Search Results (2,767)

Obesity contributes to the development of metabolic disorders such as type 2 diabetes mellitus (T2DM) and metabolic dysfunction-associated steatotic liver disease (MASLD) through sustained low-grade inflammation and mitochondrial dysfunction. In obesity, hypertrophied adipose tissue release high levels of pro-inflammatory cytokines, including TNF-α, IL-6, and IL-1β, and elevates circulating free fatty acids. These changes promote systemic insulin resistance and ectopic lipid deposition. Mitochondrial dysfunction, including reduced oxidative phosphorylation, excess reactive oxygen species (ROS) production, and mitochondrial DNA damage, further stimulate inflammatory pathways such as the NLRP3 inflammasome, creating a feedback loop that worsens metabolic stress. Ultimately, this interaction disrupts energy balance, weakens insulin signaling, and accelerates β-cell dysfunction and hepatic steatosis. In both T2DM and MASLD, oxidative stress, defective mitochondrial quality control, and dysregulated immunometabolic responses are consistently observed pathophysiological features. Interventions aimed at reducing inflammation and restoring mitochondrial function—including lifestyle modification, mitochondria-targeted therapies, inflammasome regulation, and enhancement of mitochondrial biogenesis or mitophagy—may retard disease progression. Full article

In agricultural systems, excessive application of nitrogen fertilizer often leads to low nitrogen use efficiency and environmental pollution. In order to solve this problem, we studied the synergistic effect of biochar and nitrogen fertilizer on pepper yield, quality and rhizosphere soil health. This study was conducted under a temperate continental monsoon climate in Changchun, China. Using ‘Jinfu 803’ pepper (Capsicum annuum L.) as the test material, biochar was prepared from corn straw under oxygen-limited conditions at 500 °C. the comprehensive effects of the combined application of biochar (0, 0.7% soil mass ratio) and nitrogen fertilizer (0, 75, 375, 675 kg/hm² pure nitrogen) on pepper yield, fruit quality, rhizosphere soil physicochemical properties, and microbial community structure were studied. Redundancy analysis (RDA), high-throughput sequencing, and multivariate statistical methods were used to analyze the association patterns between soil environmental factors and microbial functional groups. The results showed that the combined application of biochar and nitrogen fertilizer significantly improved soil porosity (increased by 12.3–28.6%) and nutrient content, increased yield, and improved quality, among which the treatment of 0.7% biochar combined with 375 kg/hm² nitrogen fertilizer (B1N2) had the best effect. Under this treatment, the pepper yield reached 24,854.1 kg/hm², which was 42.35% higher than that of the control (B0N0). Notably, the nitrogen partial factor productivity (PFPN) of the B1N2 treatment (66.3 kg/kg) was significantly higher than that of the corresponding treatment without biochar and was not significantly lower than that of the high-nitrogen B1N3 treatment. The contents of soluble sugar and vitamin C in fruits increased by 51.18% and 39.16%, respectively. Redundancy analysis (RDA) revealed that the bacterial community structure was primarily shaped by soil pH, organic matter, and porosity, while the fungal community was predominantly influenced by alkaline hydrolyzable nitrogen and total nitrogen. Furthermore, the B1N2 treatment specifically enriched key functional microbial taxa, such as Chloroflexi (involved in carbon cycling) and Mortierellomycota (phosphate-solubilizing), which showed significant positive correlations with improved soil properties. In conclusion, B1N2 is the optimal treatment combination as it improves soil physical conditions, increases nutrient content, optimizes microbial community structure, and enhances pepper yield and quality. Full article

The main aim of this study was to analyze the excessive biomass of invasive alien aquatic plants reducing the water quality of a lake which was restored in the past. This study was conducted on Długie Lake (26.8 ha, 17.3 m, Masurian Lake District, northeastern Poland), which was completely degraded by raw wastewater inflow. After the long-term restoration (1987–2003) and recovery of submerged macrophyte meadows, the invasion of Elodea nuttallii—an invasive alien aquatic plant (IAAP)—was observed due to the increasing water temperature in recent years, impairing the functioning, biodiversity, and ecosystem services of this urban lake, as well as causing the deterioration of lake water quality. Therefore, an excessive biomass of E. nuttallii has been removed from the lake since 2022. The analysis of physico-chemical water quality parameters showed that consecutive excessive biomass macrophyte gradual removal (three times during the growing season) helps to limit the excessive growth of E. nuttallii and also removes nutrient loads from the ecosystem. Removing excess aquatic vegetation also helps maintain the lake’s aesthetic and recreational value. Currently, the total phosphorus concentration in lake water did not exceed 0.3 mg P/L and total nitrogen did not exceed 2.0 mg N/L. Chlorophyll a contents oscillated in the range of 5 to 9 µg/L, and Secchi disk visibility exceeded 3 m. Full article

