Search Results (17,740)

Blood-based biomarkers allow monitoring of an individual’s health status and provide insights into metabolic and inflammatory processes in conditions like obesity, cardiovascular, and liver diseases. However, selecting suitable biomarkers and optimizing analytical assays presents challenges, is time-consuming and laborious. Moreover, knowledge of potential sex differences remains incomplete as research is often carried out in men. This study aims at enabling researchers to make informed choices on the type of biomarkers, analytical assays, and dilutions being used. More specifically, we analyzed plasma concentrations of >90 biomarkers using commonly available ELISA or electrochemiluminescence-based multiplex methods, comparing normal weight (BMI < 25; n = 40) with obese (BMI > 30; n = 40) adult blood donors of comparable age. To help choose optimal biomarker sets, we grouped frequently employed biomarkers into biological categories (e.g., adipokines, acute-phase proteins, complement factors, cytokines, myokines, iron metabolism, vascular inflammation), first comparing normal-weight with obese persons, and thereafter exploratively comparing women and men within each BMI group. Many biomarkers linked to chronic inflammation and dysmetabolism were elevated in persons with obesity, including several adipokines, interleukins, chemokines, acute-phase proteins, complement factors, and oxidized LDL. Further exploration suggests sex disparities in biomarker levels within both normal-weight and obese groups. This comprehensive dataset of biomarkers across diverse biological domains constitutes a reference resource that may provide valuable guidance for researchers in selecting appropriate biomarkers and analytical assays for own studies. Moreover, the dataset highlights the importance of taking possible sex differences into account. Full article

The ecological rice–eel co-culture system is not only beneficial for enhancing productivity and sustainability in agriculture but also plays a crucial role in promoting environmental health. In the present study, based on the long-term positioning trial of the rice–eel co-culture system that began in 2016 and was sampled in 2023, the effects of reduced nitrogen fertilizer application on soil physico-chemical properties and the bacterial community were investigated. Treatments included a conventional regular fertilization treatment (RT), rice–eel co-culture system regular fertilization (IT), and nitrogen-reduction 10%, 30%, and 50% fertilization treatments (IT90, IT70, and IT50). Our research demonstrated the following: (1) Compared to RT, IT significantly increased soil water-stable macroaggregates (R0.25), mean weight diameter (MWD), geometric mean diameter (GMD), and available phosphorus content, with the increases of 15.66%, 25.49%, 36.00%, and 18.42%, respectively. Among the nitrogen-reduction fertilization treatments, IT90 showed the most significant effect. Compared to IT, IT90 significantly increased R0.25, MWD, GMD, and available nitrogen content, with increases of 4.4%, 7.81%, 8.82%, and 28.89%, respectively. (2) Compared to RT, at the phylum level, the diversity of Chloroflexi was significantly increased under IT and IT50, and the diversity of Gemmatimonadota was significantly increased under IT90, IT70, and IT50. The diversity of Acidobacteriota was significantly higher in IT90 and IT70 compared to IT. It was shown that the rice–eel co-culture system and nitrogen fertilizer reduction could effectively improve the degradation capacity of organic matter and promote soil nitrogen cycling. In addition, redundancy analysis (RDA) identified total phosphorus, total nitrogen, and available nitrogen (p = 0.007) as the three most important environmental factors driving changes in the bacterial community. (3) The functional prediction analysis of soil microbiota showed that, compared to RT, the diversity of pathways related to biosynthesis (carbohydrate biosynthesis and cell structure biosynthesis) and metabolism (L-glutamate and L-glutamine biosynthesis) was significantly higher under IT70, IT90, IT, and IT50 (in descending order). However, the diversity of pathways associated with degradation/utilization/assimilation (secondary metabolite degradation and amine and polyamine degradation) was significantly lower under all the rice–eel co-culture treatments. In conclusion, the rice–eel co-culture system improved soil physicochemical properties and the soil microbial environment compared with conventional planting, and the best soil improvement was achieved with 10% less N fertilizer application. Full article

