Search Results (105,467)

The biological effects of nanoparticles are closely related to their intracellular content and location, both of which are influenced by various factors. This study investigates the effects of surface charge on the uptake, intracellular distribution, and exocytosis of CdSe/ZnS quantum dots (QDs) in Raw264.7 macrophages. Negatively charged 3-mercaptopropanoic acid functionalized QDs (QDs-MPA) show higher cellular uptake than positively charged 2-mercaptoethylamine functionalized QDs (QDs-MEA), and serum enhances the uptake of both types of QDs via protein corona-mediated receptor endocytosis. QDs-MEA primarily enter the cells through clathrin/caveolae-mediated pathways and predominantly accumulate in lysosomes, while QDs-MPA are mainly internalized through clathrin-mediated endocytosis and localize to both lysosomes and mitochondria. Exocytosis of QDs-MPA is faster and more efficient than that of QDs-MEA, though both exhibit limited excretion. In addition to endocytosis and exocytosis, cell division influences intracellular QD content over time. These results reveal the charge-dependent interactions between QDs and macrophages, providing a basis for designing biocompatible nanomaterials. Full article

Knowledge-graph-based recommendation aims to provide personalized recommendation services to users based on their historical interaction information, which is of great significance for shopping transaction rates and other aspects. With the rapid growth of online shopping, the knowledge graph constructed from users’ historical interaction data now incorporates multiattribute information, including timestamps, images, and textual content. The information of multiple modalities is difficult to effectively utilize due to their different representation structures and spaces. The existing methods attempt to utilize the above information through simple embedding representation and aggregation, but ignore targeted representation learning for information with different attributes and learning effective weights for aggregation. In addition, existing methods are not sufficient for effectively modeling temporal information. In this article, we propose MTR, a knowledge graph recommendation framework based on mixture of experts network. To achieve this goal, we use a mixture-of-experts network to learn targeted representations and weights of different product attributes for effective modeling and utilization. In addition, we effectively model the temporal information during the user shopping process. A thorough experimental study on popular benchmarks validates that MTR can achieve competitive results. Full article

Forests are considered one of the most valuable natural areas in metropolitan region landscapes. Considering the sensitivity and ecosystem services provided by trees, the definition of urban forest ecosystems is nowadays based on a comprehensive understanding of the entire urban ecosystem. The effective capturing of particulate matter is one of the ecosystem services provided by urban forests. These ecosystems function as efficient biological filters. Plants accumulate pollutants passively via their leaves. Therefore, another ecosystem service provided by city forests could be the use of tree organs as bioindicators of pollution. This paper aims to estimate differences in trace metal pollution between the wooded urban areas of Vienna and Krakow using leaves of evergreen and deciduous trees as biomonitors. An additional objective of the research was to assess the ability of the applied tree species to act as biomonitors. Plant samples of five species—Norway spruce, Scots pine, European larch, common white birch, and common beech—were collected within both areas, in seven locations: four in the “Wienerwald” Vienna forest (Austria) and three in the “Las Wolski” forest in Krakow (Poland). Concentrations of Cr, Cu, Cd, Pb, and Zn in plant material were determined. Biomonitoring studies with deciduous and coniferous tree leaves showed statistically higher heavy metal contamination in the “Las Wolski” forest compared to the “Wienerwald” forest. Based on the conducted analyses and the literature study, it can be concluded that among the analyzed tree species, only two: European beech and common white birch can be considered potential indicators in environmental studies. These species appear to be suitable bioindicators, as both are widespread in urban woodlands of Central Europe and have shown the highest accumulation levels of trace metals. Full article