Nitrogen eutrophication represents a significant environmental challenge in Chinese aquatic ecosystems, exacerbated by rapid agricultural intensification, industrial expansion, and urban development. This review consolidates existing knowledge on the drivers and impacts of nitrogen pollution in Chinese aquatic ecosystems, with a focus on environments such as lakes, rivers, and coastal waters. The primary sources of nitrogen enrichment are excessive fertilizer application, livestock manure discharge, industrial emissions, and untreated industrial and municipal wastewater. These inputs have led to severe ecological consequences, including harmful algal blooms, hypoxia, loss of biodiversity, and deteriorating water quality, threatening ecosystem health and human well-being. The review also examines mitigation strategies implemented in China, encompassing regulatory policies such as the “Zero Growth” fertilizer initiative, as well as technological advancements in wastewater treatment and sustainable farming practices. Case studies highlighting successful interventions, such as lake restoration projects and integrated watershed management, demonstrate the potential for effective nitrogen control. However, persistent challenges remain, including uneven policy enforcement, insufficient public awareness, and gaps in scientific understanding of nitrogen cycling dynamics. This review aims to inform future efforts toward achieving sustainable nitrogen management in China by synthesizing current research and identifying key knowledge gaps. Addressing these issues is crucial for safeguarding China’s aquatic ecosystems and promoting global nutrient stewardship. Full article

Impurities in polypropylene random copolymer (PPR) raw materials can seriously affect the performance of the final product, and efficient and accurate impurity detection is crucial to ensure high production quality. In order to solve the problems of high small-target miss rates, weak anti-interference ability, and difficulty in balancing accuracy and speed in existing detection methods used in complex industrial scenarios, this paper proposes an enhanced machine vision detection algorithm based on YOLOv11. Firstly, the FasterLDConv module dynamically adjusts the position of sampling points through linear deformable convolution (LDConv), which improves the feature extraction ability of small-scale targets on complex backgrounds while maintaining lightweight features. The IR-EMA attention mechanism is a novel approach that combines an efficient reverse residual architecture with multi-scale attention. This combination enables the model to jointly capture feature channel dependencies and spatial relationships, thereby enhancing its sensitivity to weak impurity features. Again, a DC-DyHead deformable dynamic detection head is constructed, and deformable convolutions are embedded into the spatial perceptual attention of DyHead to enhance its feature modelling ability for anomalies and occluded impurities. We introduce an enhanced InnerMPDIoU loss function to optimise the bounding box regression strategy. This new method addresses issues related to traditional CIoU losses, including excessive penalties imposed on small targets and a lack of sufficient gradient guidance in situations where there is almost no overlap. The results indicate that the average precision (mAP@0.5) of the improved algorithm on the self-made PPR impurity dataset reached 88.6%, which is 2.3% higher than that of the original YOLOv11n, while precision (P) and recall (R) increased by 2.4% and 2.8%, respectively. This study provides a reliable technical solution for the quality inspection of PPR raw materials and serves as a reference for algorithm optimisation in the field of industrial small-target detection. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) and its progressive form, metabolic dysfunction-associated steatohepatitis (MASH), have become the leading causes of chronic liver disease worldwide, with increasing rates of cirrhosis, hepatocellular carcinoma, and cardiovascular complications. Pathogenesis involves a complex interplay of dietary excess, sedentary lifestyle, insulin resistance, adipose tissue dysfunction, and alterations in the gut microbiome, which collectively lead to hepatocellular stress, inflammation, and fibrogenesis. Despite ongoing advances in pharmacotherapy, lifestyle intervention remains the cornerstone of management. Evidence shows that sustained weight loss of ≥5% reduces hepatic steatosis, ≥7% improves necroinflammation, and ≥10% stabilizes or reverses fibrosis. Dietary strategies, including Mediterranean-style patterns, high-protein approaches, and intermittent fasting, have been shown to be effective in improving insulin sensitivity and reducing intrahepatic triglycerides. Exercise interventions, focusing on both aerobic fitness and resistance training, enhance metabolic flexibility and combat sarcopenia, thereby improving hepatic and systemic outcomes. Equally important are behavioral support, digital health tools, and multidisciplinary approaches that enhance adherence and address barriers such as socioeconomic disparities, limited access, and patient engagement issues. Personalized nutrition plans, integrating physical activity, and ongoing support for behavioral change are essential for long-term disease management. This review synthesizes current evidence on the roles of macronutrients, micronutrients, dietary quality, physical activity, and adjunctive behavioral strategies in managing MASLD. By translating mechanistic insights into practical, evidence-based recommendations, we aim to provide clinicians, dietitians, and exercise professionals with effective frameworks to slow disease progression and improve outcomes across diverse patient populations. Full article