Background/Objectives: The two major subtypes of inflammatory bowel disease (IBD)—Crohn’s disease (CD) and ulcerative colitis (UC)—are known to increase the likelihood of developing colorectal cancer (CRC). While this relationship has been well studied in Western populations, evidence from East Asia remains limited and inconsistent. Using nationwide cohort data, this study explored the potential connection between IBD and CRC in a large Korean population. Methods: We conducted a retrospective cohort study using data from the Korean National Health Insurance Service–National Sample Cohort from 2005 to 2019. A total of 9920 CRC patients were matched 1:4 with 39,680 controls using propensity scores based on age, sex, income, and region. Overlap weighting and multivariable logistic regression were used to evaluate the association between IBD and CRC. Subgroup analyses were conducted to assess effect modification by demographic and clinical factors. Results: IBD markedly increased the likelihood of developing CRC (adjusted odds ratio (aOR) = 1.38; 95% confidence interval (CI): 1.20–1.58; p < 0.001), with the association primarily driven by UC (aOR = 1.52; 95% CI: 1.27–1.83). CD appeared unrelated to heightened CRC risk overall, though a significant association was observed among low-income CD patients (aOR = 1.58; 95% CI: 1.15–2.16). The UC–CRC association persisted across all subgroups, including patients without comorbidities. Conclusions: Our findings support an independent association between IBD—particularly UC—and increased CRC risk in Korea. These results underscore the need for personalized CRC surveillance strategies that account for disease subtype, comorbidity burden, and socioeconomic status, especially in vulnerable subpopulations. Full article

With the global economic restructuring and the consequent population mobility, urban shrinkage has become a common phenomenon. The Qinling–Daba Mountains, a zone with a key ecological function in China, have long experienced population decline and functional degradation. Clarifying the dynamics and influencing factors of urban shrinkage plays a vital role in supporting the sustainable development of the region. This study, using permanent resident population growth rates and nighttime light data, classified cities in the region into four spatial patterns: expansion–growth, intensive growth, expansion–shrinkage, and intensive shrinkage. It further examined the spatial characteristics of shrinkage across four periods (2005–2010, 2010–2015, 2015–2020, and 2020–2022). A Geographically and Temporally Weighted Regression (GTWR) model was applied to examine core influencing factors and their spatiotemporal heterogeneity. The results indicated the following: (1) The dominant pattern of urban shrinkage in the Qinling–Daba Mountains shifted from expansion–growth to expansion–shrinkage, highlighting the paradox of population decline alongside continued spatial expansion. (2) Three critical indicators significantly influenced urban shrinkage: the number of students enrolled in general secondary schools (X₅), the per capita disposable income of urban residents (X₇), and the number of commercial and residential service facilities (X₁₂), with their effects exhibiting significant spatiotemporal heterogeneity. Temporally, X₁₂ was the most influential factor in 2005 and 2010, while in 2015, 2020, and 2022, X₅ and X₇ became the dominant factors. Spatially, X₇ significantly affected both eastern and western areas; X₅’s influence was most pronounced in the west; and X₁₂ had the greatest impact in the east. This study explored the patterns and underlying drivers of urban shrinkage in underdeveloped areas, aiming to inform sustainable development practices in regions facing comparable challenges. Full article

Background: Claustrophobia is defined as the fear of enclosed spaces, and it is a rather common specific phobia. Although the Claustrophobia Questionnaire (CLQ) is a valid questionnaire to measure claustrophobia, there have been no studies validating this tool in Greek. Thus, our aim was to translate and validate the CLQ in Greek. Methods: We applied the forward–backward translation method to translate the English CLQ into Greek. We conducted confirmatory factor analysis (CFA) to examine the two-factor model of the CLQ. We examined the convergent and divergent validity of the Greek CLQ by using the Fear Survey Schedule-III (FSS-III-CL), the NEO Five-Factor Inventory (NEO-FFI-NL-N), and the Spielberger’s State-Trait Anxiety Inventory (STAI). We examined the convergent validity of the Greek CLQ by calculating Pearson’s correlation coefficient between the CLQ scores and scores on FSS-III-CL, NEO-FFI-NL-N, STAI-S (state anxiety), and STAI-T (trait anxiety). We examined the divergent validity of the Greek CLQ using the Fisher r-to-z transformation. To further evaluate the discriminant validity of the CLQ, we calculated the average variance extracted (AVE) score and the Composite Reliability (CR) score. We calculated the intraclass correlation coefficient (ICC) and Cronbach’s alpha to assess the reliability of the Greek CLQ. Results: Our CFA confirmed the two-factor model of the CLQ since all the model fit indices were very good. Standardized regression weights between the 26 items of the CLQ and the two factors ranged from 0.559 to 0.854. The convergent validity of the Greek CLQ was very good since it correlated strongly with the FSS-III-CL and moderately with the NEO-FFI-NL-N and the STAI. Additionally, the Greek CLQ correlated more highly with the FSS-III-CL than with the NEO-FFI-NL-N and the STAI, indicating very good divergent validity. The AVE for the suffocation factor was 0.573, while for the restriction factor, it was 0.543, which are both higher than the acceptable value of 0.50. Moreover, the CR score for the suffocation factor was 0.949, while for the restriction factor, it was 0.954. The reliability of the Greek CLQ was excellent since the ICC in test–retest study was 0.986 and the Cronbach’s alpha was 0.956. Conclusions: The Greek version of the CLQ is a reliable and valid tool to measure levels of claustrophobia among individuals. Full article