The objectives of this study were to prepare whey protein–quercetin–gellan gum conjugates using the pH-shift method and to evaluate the impacts of varying pH values and quercetin concentrations on the interaction mechanisms and functional characteristics of the complexes. Spectroscopic analyses (fluorescence, UV-vis, and FT-IR) revealed that new complexes formed under alkaline conditions. Notably, an increasing quercetin concentration led to a reduction in complex particle size and an increase in the zeta potential value, with these effects being more pronounced under alkaline conditions. The particle size was 425.7 nm, and the zeta potential value was −30.00 mV at a quercetin addition concentration of 15 umol/g protein. Additionally, the complexes formed under alkaline conditions exhibited superior foaming capacity, emulsification properties, and significantly enhanced free radical scavenging activity. The complex’s DPPH and ABTS radical scavenging rates rose by 41.57% and 57.69%, respectively. This study provides theoretical foundations and practical insights for developing protein—polyphenol systems, offering significant implications for the application of quercetin functional foods and supplements in the food science and pharmaceutical industries. Full article

Quasi-solid aqueous zinc batteries (QSAZBs) have wide applications in the energy storage field due to their advantages of high safety, cost-effectiveness, and eco-friendliness. Despite prolific research output in the field of QSAZBs, existing reviews predominantly focus on experimental advancements, with limited synthesis of global research trends, interdisciplinary connections, or knowledge gaps. Herein, we review the research on QSAZBs via bibliometric analysis using the VOSviewer software (version 1.6.20). First, the data from qualitatively evaluated publications on QSAZBs from 2016 and 2024 are integrated. In addition, the annual trends, leading countries/regions and their international collaborations, institutional research and patent distribution, and important keyword cluster analyses in QSAZB research are evaluated. The results reveal that China dominates in terms of publication output (71.16% of total papers), and Singapore exhibits the highest citation impact (103.2 citations/paper). International collaboration networks indicate the central role of China, with strong ties to Singapore, the USA, and Australia. Keyword clustering indicates core research priorities: cathode materials (MnO₂ and V₂O₅), quasi-solid electrolyte optimization (hydrogels and graphene composites), and interfacial stability mechanisms. By mapping global trends and interdisciplinary linkages, this work provides insights to accelerate QSAZBs’ transition from laboratory breakthroughs to grid-scale and wearable applications. Full article

Ozone (O₃) occurs in nature as a chemical compound made of three oxygen atoms. It is an unstable, highly oxidative gas that rapidly decomposes into oxygen. The therapeutic use of O₃ dates back to the beginning of the 20th century and is currently based on the application of low doses, inducing a moderate oxidative stress that stimulates the antioxidant cellular defenses without causing cell damage. Low O₃ doses also induce anti-inflammatory and regenerative effects, and their anticancer potential is under investigation. In addition, the oxidative properties of O₃ make it an excellent antibacterial, antimycotic, and antiviral agent. Thanks to these properties, O₃ is currently widely used in several medical fields. However, its chemical instability represents an application limit, and ozonated oil is the only stabilized form of medical O₃. In recent years, novel O₃ formulations have been proposed for their sustained and more efficient administration, based on nanotechnology. This review offers an overview of the nanocarriers designed for the delivery of medical O₃, and of their therapeutic applications. The reviewed articles demonstrate that research is active and productive, though it is a rather new entry in the nanotechnological field. Liposomes, nanobubbles, nanoconstructed hydrogels, polymeric nanoparticles, and niosomes were designed to deliver O₃ and have been proven to exert antiseptic, anticancer, and pro-regenerative effects when administered in vitro and in vivo. Improving the therapeutic administration of O₃ through nanocarriers is a just-started challenge, and multiple prospects may be foreseen. Full article

Next Point-of-Interest (POI) recommendation is aimed at predicting users’ future visits based on their current status and historical check-in records, providing convenience to users and potential profits to businesses. The Graph Neural Network (GNN) has become a common approach for this task due to the capabilities of modeling relations between nodes in a global perspective. However, most existing studies overlook the more prevalent heterogeneous relations in real-world scenarios, and manually constructed graphs may suffer from inaccuracies. To address these limitations, we propose a model called Heterogeneous Graph Structure Learning for Next POI Recommendation (HGSL-POI), which integrates three key components: heterogeneous graph contrastive learning, graph structure learning, and sequence modeling. The model first employs meta-path-based subgraphs and the user–POI interaction graph to obtain initial representations of users and POIs. Based on these representations, it reconstructs the subgraphs through graph structure learning. Finally, based on the embeddings from the reconstructed graphs, sequence modeling incorporating graph neural networks captures users’ sequential preferences to make recommendations. Experimental results on real-world datasets demonstrate the effectiveness of the proposed model. Additional studies confirm its robustness and superior performance across diverse recommendation tasks. Full article