Background. Melioidosis is a severe infection caused by Burkholderia pseudomallei and is endemic in regions with a high prevalence of thalassemia. Patients with thalassemia are thought to be at increased risk due to iron overload, splenectomy, and immune dysfunction. However, the pooled prevalence and mortality outcomes of melioidosis in this population remain unclear. Methods. We conducted a systematic review and meta-analysis in accordance with PRISMA 2020 guidelines (PROSPERO: CRD420251108294). PubMed, Embase, and Scopus were searched from inception to July 2025. Observational studies reporting prevalence or mortality of melioidosis in patients with thalassemia were eligible. Pooled odds ratios (ORs) for mortality were calculated using random-effects models, with subgroup and sensitivity analyses based on age, thalassemia subtype, and study quality. Results. Six retrospective studies including 7529 melioidosis patients, of whom 173 had thalassemia, were analyzed. The prevalence of thalassemia among melioidosis cases ranged from 0.5% to 40.7%. Mortality among thalassemia patients varied from 0% to 100%. Pooled analysis demonstrated no significant excess mortality compared with non-thalassemia controls (OR 0.55, 95% CI 0.16–1.89; I² = 44.9%). Sensitivity analysis restricted to moderate- and high-quality studies showed a significantly lower risk of death (OR 0.23, 95% CI 0.15–0.36; I² = 0%). Subgroup analyses by thalassemia subtype and age revealed no clear effect modification, although power was limited. Conclusions. Despite biological plausibility, thalassemia was not associated with increased melioidosis mortality. These findings suggest that closer clinical monitoring, iron chelation, and comorbidity profiles may influence outcomes. Prospective, well-characterized cohort studies are needed to refine risk stratification and guide management in endemic regions. Full article

Sleep staging is a crucial indicator for assessing sleep quality, which contributes to sleep monitoring and the diagnosis of sleep disorders. Although existing sleep staging methods achieve high classification performance, two major challenges remain: (1) the ability to effectively extract salient features from multi-channel sleep data remains limited; (2) excessive model parameters hinder efficiency improvements. To address these challenges, this work proposes a lightweight multi-channel sleep staging network (LMCSleepNet). LMCSleepNet is composed of four modules. The first module enhances frequency domain features through continuous wavelet transform. The second module extracts time–frequency features using multi-scale convolutions. The third module optimizes ResNet18 with depthwise separable convolutions to reduce parameters. The fourth module improves spatial correlation using the Convolutional Block Attention Module (CBAM). On the public datasets SleepEDF-20, SleepEDF-78, and LMCSleepNet, respectively, LMCSleepNet achieved classification accuracies of 88.2% (κ = 0.84, MF1 = 82.4%) and 84.1% (κ = 0.77, MF1 = 77.7%), while reducing model parameters to 1.49 M. Furthermore, experiments validated the influence of temporal sampling points in wavelet time–frequency maps on sleep classification performance (accuracy, Cohen’s kappa, and macro-average F1-score) and the influence of multi-scale dilated convolution module fusion methods on classification performance. LMCSleepNet is an efficient lightweight model for extracting and integrating multimodal features from multichannel Polysomnography (PSG) data, which facilitates its application in resource-constrained scenarios. Full article

Epidermolysis bullosa (EB) is a group of debilitating, genetic skin disorders characterized by excessive skin fragility, blistering, and ulcerations that cause a cyclical wound healing process. EB presents itself in various subtypes, such as EB simplex (EBS), junctional EB (JEB), dystrophic (DEB), and Kindler Syndrome (KS), which all differ in their genetic cause, severity, and harbor different causes of mortality. Of these variants, JEB and DEB are the most severe, with EBS being the mildest form of the disease and KS presenting in extremely rare cases. The JEB variant tends to cause mortality early on in children less than two years of age due to failure to thrive, sepsis from wound infections, and airway obstruction. In the recessive form of DEB (RDEB), cutaneous squamous cell carcinoma (cSCC) is the major cause of death in patients, with one study reporting a mere 4-year survival after the first EB-cSCC diagnosis. Cutaneous SCCs in the setting of RDEB are particularly concerning because they are often more aggressive and show greater metastatic potential, as compared to ultraviolet-induced SCCs. This review aims to explore the pathophysiology of these EB variants as well as their implications for developing cSCCs. It will also discuss elements of the clinical presentation of such lesions in EB patients and the challenges associated with making a definitive diagnosis. Additionally, we will illuminate various diagnostic techniques, current and future management and treatment strategies for both cSCC and EB, and the importance of early screening and education for patients with EB to maximize patient lifespan and quality of life. Full article

