the baseline models, the hybrid model provides more stable and reliable interpretability results for landslide susceptibility. It identifies the slope, elevation, and LS factor as the three most important factors for landslide susceptibility in Xi’an city. Furthermore, the quantitative nonlinear relationships between these predisposing factors and susceptibility were identified, providing empowering knowledge for the landslides risk prevention and urban planning in the regions vulnerable to landslides. Full article

This study investigates the feasibility of pumice-based internal curing based on the 3D printability of engineered cementitious composites (ECCs) for water-scarce environments and arid regions. Natural river sand was partially replaced with the presoaked pumice lightweight aggregates (LWAs) at two different levels, 30% and 60% by volume, and 50% of the cement was replaced with slag to enhance sustainability. Furthermore, 2% polyethylene (PE) fibers were used to improve the mechanical characteristics and 1% methylcellulose (MC) was used to increase the rheological stability. Pumice aggregates, presoaked for 24 h, were used as an internal curing agent to assess their effect on the printability. Three ECC mixes, CT-PE2-6-10 (control), P30-PE2-6-10 (30% pumice), and P60-PE2-6-10 (60% pumice), were printed using a 3D gantry printing system. A flow table and rheometer were used to evaluate the flowability and rheological properties. Extrudability was measured in terms of dimensional consistency and the coefficient of variation (CV%) to evaluate printability, whereas buildability was determined in terms of the maximum number of layers stacked before failure. All of the mixes met the extrudability criterion (CV < 5%), with P30-PE2-6-10 demonstrating superior printing quality and buildability, having 16 layers, which was comparable with the control mix that had 18 layers. Full article

Halloysite nanotubes, a naturally occurring nanomaterial with a unique tubular morphology, have shown considerable potential for heavy metal remediation. However, significant inconsistencies in the reported maximum adsorption capacities (q_max) for heavy metal ions—such as Pb²⁺, which ranges from 7.5 to 84.0 mg/g with a coefficient of variation (CV) of 68%—have severely hindered both scientific understanding and practical application of this promising material. To address this critical knowledge gap, we conducted a reassessment using carefully selected halloysite specimens from three geologically distinct deposits (Utah, USA; Henan and Yunnan, China). Under rigorously controlled experimental conditions, we precisely quantified the adsorption capacities of halloysite for Cd²⁺, Zn²⁺, and Pb²⁺. Through an integrated multi-technique characterization approach involving XRF, XRD, FTIR, TEM, and BET analyses, we identified two fundamental crystallochemical parameters that govern the adsorption performance of halloysite: the degree of lattice substitution and the density of surface hydroxyl groups. Our findings reveal that optimal heavy metal adsorption occurs in halloysite with lower lattice substitution and higher surface hydroxyl density. This work not only provides a reliable range of adsorption capacities for halloysite but, more importantly, establishes a scientific foundation for optimizing the application of halloysite in heavy metal remediation. Full article

Background/Objectives: Postprandial hyperglycemia is a risk factor for diabetes and cardiovascular diseases, even in healthy individuals. Kanzaki mulberry leaf and water chestnut tea (MW tea), a blend of mulberry (Morus alba) leaves and water chestnut (Trapa japonica) leaves and husks, is rich in polyphenols and 1-deoxynojirimycin (DNJ) and may suppress postprandial glucose spikes, but evidence regarding its short-term daily intake is limited. This study aimed to evaluate the postprandial glycemic response and safety of two-week MW tea consumption using continuous glucose monitoring (CGM). Methods: We conducted a randomized, double-blind, placebo-controlled, two-period crossover trial involving 31 participants. Each intervention period lasted two weeks, separated by a one-week washout. Participants consumed either MW tea or a placebo before meals. Interstitial glucose levels were measured every 15 min using CGM. Postprandial glucose responses were recorded every 15 min for 180 min after a standardized meal on the first day of each period. The primary outcome was the coefficient of variation (CV) in glucose levels, calculated using data from the central 10 days of each intervention period. Safety was assessed using CGM-derived hypoglycemia metrics and blood test results. Results: The CV of glucose levels during the MW tea period was significantly lower than during the placebo period (mean difference: 0.02, p = 0.0006). A significant reduction in 1 h postprandial glucose area under the curve was also observed. No significant differences were found in hypoglycemia occurrence, liver/renal/inflammatory markers, or self-reported adverse symptoms. Notably, 1,5-anhydroglucitol (1,5-AG) levels significantly increased during MW tea intake, suggesting improved glycemic control. Conclusions: Short-term consumption of Kanzaki MW tea effectively suppressed postprandial glucose variability without safety concerns. These findings support MW tea as a promising natural supplement for glycemic management and the prevention of diabetes. Full article

