Search Results (288)

This study compares the efficacy of ozonated sunflower oil (OSO) and ozonated olive oil (OOO) in terms of antioxidant properties, modulation of high-density lipoprotein (HDL) functionality, and protective effects against carboxymethyllysine (CML)-mediated stress in zebrafish embryos and adults. The spectral and electronic nose (e-nose) analyses revealed that OSO and OOO possessed markedly distinct physicochemical characteristics and volatile and olfactory constituents compared with non-ozonated sunflower (SO) and olive oil (OO). The fluorescence spectrum analysis of HDL treated with OOO and OSO exhibited a red shift (2.6~3.3 nm) in the wavelength maximum fluorescence (WMF), accompanied by pronounced quenching of tryptophan fluorescence. Additionally, a significant increase in HDL-associated paraoxonase (PON) and ferric ion reduction (FRA) activity was observed in the OSO- and OOO-treated HDL. However, compared to OOO, significantly higher PON and FRA activities were observed in HDL treated with OSO. Also, compared to OOO, OSO effectively reverses CML-induced oxidative stress, altered heart rate, and reduced embryo survival. Similarly, in adult zebrafish, CML-compromised survival, swimming impairment, and disturbed antioxidant parameters were prevented by treatment with OOO and OSO. Nonetheless, OSO showed significantly higher efficacy than OOO. Consistently, OSO substantially reduced the CML-elevated blood glucose, total cholesterol (TC), triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) levels with a marked increase in high-density lipoprotein cholesterol (HDL-C) levels. Notably, no significant effect of OOO was observed on the reduction in and augmentation of LDL-C and HDL-C, respectively. Both OOO and OSO significantly protect against CML-triggered liver and kidney damage. However, compared with OOO, OSO significantly reduced neutrophil infiltration, interleukin-6 (IL-6) production, liver steatosis, ROS generation, and cellular senescence in the kidneys. The study concludes that OSO exerts significantly higher beneficial effects than OOO on HDL functionality and antioxidant defense, thereby attenuating CML-induced inflammatory and oxidative damage. Full article

The increasing integration of renewable energy sources, high-voltage direct current (HVDC) and power-electronics-based equipment has intensified the exposure of transformer windings to high-frequency voltage components, steep-front transients and high-dv/dt stresses, highlighting the need for detailed high-frequency winding models. This study presents a high-frequency model of a six-section winding assembly corresponding to one phase of a 10 kV/0.41 kV, Dyn11, 2500 kVA distribution transformer. The winding assembly was experimentally investigated under coreless conditions using frequency response analysis (FRA) measurements over the frequency range of 20 Hz–2 MHz. Frequency-dependent resistance $\mathit{R}\left(f\right)$ parameters were extracted from finite element method (FEM)-based electromagnetic field analyses, while the self- and mutual inductance matrix and the capacitance parameters were obtained from electromagnetic and electrostatic field solutions, respectively. The resulting segmented resistance–inductance–mutual inductance–capacitance (R-L-M-C) equivalent circuit model was solved in the frequency domain using Modified Nodal Analysis (MNA). Before the FRA-based validation, the low-frequency consistency of the model was checked at 50.431 Hz, where the calculated and measured magnitudes differed by only 0.1074 dB. Over the common frequency range, the model achieved a root mean square error (RMSE) of 3.09 dB and a mean absolute error (MAE) of 1.76 dB. The results show that the proposed field-extracted model can represent the overall FRA trend, the dominant attenuation region and the main resonance/anti-resonance characteristics of the winding assembly, although deviations remain around sharp resonance points. Full article