The problems of excessive nitrogen fertilizer application and mismatch between varieties and planting density are common in potato production in the dryland farming areas of Loess Plateau, and it is of great significance to select suitable nitrogen application rates and planting densities for the green and sustainable production of dryland potatoes in this area. In this study, Longshu 16 was selected as the potato variety, and we investigated two nitrogen application rates: 200 kg·hm⁻² (N1), 300 kg·hm⁻² (N2); and three planting densities: 37,500 plants·hm⁻² (D1), 52,500 plants·hm⁻² (D2), 67,500 plants·hm⁻² (D3). The effects of different nitrogen fertilization rates and planting densities on photosynthetic characteristics, leaf carbon and nitrogen metabolism enzyme activities, and yield and quality of potato were measured and analyzed. The results showed that during the tuber swelling stage, the activity of ribose-1,5-diphosphate carboxylase oxygenase (Rubisco) in potato leaves was increased by 9.05%. During the starch accumulation stage, the activity of glutamine synthetase (GS) in potato leaves was increased by 3.02~22.34% in N1D2 treatment compared with other treatments, and the activity of glutamate synthase (GOGAT) was increased by 2.83~7.35% compared with other treatments. During the starch accumulation stage, the activity of ADP-glucose pyrophosphorylase (AGPase) in potato leaves was increased by 7.85~31.17% in N1D2 treatment compared with other treatments. The contents of protein, starch, vitamin C, and calcium in potato tubers in N1D2 treatment were the highest, and the yield was the highest in N1D2 treatment. In conclusion, the recommended nitrogen application rate of 200 kg·hm⁻² and planting density of 52,500 plants·hm⁻² in dry-fed potato production improved the yield and quality of potato by enhancing activities of GAPDH, GS, and AGPase. Full article

Reducing the carbon footprint of the construction sector is a growing priority. This study explores the potential of using submerged arc welding (SAW) slag as a precursor in the development of low-carbon geopolymeric materials for 3D printing. The influence of potassium hydroxide (KOH) molarity, partial replacement of ground granulated blast furnace slag (GGBFS) with SAW slag, and water-to-binder (w/b) ratio was evaluated in terms of fresh and hardened properties. Increasing KOH molarity delayed setting times, with the longest delays at 10 M and 12 M. The highest compressive strength (48.5 MPa at 28 days) was achieved at 8 M; higher molarities led to strength losses due to excessive precursor dissolution and increased porosity. GGBFS replacement increased setting times due to its higher Al₂O₃ and MgO content, which slowed geopolymerization. The optimized formulation, containing 20% SAW slag and activated with 8 M KOH at a w/b ratio of 0.29, exhibited good workability, extrudability, and shape retention. This mixture also performed best in 3D printing trials, strong layer adhesion and no segregation, although minor edge irregularities were observed. These results suggest that SAW slag is a promising sustainable material showing for 3D-printed geopolymers, with further optimization of printing parameters needed to enhance surface quality. Full article

The aim of this work was to systematically evaluate the effects of Lion’s Mane Mushroom powder (LMM, 0–40%) on the physicochemical properties, structural characteristics, and flavor profile of soy protein isolate-based high-moisture meat analogues (HMMAs). Optimal incorporation of 20% LMM significantly enhanced product quality by acting as a secondary phase that inhibited lateral protein aggregation while promoting longitudinal alignment, achieving a peak fibrous degree of 1.54 with dense, ordered fibers confirmed by scanning electron microscopy. Rheological analysis showed that LMM improved viscoelasticity (G′ > G″) through β-glucan; however, excessive addition (≥30%) compromised structural integrity due to insoluble dietary fiber disrupting protein network continuity, concurrently reducing thermal stability as denaturation enthalpy (_ΔH) decreased from 1176.6 to 776.3 J/g. Flavor analysis identified 285 volatile compounds in HMMAs with 20% LMM, including 98 novel compounds, and 101 flavor metabolites were upregulated. The mushroom-characteristic compound 1-octen-3-ol exhibited a marked increase in its Relative Odor Activity Value of 18.04, intensifying mushroom notes. Furthermore, LMM polysaccharides promoted the Maillard reaction, increasing the browning index from 48.77 to 82.07, while β-glucan induced a transition in protein secondary structure from random coil to β-sheet configurations via intramolecular hydrogen bonding. In conclusion, 20% LMM incorporation synergistically improved texture, fibrous structure, and flavor complexity—particularly enhancing mushroom aroma. This research offers valuable insights and a foundation for future research for developing high-quality fungal protein-based meat analogues Full article