The Three Gorges Reservoir Area in China presents a critical conflict between industrial development and ecological conservation. It functions as a key hub for water management, energy production, and shipping, while also serving as a vital zone for ecological and environmental protection. Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. The findings indicate the following: (1) The RAGA-PP model outperforms conventional AHP-CV methods in assessing Zigui County’s eco-geological environment, showing superior accuracy (higher Moran’s I) and spatial consistency. (2) Hotspot analysis confirms these results, revealing distinct spatial patterns. (3) From 2000 to 2020, “bad” quality areas decreased from 17.31% to 12.33%, while “moderate” or “better” zones expanded. (4) This improvement reflects favorable natural conditions and reduced human impacts. These trends underscore the effectiveness of China’s ecological civilization policies, which have prioritized sustainable development through targeted environmental governance, afforestation initiatives, and stringent regulations on industrial activities. Full article

Sperm membrane potential (Em) hyperpolarization during capacitation is a functional hallmark of fertilizing ability and has been proposed as a predictive biomarker for conventional in vitro fertilization (IVF) success. However, it is unclear whether Em remains stable across ejaculates over time and can reliably guide assisted reproductive technology (ART) decisions in advance. Thus, we aimed to evaluate the temporal consistency of human sperm Em within individuals and assess its utility as a prognostic marker when measured days or weeks prior to IVF procedures. Em was assessed in capacitated and non-capacitated sperm from normospermic donors at three time points over 28 days, using a fluorometric assay. Capacitated values were compared to a −48.6 mV threshold previously associated with successful fertilization. Intra-donor Em variability and coefficients of variation (CV) were analyzed statistically. Our results showed that Em values exhibited significant intra-donor variability over time (p = 0.007), with approximately half of the donors crossing the −48.6 mV functional threshold across sessions. Capacitated sperm samples showed significantly greater variability than non-capacitated ones, with several donors exceeding a 30% CV cutoff. No consistent correlation was found between CV and mean Em values. While Em remains a promising functional marker when assessed on the day of IVF, its temporal variability undermines its reliability as a predictive tool for ART decisions made in advance. These findings underscore the importance of timing in functional sperm assessments and call for further studies to identify the physiological factors influencing Em stability. Full article

Agricultural greenhouse gas (GHG) emissions contribute significantly to climate change and underline the importance of reliable measurements and mitigation strategies. This life cycle assessment (LCA)-based study evaluates the environmental impacts of four key Mediterranean agricultural products, namely olives, sweet potatoes, corn, and grapes using GHG measurements at four pilot fields located in different regions of Greece. With the use of a cradle-to-gate approach six environmental impact categories, more specifically acidification potential (AP), eutrophication potential (EP), global warming potential (GWP), ozone depletion potential (ODP), photochemical ozone creation potential (POCP), and cumulative energy demand (CED) as energy-based indicator are assessed. The functional unit used is 1 ha of cultivated land. Any potential carbon offsets from mitigation practices are assessed through an integrated low-carbon certification framework and the use of innovative, site-specific technologies. In this context, the present study evaluates three life cycle inventory (LCI)-based scenarios: Baseline (BS), which represents a 3-year crop production period; Field-based (FS), which includes on-site CO₂ and CH₄ measurements to assess the effects of mitigation practices; and Inventoried (IS), which relies on comprehensive datasets. The adoption of carbon mitigation practices under the FS scenario resulted in considerable reductions in environmental impacts for all pilot fields assessed, with average improvements of 8% for olive, 5.7% for sweet potato, 4.5% for corn, and 6.5% for grape production compared to the BS scenario. The uncertainty analysis indicates that among the LCI-based scenarios evaluated, the IS scenario exhibits the lowest variability, with coefficient of variation (CV) values ranging from 0.5% to 7.3%. In contrast, the FS scenario shows slightly higher uncertainty, with CVs reaching up to 15.7% for AP and 14.7% for EP impact categories in corn production. The incorporation of on-site GHG measurements improves the precision of environmental performance and supports the development of site-specific LCI data. This benchmark study has a noticeable transferability potential and contributes to the adoption of sustainable practices in other regions with similar characteristics. Full article