While individual determinants of students’ well-being are well established, less is known about the association with the institutional context. This study evaluates institutional-level factors associated with students’ mental health while controlling for individual characteristics. The cross-sectional analysis used data from 12 German institutions (n = 13,715) collected in the StudiBiFra survey on study conditions and student mental health. Individual-level variables included gender, age, study subject group, and four mental health variables (general well-being, depressiveness, cognitive stress, and exhaustion). Institution-level variables comprised institution type, excellence status, multi-campus structure, size, and satisfaction with the quality of health promotion services. Multilevel binary logistic regression models were applied to examine associations between institutional characteristics and mental health outcomes, adjusting for individual factors. Students enrolled at universities of applied sciences showed a lower likelihood of reporting depressiveness and exhaustion. Higher levels of depressiveness and cognitive stress were observed among students at medium-sized institutions compared to small ones. Students not enrolled at institutions with excellence status had lower risks of depressiveness, stress, and exhaustion. Additionally, higher satisfaction with institutional health promotion services was associated with reduced odds of depressiveness. Institutional factors are related to students’ mental health beyond individual characteristics, highlighting the need for a holistic, setting-based approach. Full article

Family caregivers play a critical role in supporting patients with advanced cancer, yet their quality of life (QoL) is often adversely affected and remains insufficiently addressed in routine care. Although family relationships have been widely recognized as important in the caregiving context, their specific domains have rarely been examined in relation to caregiver outcomes. This study aimed to examine the associations between distinct domains of family relationships and caregiver QoL. A total of 170 caregivers were recruited from nine hospice units in Korea between September 2021 and March 2024. for this multicenter study. The Family Relationship Assessment Scale (FRAS) and the Korean version of the Caregiver QOL Index-Cancer (CQOLC-K) were used to assess family relationships and caregiver QoL, respectively. Multivariate regression analyses were performed to evaluate the associations between specific domains of family relationships and caregiver QoL. Family relationship domains were differentially associated with caregiver QoL. Overall family relationship scores were positively associated with QoL (β = 0.30, p = 0.004), while family conflict showed the strongest negative association (β = −1.03, p = 0.001). In contrast, family support was associated with better positive adaptation (β = 0.24, p = 0.027). The associations between family relationships and QoL were more pronounced among vulnerable caregivers, including those who were younger, unemployed, had lower social support or resilience, or were dissatisfied with care. Family relationships, particularly conflict and support, are important correlates of caregiver QoL. Incorporating the assessment of family relationship domains helps identify caregivers at increased risk and informs the development of more family-centered supportive approaches in palliative oncology care. Full article

The study compares the effects of the HSP60-derived mutated peptide (CIGB-258) and its wild-type peptide (E18-3) on preventing carboxymethyllysine (CML)- and ethanol (Et-OH)-induced hemorrhagic events and acute toxicity in zebrafish. The results suggest a 67% survivability and swimming recovery in CIGB-258-treated zebrafish compared to only 20% in the CML+Et-OH-treated group. No effect of E18-3 was noticed on CML+Et-OH-impaired zebrafish survivability and swimming ability. Similarly, no effect of E18-3 was noticed on the CML+Et-OH-disturbed blood oxidative and antioxidant variables. In contrast, CIGB-258 showed a notable 35% lower rate of oxidized contents, and 2.0-fold and 1.2-fold higher paraoxonase (PON) and ferric ion reduction activity (FRA), respectively, than in the E18-3 group. Also, the CML+Et-OH-induced dyslipidemia was substantially prevented by the CIGB-258, whereas no protective effect of E18-3 was noticed. Similarly, the CML+Et-OH-triggered hepatic inflammation, steatosis, kidney damage, severe gastrointestinal bleeding, and intestinal fibrosis were successfully mitigated by co-treatment with CIGB-258. Surface plasmon resonance analysis revealed a substantial binding affinity of CIGB-258 for HDL₂ and HDL₃, characterized by association rate constants (K_a) of 14.78 and 6.20 μM⁻¹s⁻¹, dissociation rate constants (K_d) of 0.35 s⁻¹ and 0.22 s⁻¹, and equilibrium dissociation constants (K_D) of 0.024 and 0.035 μM, respectively. In conclusion, CIGB-258 exerted a substantial impact on CML+Et-OH-triggered adverse events, with high affinity for HDL, whereas E18-3 exposure remained unaffected and failed to produce any beneficial effects. Full article