Early blight, caused by the pathogen Alternaria solani, is a major fungal disease impacting potato production globally, with reported yield losses of up to 40% in susceptible varieties. As one of the most common diseases affecting potatoes, its incidence has been steadily increasing year after year. This study aimed to elucidate the molecular mechanisms underlying resistance to early blight by comparing gene expression profiles in resistant (B1) and susceptible (D30) potato seedlings. Transcriptome sequencing was conducted at three time points post-infection (3, 7, and 10 dpi) to identify differentially expressed genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) and pathway enrichment analyses were performed to explore resistance-associated pathways and hub genes. Over 11,537 DEGs were identified, with the highest number observed at 10 dpi. Genes such as LOC102603761 and LOC102573998 were significantly differentially expressed across multiple comparisons. In the resistant B1 variety, upregulated genes were enriched in plant–pathogen interaction, MAPK signaling, hormonal signaling, and secondary metabolite biosynthesis pathways, particularly flavonoid biosynthesis, which likely contributes to biochemical defense against A. solani. WGCNA identified 24 distinct modules, with hub transcription factors (e.g., WRKY33, MYB, and NAC) as key regulators of resistance. These findings highlight critical molecular pathways and candidate genes involved in early blight resistance, providing a foundation for further functional studies and breeding strategies to enhance potato resilience. Full article

Background and Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a progressive liver disorder associated with metabolic risk factors such as obesity, type 2 diabetes, and cardiovascular disease. If left untreated, the accumulation of excess hepatic fat can lead to inflammation, fibrosis, cirrhosis, hepatocellular carcinoma, and ultimately liver failure. Capsaicin (CAP), the primary pungent compound in chili peppers, has previously been shown to prevent weight gain in high-fat diet (HFD)-induced obesity models. In this study, we investigated the potential of dietary CAP to prevent HFD-induced MASLD. Methods: C57BL/6 mice were fed an HFD (60% kcal from fat) with or without 0.01% CAP supplementation for 26 weeks. We evaluated CAP’s effects on hepatic fat accumulation, inflammation, and mitochondrial function to determine its role in preventing MASLD. Results: CAP acts as a potent and selective agonist of the transient receptor potential vanilloid 1 (TRPV1) channel. We confirmed TRPV1 expression in the liver and demonstrated that CAP activates hepatic TRPV1, thereby preventing steatosis, improving insulin sensitivity, reducing inflammation, and enhancing fatty acid oxidation. These beneficial effects were observed in wild-type but not in TRPV1 knockout mice. Mechanistically, CAP-induced TRPV1 activation promotes calcium influx and activates AMPK, which leads to SIRT1-dependent upregulation of PPARα and PGC-1α, enhancing mitochondrial biogenesis and lipid metabolism. Conclusions: Our findings suggest that dietary CAP prevents MASLD through TRPV1 activation. TRPV1 signaling represents a promising therapeutic target for the prevention and management of MASLD in individuals with metabolic disorders. Full article