Fault diagnosis is of great significance for the maintenance of rotating machinery. Deep learning is an intelligent diagnostic technique that is receiving increasing attention. To address the issues of industrial data with small samples and varying working conditions, a residual convolutional neural network based on the attention mechanism is put forward for the fault diagnosis of rotating machinery. The method incorporates channel attention and spatial attention simultaneously, implementing channel-wise recalibration for frequency-dependent feature adjustment and performing spatial context aggregation across receptive fields. Subsequently, a residual module is introduced to address the vanishing gradient problem of the model in deep network structures. In addition, LSTM is used to realize spatiotemporal feature fusion. Finally, label smoothing regularization (LSR) is proposed to balance the distributional disparities among labeled samples. The effectiveness of the method is evaluated by its application to the vibration signal data from the safe injection pump and the Case Western Reserve University (CWRU). The results show that the method has superb diagnostic accuracy and strong robustness. Full article

Background/Objectives: This study evaluated the real-world effectiveness of prophylactic Human Papillomavirus (HPV) vaccination in Korean women aged over 26 years, focusing on its impact on persistent HPV infection and disease progression. Methods: This multicenter prospective study analyzed data from the Korea HPV Cohort (2010–2021). After applying exclusion criteria, the final analytical cohort included 1,231 women aged ≥ 27 years with cytologic findings of atypical squamous cells of undetermined significance/low-grade squamous intraepithelial lesions and HPV infection. Propensity score matching was used to compare vaccinated (n = 340) and unvaccinated (n = 891) participants. After matching, 273 vaccinated and 273 unvaccinated individuals were included in the final analysis. The primary outcomes were persistent HPV infection and progression to biopsy-confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+). Logistic and Cox regression models were employed, with additional age-stratified analyses. Results: Among women aged 27–39 years, vaccination was significantly associated with a 54% reduction in the odds of persistent HPV infection (odds ratio = 0.46; 95% CI: 0.22–0.96; p = 0.040). In the full cohort, vaccinated participants had a 62% lower risk of progression to CIN2+ compared with unvaccinated participants (hazard ratio = 0.38; 95% CI: 0.18–0.81; p = 0.011). Body mass index had a notable impact on HPV persistence in HPV 16/18 genotype groups. Conclusions: HPV vaccination effectively reduced persistent infection and progression to CIN2+ in Korean women, particularly those vaccinated before age 40. These findings support the age-extended HPV vaccination policies in South Korea. Full article

Background and Objectives: Multiple sclerosis (MS) is a chronic immune-mediated neurological disorder that primarily affects young adults and is frequently accompanied by psychiatric comorbidities such as depression and anxiety, both of which significantly diminish patients’ quality of life (QoL). This study investigated the effect of two oral disease-modifying therapies (DMTs), fingolimod and cladribine, on mental health and QoL in patients with relapsing-remitting MS (RRMS). The aim of the study was to compare levels of depression, anxiety, and health-related quality of life (HRQoL) in RRMS patients treated with fingolimod or cladribine, and to evaluate their associations with clinical and radiological parameters. Materials and Methods: Eighty RRMS patients aged 18 to 50 years with Expanded Disability Status Scale (EDSS) scores of 3.0 or less, no recent disease relapse, and no history of antidepressant use were enrolled. Forty patients were treated with fingolimod and forty with cladribine. Depression and anxiety were assessed using the Hamilton Depression Rating Scale (HDRS) and the Hamilton Anxiety Rating Scale (HARS). QoL was evaluated using the Multiple Sclerosis QoL-54 (MSQOL-54) instrument. Additional clinical data, including MRI-based lesion burden, EDSS scores, age, disease duration, and occupational status, were collected. Results: No statistically significant differences were observed between the two groups regarding HDRS and HARS scores (p > 0.05). However, patients treated with fingolimod had significantly higher scores in the Energy/Fatigue subdomain (7.55 ± 2.02 vs. 6.56 ± 2.57, p = 0.046) and Composite Mental Health (CMH) score (64.73 ± 15.01 vs. 56.00 ± 18.93, p = 0.029) compared to those treated with cladribine. No significant differences were found in the independent items of the MSQOL-54. A negative correlation was identified between total lesion load and QoL scores. Conclusions: Although fingolimod and cladribine exert comparable effects on depression and anxiety levels, fingolimod may be associated with better mental health outcomes and reduced fatigue in RRMS patients. Furthermore, lesion burden and clinical parameters such as age and EDSS score may independently influence QoL, regardless of the DMT used. Full article