Three medium-chain fatty acids (MCFAs), namely decanoic acid, octanoic acid, and hexanoic acid, were identified in ozonated sunflower oil (OSO) using high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC/MS). All three MCFAs exhibited strong in vitro antioxidant activity to enhance high-density lipoprotein (HDL)-associated paraoxonase and protected low-density lipoproteins (LDL) from oxidative damage caused by Cu²⁺ ions. Consistently, MCFAs displayed substantial cellular antioxidant activity and minimized carboxymethyllysine (CML)-induced reactive oxygen species (ROS) generation and apoptotic cell death in zebrafish embryos. In adult zebrafish, MCFAs treatment mitigated CML-induced acute death and swimming abnormalities, and substantially augmented plasma sulfhydryl content, ferric ion reduction ability (FRA), and paraoxonase (PON)-like activity. Also, MCFA-treated zebrafish showed lower blood glucose, total cholesterol (TC) and triglycerides (TG) with raising HDL cholesterol levels. The MCFAs showed substantial inhibition of hepatic ROS generation, neutrophil efflux, interleukin (IL)-6 production, and steatosis, leading to hepatoprotection against CML-triggered adversity. Consistent with hepatic histology results, reduced plasma hepatic function biomarkers aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were observed in MCFA-treated groups than in the CML-treated group. In the kidney, MCFA treatment effectively reduced oxidative stress and cellular senescence and protected against kidney damage induced by exposure to CML. The study concludes the presence of three MCFAs in the OSO, which serve as functional antioxidants and anti-inflammatory agents, accounting for its diverse pharmacological properties. Full article

Frequency response analysis (FRA) is recognized as an effective method in power transformer winding fault diagnosis. However, the traditional numerical index methods focus on the overall features of FRA curves, making it difficult to capture subtle deformations in transformer windings. Similarly, existing digital image processing methods rely on a single feature or a simple feature combination without adaptive fusion. These methods ignore differences in the data distributions of features, leading to feature mismatch, the loss of sensitive fault information, and lower diagnostic accuracy. To solve this problem, a novel adaptive multiple-image-feature fusion method for transformer winding fault diagnosis is proposed. First, a multi-dimensional feature space combining image pixel matrix similarity, morphological features, and image texture features is built to decode the difference in fault of FRA images. Second, the multiple kernel learning (MKL) framework is used to dynamically adjust the fusion weights of different kernels to make features compatible and remove redundant information. Finally, comparative and ablation experiments show that the proposed method outperforms the traditional methods in identifying different types and levels of faults. The method achieves over 99% accuracy in fault type identification across SVM, KNN, and RF classifiers. For radial deformation (RD) severity prediction, the accuracy of the proposed model is 93.37% with SVM and 94.85% with KNN, outperforming the full-feature concatenation method. These results confirm the method’s robustness and diagnostic precision. Full article

Background/Objectives: This study aimed to evaluate the femoral rotation angle (FRA) before and after THA using a single approach and to identify its influencing factors through three-dimensional measurements. Methods: This retrospective study analyzed patients undergoing 108 primary unilateral THA via the anterolateral-supine approach (ALSA) from May to October 2023. Patients with hip contractures, femoral deformities, or other specific conditions were excluded for precise FRA measurements. Preoperative and postoperative CT scans were used for measurements of the FRA, anteversion, leg lengthening, and global offset. FRA was defined as the angle between the posterior condylar line and the line connecting the bilateral anterosuperior iliac spines, with external rotation as positive. Multiple linear regression, adjusted for age, sex, body mass index, and stem design, assessed the influence of anteversion change, leg lengthening, global offset change, and soft tissue release on the difference in FRA. Results: The mean FRA changed significantly from −2.8° preoperatively to −11.8° postoperatively (p < 0.001), demonstrating an average internal rotation of 9.0° after THA. Anteversion increased by a mean of 9.0° (p < 0.001), leg length increased by 9.0 mm (p < 0.001), and global offset decreased by 1.7 mm (p < 0.001). Multivariate analysis revealed that anteversion change (β = −0.41, p < 0.001) and global offset change (β = 0.40, p = 0.022) were significantly associated with FRA differences. Leg lengthening and ischiofemoral ligament or conjoint tendon resection were not significant (p = 0.089, p = 0.917, and p = 0.750, respectively). Conclusions: ALSA THA significantly rotates the femur internally, associated with an increase in anteversion and a decrease in global offset. Full article