Although adding iron salts can improve phosphorus removal in membrane bioreactor (MBR) processes, overdosing iron salts may result in excessive iron concentrations in the effluent and pose risks of surface water contamination. In this study, an optimized iron salt dosing method was proposed to comprehensively investigate its effects on the performance of MBRs and the control of iron leakage. The results showed that batch dosing of solid iron salts (Fe₂(SO₄)₃) into the influent or activated sludge maintained an effluent Fe³⁺ concentration below 1.0 mg/L and a total phosphorus (TP) concentration below 0.30 mg/L. Long-term operation of the MBR (under conditions of HRT = 4.3 h, SRT = 20 d, and MLSS = 12 g/L) showed that batch dosing of solid iron salts led to an increase in the effluent ammonia–nitrogen (NH₃-N) concentration, and the nitrification effect was restored after supplementing the alkalinity. Iron salts increased the TP removal rate by approximately 40% while inhibiting the biological phosphorus removal capacity. The average Fe³⁺ concentration in the membrane effluent (0.23 ± 0.11 mg/L) met China’s Environmental Quality Standard for Surface Water (GB3838-2002). This study demonstrates that batch dosing of solid iron salts effectively controls iron concentration in the MBR effluent while preventing secondary pollution. The mechanisms of the impact of iron salts on MBR performance provide crucial theoretical and technical support for MBR process optimization. Full article

Obesity is a complex, multifactorial disease and a growing global health challenge associated with type 2 diabetes, cardiovascular disorders, cancer, and reduced quality of life. The existing pharmacological therapies are characterized by their limited number and efficacy, and safety concerns further restrict their utilization. This review synthesizes extensive knowledge regarding the role of the endocannabinoid system (ECS) in the pathogenesis of obesity, as well as its potential as a therapeutic target. A thorough evaluation of preclinical and clinical data concerning endocannabinoid ligands, cannabinoid receptors (CB1, CB2), their genetic variants, and pharmacological interventions targeting the ECS was conducted. Literature data suggests that the overactivation of the ECS may play a role in the pathophysiology of excessive food intake, dysregulated energy balance, adiposity, and metabolic disturbances. The pharmacological modulation of ECS components, by means of CB1 receptor antagonists/inverse agonists, CB2 receptor agonists, enzyme inhibitors, and hybrid or allosteric ligands, has demonstrated promising anti-obesity effects in animal models. However, the translation of these findings into clinical practice remains challenging due to safety concerns, particularly neuropsychiatric adverse events. The development of novel strategies, including peripherally restricted compounds, hybrid dual-target agents, dietary modulation of endocannabinoid tone, and non-pharmacological interventions, promises to advance the field of obesity management. Full article

Purpose: To develop and validate a two-stage system for automated quality assessment of shoulder true-AP radiographs by combining joint localization with quality classification. Materials and Methods: From the MURA “SHOULDER” subset, 2956 anteroposterior images were identified; 59 images with negative–positive inversion, excessive metallic implants, extreme exposure, or presumed fluoroscopy were excluded, yielding a class-balanced set of 2800 images (1400 OK/1400 NG). A YOLOX-based detector localized the glenohumeral joint, and classifiers operated on both whole images and detector-centered crops. To enhance interpretability, we integrated Grad-CAM into both whole-image and local classifiers and assessed attention patterns against radiographic criteria. Results: The detector achieved AP@0.5 = 1.00 and a mean Dice similarity coefficient of 0.967. The classifier attained AUC = 0.977 (F1 = 0.943) on a held-out test set. Heat map analyses indicated anatomically focused attention consistent with expert-defined regions, and coverage metrics favored local over whole-image models. Conclusions: The two-stage, XAI-integrated approach provides accurate and interpretable assessment of shoulder true-AP image quality, aligning model attention with radiographic criteria. Full article