Congenital cataracts (CCs) are a leading cause of preventable childhood blindness, with genetic factors playing a crucial role in their etiology. Nance–Horan syndrome (NHS) is a rare X-linked dominant disorder associated with CCs but is often underdiagnosed due to variable expressivity, particularly in female carriers. Objective: This study aimed to explore the genetic landscape of CCs in a Swiss cohort, focusing on two novel NHS and one novel GJA8 variants and their phenotypic presentation. Methods: Whole-exome sequencing (WES) was conducted on 20 unrelated Swiss families diagnosed with CCs. Variants were analyzed for pathogenicity using genetic databases, and segregation analysis was performed. Clinical data, including cataract phenotype and associated systemic anomalies, were assessed to establish genotype–phenotype correlations. Results: Potentially pathogenic DNA sequence variants were identified in 10 families, including three novel variants, one in GJA8 (c.584T>C) and two NHS variants (c.250_252insA and c.484del). Additional previously reported variants were detected in CRYBA1, CRYGC, CRYAA, MIP, EPHA2, and MAF, reflecting genetic heterogeneity in the cohort. Notably, NHS variants displayed significant phenotypic variability, suggesting dose-dependent effects and X-chromosome inactivation in female carriers. Conclusions: NHS remains underdiagnosed due to its variable expressivity and the late manifestation of systemic features, often leading to misclassification as isolated CC. This study highlights the importance of genetic testing in unexplained CC cases to improve early detection of syndromic forms. The identification of novel NHS and GJA8 variants provides new insights into the genetic complexity of CCs, emphasizing the need for further research on genotype–phenotype correlations. Full article

Monitoring sediment concentration in water bodies is crucial for assessing water quality, ecosystems, and environmental health. However, physical sampling and sensor-based approaches are labor-intensive and unsuitable for large-scale, continuous monitoring. This study employs machine learning models to estimate suspended sediment concentration using images captured in natural light, named RGB, and near-infrared (NIR) conditions. A controlled dataset of approximately 1300 images with SSC values ranging from 1000 mg/L to 150,000 mg/L was developed, incorporating temperature, time of image capture, and solar irradiance as additional features. Random forest regression and gradient boosting regression were trained on mean RGB values, red reflectance, time of captured, and temperature for natural light images, achieving up to 72.96% accuracy within a 30% relative error. In contrast, NIR images leveraged gray-level co-occurrence matrix texture features and temperature, reaching 83.08% accuracy. Comparative analysis showed that ensemble models outperformed deep learning models like Convolutional Neural Networks and Multi-Layer Perceptrons, which struggled with high-dimensional feature extraction. These findings suggest that using machine learning models and RGB and NIR imagery offers a scalable, non-invasive, and cost-effective way of sediment monitoring in support of water quality assessment and environmental management. Full article