This article presents a comprehensive assessment of mudflow risk in the Talgar River basin through the application of Multi-Criteria Decision Analysis (MCDA) methods and numerical modeling using the Rapid Mass Movement Simulation (RAMMS) environment. The first part of the study involves a spatial assessment of mudflow hazard and susceptibility using GIS technologies and MCDA. The key condition for evaluating mudflow hazard is the identification of factors influencing the formation of mudflows. The susceptibility assessment was based on viewing the area as an object of spatial and functional analysis, enabling determination of its susceptibility to mudflow impacts across geomorphological zones: initiation, transformation, and accumulation. Relevant criteria were selected for analysis, each assigned weights based on expert judgment and the Analytic Hierarchy Process (AHP). The results include maps of potential mudflow hazard and susceptibility, showing areas of hazard occurrence and risk impact zones within the Talgar River basin. According to the mudflow hazard map, more than 50% of the basin area is classified as having a moderate hazard level, while 28.4% is subject to high hazard, and only 1.8% falls under the very high hazard category. The remaining areas are categorized as very low (4.1%) and low (14.7%) hazard zones. In terms of susceptibility to mudflows, 40.1% of the territory is exposed to a high level of susceptibility, 35.6% to a moderate level, and 5.5% to a very high level. The remaining areas are classified as very low (1.8%) and low (15.6%) susceptibility zones. The predictive performance was evaluated through Receiver Operating Characteristic (ROC) curves, and the Area Under the Curve (AUC) value of the mudflow hazard assessment is 0.86, which indicates good adaptability and relatively high accuracy, while the AUC value for assessing the susceptibility of the territory is 0.71, which means that the accuracy of assessing the susceptibility of territories to mudflows is within the acceptable level of model accuracy. To refine the spatial risk assessment, mudflow modeling was conducted under three scenarios of glacial-moraine lake outburst using the RAMMS model. For each scenario, key flow parameters—height and velocity—were identified, forming the basis for classification of zones by impact intensity. The integration of MCDA and RAMMS results produced a final mudflow risk map reflecting both the likelihood of occurrence and the extent of potential damage. The presented approach demonstrates the effectiveness of combining GIS analysis, MCDA, and physically-based modeling for comprehensive natural hazard assessment and can be applied to other mountainous regions with high mudflow activity. Full article

Strengthening climate resilience constitutes a foundational approach through which cities adapt to climate change and mitigate associated environmental risks. However, research on the influence of economic policy environments on climate resilience remains limited. Guided by institutional theory and dynamic capability theory, this study employs a panel dataset comprising 272 Chinese cities at the prefecture level and above, covering the period from 2009 to 2023. It constructs a composite index framework for evaluating the green business environment (GBE) and urban climate resilience (UCR) using the entropy weight method. Employing a two-way fixed-effect regression model, it examined the impact of GBE optimization on UCR empirically and also explored the underlying mechanisms. The results show that improvements in the GBE significantly enhance UCR, with green innovation (GI) in technology functioning as an intermediary mechanism within this relationship. Moreover, climate policy uncertainty (CPU) exerts a moderating effect along this transmission pathway: on the one hand, it amplifies the beneficial effect of the GBE on GI; on the other hand, it hampers the transformation of GI into improved GBEs. The former effect dominates, indicating that optimizing the GBE becomes particularly critical for enhancing UCR under high CPU. To eliminate potential endogenous issues, this paper adopts a two-stage regression model based on the instrumental variable method (2SLS). The above conclusion still holds after undergoing a series of robustness tests. This study reveals the mechanism by which a GBE enhances its growth through GI. By incorporating CPU as a heterogeneous factor, the findings suggest that governments should balance policy incentives with environmental regulations in climate resilience governance. Furthermore, maintaining awareness of the risks stemming from climate policy volatility is of critical importance. By providing a stable and supportive institutional environment, governments can foster steady progress in green innovation and comprehensively improve urban adaptive capacity to climate change. Full article

Anthraquinone acid dyes are widely used in dyeing polyamide due to their good exhaustion and brightness. While ionic interactions primarily govern dye–fiber bonding, the molecular weight (Mw) of these dyes can significantly influence migration, apparent color strength, and fastness behavior. This study offers comparative insight into how the Mw of structurally similar anthraquinone acid dyes impacts their diffusion, fixation, and functional outcomes (e.g., UV protection) on polyamide 6 fabric, using Acid Blue 260 (Mw~564) and Acid Blue 127:1 (Mw~845) as representative low- and high-Mw dyes. The effects of dye concentration, pH, and temperature on color strength (K/S) were evaluated, migration index and zeta potential were measured, and UV protection factor (UPF) and FTIR analyses were used to assess fabric functionality. Results showed that the lower-Mw dye exhibited higher migration tendency, particularly at increased dye concentrations, while the higher-Mw dye demonstrated greater color strength and superior wash fastness. Additionally, improved UPF ratings were associated with higher-Mw dye due to enhanced light absorption. These findings offer practical insights for optimizing acid dye selection in polyamide coloration to balance color performance and functional attributes. Full article