Rail trespassing remains a persistent safety challenge at the system level in the United States, with a 24% increase in incidents within the last decade (2016–2025). Identifying hotspots proactively is difficult due to limited incident data and strong spatial dependencies within the built environment. This study thus creates a ZIP-code–level geospatial analytics framework to identify current and emerging trespassing hotspots across North Carolina by combining land-use composition, rail exposure metrics, and historical Federal Railroad Administration (FRA) trespassing records. Geospatial layers were integrated within a GIS workflow to derive attributes such as rail miles, grade crossings, population density, and land-use types. Exploratory spatial analysis showed significant clustering of trespassing incidents, with Global Moran’s I indicating positive spatial autocorrelation across multiple neighborhood sizes. Permutation z-scores confirmed non-random hotspot formation along major rail corridors. A k-means clustering method also identified four structural risk environments, and a Composite Risk Index (CRI) was developed from weighted, standardized exposure and land-use variables to quantify latent risk, independent of raw casualty counts. Results indicate that clusters characterized by higher rail infrastructure exposure and mixed land-use environments exhibit the highest CRI values and elevated hotspot probabilities. In contrast, clusters with limited rail infrastructure, including predominantly commercial and rural ZIP codes, show substantially lower risk levels. The findings highlight that trespassing risk is more strongly associated with structural exposure conditions than with isolated historical incident counts. The resulting risk surfaces and hotspots provide an interpretable and scalable framework for statewide safety planning, early hotspot detection, and targeted interventions by transportation agencies. Full article

Accurately extracting deviation features in frequency response curves, which reflect winding deformation states, and selecting appropriate machine learning algorithms are critical for achieving a precise quantitative diagnosis of winding deformation based on frequency response analysis (FRA). To address the existing challenges in transformer winding fault diagnosis, including the absence of a systematic feature evaluation framework for frequency response data and the limited recognition accuracy of machine learning models, a novel hybrid feature selection and diagnostic framework was developed. First, a high-dimensional feature pool comprising 25 numerical indices was extracted from experimental FRA curves. To eliminate feature redundancy and arbitrary selection, a hybrid mechanism integrating maximum-relevance, minimum-redundancy (mRMR) with random forest (RF) was developed to dynamically construct task-specific optimal feature subsets. Furthermore, an inverse-distance-weighted K-nearest neighbors (IKNN) model was introduced to enhance diagnostic sensitivity by accounting for feature-space distance variations. Experimental results obtained from a laboratory winding model demonstrate that the proposed mRMR-RF-IKNN model significantly outperforms traditional and optimized benchmarks across multiple macro-evaluation metrics. This study provides a systematic, intelligent screening mechanism that ensures high-precision identification of both the types and severity of faults in power transformers. Full article

Objectives: To characterize the prenatal phenotypic spectrum, genetic findings, and pregnancy outcomes of fetal renal agenesis (RA), and to clarify the complementary roles of chromosomal microarray analysis (CMA) and whole exome sequencing (WES) in phenotype-stratified prenatal evaluation. Methods: This retrospective study included 203 RA fetuses between March 2017 and November 2025. All cases underwent genome-wide copy number variant (CNV) analysis, and selected cases underwent WES. Detection rates were compared across subgroups by laterality, isolated vs. non-isolated phenotype, fetal sex, and presence of extrarenal anomalies. Pregnancy outcomes and postnatal imaging follow-up were collected when available. A systematic literature review of prenatal genetic testing in RA fetuses was performed. Results: Among 203 fetuses, unilateral RA accounted for 92.6% of cases, and 65.0% were isolated. Chromosomal abnormalities were identified in 15 fetuses (7.4%), including aneuploidies and pathogenic or likely pathogenic (P/LP) CNVs. WES identified P/LP single nucleotide variants in 8 of 127 cases (6.3%), increasing to 8.7% when variants with potential clinical relevance were included. Diagnostic yield of WES was significantly higher in bilateral RA, non-isolated cases, and fetuses with extrarenal anomalies. Postnatal follow-up confirmed RA in most liveborn cases, although additional phenotypes emerged in some children. Literature synthesis identified recurrent CNVs at 16p11.2 and 22q11.21 and frequent involvement of FRAS1, FREM2, GFRA1, and GREB1L. Conclusions: RA shows marked phenotypic and genetic heterogeneity. CMA remains a first-tier prenatal test, while WES provides substantial incremental yield in bilateral, non-isolated, or extrarenal-associated RA. Integrated, phenotype-driven testing with longitudinal follow-up supports improved prognostication and genetic counseling. Full article

Background/Objectives: Epilepsy is characterized by unpredictable seizures and drug resistance, along with rising antimicrobial resistance (AMR), highlighting the urgent need for innovative dual-action therapies. This study aimed to design, develop, and evaluate novel pyrazolone derivatives for a dual antimicrobial and antiepileptic potential. Methods: Novel pyrazolone derivatives were designed, synthesized (using 2,4-dinitrophenylhydrazine/semicarbazide condensation with ethyl acetoacetate), and evaluated through molecular docking against antimicrobial (4URM, 3FYV, 3FRA) and neuronal targets (4COF, 5TP9, 5L1F). The in vitro antimicrobial activity was assessed against Gram-positive (S. aureus) and in vitro Gram-negative (E. coli, P. aeruginosa) strains via agar cup plate assays, while in vivo antiepileptic efficacy was tested in a PTZ-induced seizure model in Swiss albino mice. Results: Compound IIa showed potent dual activity, inhibiting E. coli (9 mm zone at 80 μg/mL) and S. aureus (9.5 mm at 80 μg/mL), alongside a significantly delayed seizure onset in the PTZ-induced mouse model (100% survival rate, 45 sec delayed seizure onset, p < 0.001). Compounds Ia and Id showed selective activity against E. coli (6 mm at 80 μg/mL) and P. aeruginosa (7 mm at 80 μg/mL), respectively. Docking studies revealed that compound IIa has a superior binding affinity (−7.57 kcal/mol for 3FYV) compared to standards, driven by hydrogen bonds (SER X: 49) and hydrophobic interactions (LEU X: 20). Conclusions: This study presents a novel approach by proposing a rationally designed pyrazolone scaffold exhibiting both antimicrobial and antiepileptic activity, which integrates in silico modeling with experimental validation. Compound IIa emerged with preliminary dual biological activities, exhibiting strong antibacterial activity, a superior binding affinity toward both bacterial and neuronal targets, and notable seizure prevention in vivo. These findings show the potential of multifunctional pyrazolone derivatives as a new treatment strategy for addressing drug-resistant infections linked to epilepsy and support further optimization toward clinical development. Full article

The spaceborne full-polarimetric (FP) synthetic aperture radar (SAR) is an advanced sensor for high-resolution Earth observation. However, FP data acquired by such a system are prone to distortions induced by ionospheric Faraday rotation (FR). From the perspective of exploiting these distortions, this enables the estimation of the ionospheric FR angle (FRA), and consequently the total electron content, across most global regions (including the extensive ocean areas) using spaceborne FP SAR measurements. The accuracy of FRA estimation, however, is highly sensitive to noise interference. This study addresses denoising in FRA retrieval based on the Bickel–Bates estimator, with a specific focus on noise reduction methods built upon the adaptive Goldstein filter (AGF) that was originally designed for radar interferometric processing. For the first time, three signal-to-noise ratio (SNR)-based AGFs suitable for FRA estimation are investigated. A key feature of these filters is that their SNRs are all defined using the amplitude of the Bickel–Bates estimator signal rather than the FRA estimates themselves. Accordingly, these AGFs are applied to the estimator signal instead of the estimated FRAs. Two of the three AGFs are developed by adopting the mathematical forms of SNRs and filter parameters consistent with the existing SNR-based AGFs for interferogram. The third AGF is newly proposed by utilizing more general mathematical forms of SNR and filter parameter that differ from the first two. Specifically, its SNR definition aligns with that widely used in image processing, and its filter parameter is derived as a function of the defined SNR plus an additionally introduced adjustable factor. The three SNR-based AGFs tailored for FRA estimation are tested and evaluated against existing AGF variants and classical image denoising methods using three sets of FP SAR Datasets acquired by the L-band ALOS PALSAR sensor, encompassing an ocean-only scene, a plain land–ocean combined scene, and a more complex land–ocean combined scene. Experimental results demonstrate that all three filters can effectively mitigate noise, with the newly proposed AGF achieving the best performance among all denoising methods included in the comparison. Full article