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

The problem of choosing an electric generator in order to increase the reliability and continuity of energy supply to households in Ukraine was considered. It was shown that this choice is made under conditions of uncertainty. The methods of choosing alternatives to technical systems under conditions of uncertainty, based on axiomatic, heuristic and verbal decision-making methods described in the sources, were analyzed, and the Analytical Hierarchical Process (AHP) was selected to develop a model for choosing an electric generator. The technical, economic, operational and ergonomic criteria for choosing an electric generator were justified. The novelty of the article lies in the use of the developed structural hierarchical model for choosing an electric generator for a household, and the selection of the appropriate generator option for a household was carried out using the AHP. The selected F3001 generator model is characterized by the highest value of the generalized weighting factor due to the impact of estimates based on economic and operational criteria. The use of the cogeneration unit in an agricultural biogas plant was also indicated—as an alternative to household energy supply. Full article

Unsupervised feature selection aims to characterize the cluster structure of original features and select the optimal subset without label guidance. However, existing methods overlook fuzzy information in the data, failing to model cluster structures between data effectively, and rely on squared error for data reconstruction, exacerbating noise impact. Therefore, a robust unsupervised feature selection algorithm based on fuzzy anchor graphs (FWFGFS) is proposed. To address the inaccuracies in neighbor assignments, a fuzzy anchor graph learning mechanism is designed. This mechanism models the association between nodes and clusters using fuzzy membership distributions, effectively capturing potential fuzzy neighborhood relationships between nodes and avoiding rigid assignments to specific clusters. This soft cluster assignment mechanism improves clustering accuracy and the robustness of the graph structure while maintaining low computational costs. Additionally, to mitigate the interference of noise in the feature selection process, an adaptive fuzzy weighting mechanism is presented. This mechanism assigns different weights to features based on their contribution to the error, thereby reducing errors caused by redundant features and noise. Orthogonal tri-factorization is applied to the low-dimensional representation matrix. This guarantees that each center represents only one class of features, resulting in more independent cluster centers. Experimental results on 12 public datasets show that FWFGFS improves the average clustering accuracy by 5.68% to 13.79% compared with the state-of-the-art methods. Full article

Background and Clinical Significance: The term “boomerang sign” refers to a boomerang-shaped area of cytotoxic edema in the splenium of the corpus callosum. It is seen as hyperintense lesions on T2-weighted images, FLAIR and DWI in MRI. No specific pathomechanism leading to these changes in the splenium have been yet found; however, authors have listed a variety of potential causes. Case Presentation: The case presents a 38-year-old male patient after left cerebellopontine angle tumor resection with an abnormal, increased signal intensity within the corpus callosum (boomerang sign) in FLAIR MRI sequence. In the case of our patient, unlike the patients described in the literature, the changes in the commissure persist. Conclusions: These lesions could be caused by several factors such as the development of cerebellar edema and subarachnoid bleeding or hypertonic salt usage while in the intensive care unit. Full article

This study investigated pesticide residues in 580 vegetable samples collected from markets in Serbia, encompassing potatoes, carrots, celery, radishes, horseradish, ginger, onions, and leeks. In total, 33 distinct pesticides were detected using validated HPLC-MS/MS and GC-MS/MS analytical methods. Multiple residues were identified in 19 samples, while 29 samples exceeded established maximum residue levels (MRLs). Acute and chronic dietary risks were assessed for both adults and children. Although individual hazard quotients (HQs) for adults and children remained below the threshold of concern (HQ < 1), the cumulative acute risk reached up to 63.1% of the Acute Reference Dose (ARfD) for children and 51.1% ARfD for adults, with ginger and celery posing the highest risks. Similarly, cumulative chronic risks remained below the safety threshold, with the Acceptable Daily Intake (ADI) percentages reaching a maximum of 5.9% ADI for adults and increased vulnerability of 11.0% ADI among children. Monte Carlo simulations were applied to account for variability and uncertainty in chronic exposure estimates. The hazard index (HI) results showed that adverse health effects for both population groups remained within acceptable safety limits (HI < 1), although higher susceptibility was observed in children. Sensitivity analysis identified body weight and vegetable consumption rates as the most influential factors affecting chronic risk variability. Full article