The quality of high-density lipoproteins (HDLs) is characterized by lipid and protein composition, oxidation and glycation extent, and particle size, while the quantity of HDL-C is just the cholesterol amount in HDL. The inverse association between HDL-C and cardiovascular disease (CVD) and hypertension has been well established; however, the U-shaped mortality risk observed from HDL-C underscores that HDL quality and function are equally important. The present cross-sectional study assessed the correlations of serum lipid and glucose profiles, and low-density lipoprotein (LDL) and HDL characteristics, with blood pressure (BP) distribution in ordinary middle-aged Korean participants (n = 50; mean age 47.0 ± 11.7 years; males: n = 25, 49.2.0 ± 11.7 years; females: n = 25, 44.8 ± 11.5 years), with particular focus on HDL quality and its antioxidant capacity. This study observed that serum elevated triglyceride (TG) and glucose levels were directly proportional to elevated systolic BP (SBP) and diastolic BP (DBP), whereas serum total cholesterol (TC), LDL-C, and HDL-C were not correlated with BP. However, HDL-C/TC (%) was negatively associated with SBP (p = 0.036), while TG/HDL-C and glucose/HDL-C ratios were positively associated with both SBP and DBP, suggesting that TG and glucose proportions relative to HDL-C are probable predictors of hypertension. Elevations of TG, oxidation, and glycation in LDL were positively associated with elevations of BP, whereas LDL particle size was negatively correlated with BP. Similarly, elevations of TG and glycation in HDL₂ and HDL₃ were positively correlated with elevations of BP, while the particle size of HDL₂ was negatively correlated with BP. The heightened HDL₂-associated paraoxonase (PON) activity and ferric ion reduction ability (FRA) negatively correlated with LDL oxidation and particle size, whereas elevated HDL₃-associated PON and FRA activities were inversely related to LDL glycation. An enhanced glycation in HDL₂ was negatively correlated with HDL₂-associated PON activity and FRA, while an increase in HDL₂ particle size was only dependent on the associated PON activity but not on FRA. In conclusion, observational outcomes demonstrated that improved HDL quality and functionality (characterized by large particle size, reduced glycation, and higher FRA and PON activities) were inversely correlated with LDL oxidation, glycation, particle shrinkage, and the risk of hypertension. Full article

Transformers are essential power transformation equipment in power systems. Winding deformation is one of the main forms of transformer winding faults, which may cause performance degradation or even overall damage to the equipment. As the commonly used methods for diagnosing winding deformation, frequency response analysis (FRA) has problems such as the reliance on expert experience, insufficient universality for windings of different voltage levels and connection methods, etc. If the equivalent network parameters of the windings are identified based on the frequency response curve, the universality and effectiveness can be fundamentally guaranteed. This paper presents a comprehensive review and classification of domestic and international methods for parameter identification of transformer winding equivalent network based on FRA. It elaborates on the principles of parameter identification, as well as the correlation mechanism between frequency response curves and the equivalent network model of transformer windings. In addition, an evaluation is conducted on the principles, strengths, and key challenges of different algorithmic of parameter identification. Drawing upon existing research cases, practical recommendations are provided for the application of different algorithms. Finally, the challenges currently facing research in transformer winding parameter identification are analyzed, and potential future development trends are discussed. Full article