Introduction: Oxidative stress is a key factor in the pathogenesis of many chronic diseases, especially in postmenopausal women. Xylitol, a sugar alcohol with potential antioxidant properties, may affect oxidative balance when used as a sugar substitute. Aim: This pilot study aimed to assess the effect of replacing sucrose with xylitol on serum antioxidant capacity in postmenopausal women. Methods: This study included 34 women aged 50 to 65 years who successively consumed 5 g/d, 10 g/d, and 15 g/d of xylitol. The dietary intervention lasted a total of 6 weeks, with each phase covering a 2-week period. Diet was assessed twice based on a 7-day dietary interview (Diet 6.0, NIZP–PZH, Warsaw). The material for this study was venous blood. Antioxidant capacity was determined using the DPPH radical scavenging method and the ABTS cation radical scavenging method. Results: In both methods, a significant increase in serum antioxidant potential was observed after replacing sugar with xylitol (p < 0.0001). An increase in the ability to neutralize free radicals was observed in almost all women studied. Additional analysis of the effect of selected nutrients on the obtained effects of the nutritional intervention showed that the most significant effect could potentially be exerted by manganese, maltose, sucrose, and mercury, and the strongest positive correlation was exerted by vitamin A, retinol, and vitamin E. Although the values obtained in the constructed models were not statistically significant, the large effect indicates potentially significant relationships that could have a significant impact on serum antioxidant potential in the studied group of women. Conclusions: The results suggest a potential role of xylitol in enhancing antioxidant defense mechanisms in menopausal women. Although the sample size was relatively small, this study was powered at approximately 80% to detect large effects, supporting the reliability of the observed results. Nevertheless, given the pilot nature of this study, further research with larger cohorts is warranted to confirm these preliminary observations and to clarify the clinical significance of xylitol supplementation in populations exposed to oxidative stress. Full article

Background/Objectives: This study aimed to investigate the optimal sound presentation level for sound localization testing to assess the effect of hearing interventions in individuals with unilateral conductive hearing loss (UCHL). Methods: Nine participants with normal hearing were tested, and simulated two-stage UCHL was created using earmuffs and earplugs. We created two types of masking conditions: (1) only an earplug inserted, and (2) an earplug inserted with an earmuff worn. A sound localization test was performed for each condition. The sound presentation levels were 40, 45, 50, 55, 60, 65, and 70 dB SPL, and the results were evaluated using root mean square and d-values. Results: Both values showed little difference in masking Condition 2, regardless of the sound presentation level, whereas in masking Condition 1, the values were at their minimum at 55 dB SPL. In addition, comparing the differences between masking Conditions 1 and 2 for each sound presentation level, the greatest difference was observed at 55 dB SPL for both values. Conclusions: The optimal sound presentation level for sound localization testing to assess hearing intervention effects in UCHL was 55 dB. This result may be attributed to the effect of input from the non-masked ear, accounting for interaural attenuation; the effect was considered minimal at 55 dB SPL. Full article

The energetic valorization of digestate obtained from anaerobic digestion (AD) of the organic fraction of municipal solid waste (OFMSW) was investigated via pyrolysis in a bench-scale rotary kiln. The mass rate of dried digestate to the rotary kiln pyrolyzer was fixed at 500 gr/h. The effect of the pyrolysis temperature was investigated at 600, 700, and 800 °C. The pyrolysis products, char, oil, and gas, were quantified and chemically analyzed. It was observed that with the increase in the temperature from 600 to 800 °C, the char decreased from 60.3% to 52.2% and the gas increased from 26.5% to 35.3%. With the aim of increasing the methane production and methane concentration in syngas, the effect of CaO addition to the pyrolysis process was investigated at the same temperature, too. The mass ratio CaO/dried digestate was set at 0.2. The addition of CaO sorbent has a clear effect on the yield and composition of pyrolysis products. Under the experimental conditions, CaO was observed to act both as a CO₂ sorbent and as a catalyst, promoting cracking and reforming reactions of volatile compounds. In more detail, at the investigated temperatures, a net reduction in CO₂ concentration was observed in syngas, accompanied by an increase in CH₄ concentration. The gas yield decreased with the CaO addition because of CO₂ chemisorption. The oil yield decreased as well, probably because of the cracking and reforming effect of the CaO on the volatiles. A very promising performance of the CaO sorbent was observed at 600 °C; at this temperature, the CO₂ concentration decreased from 32.2 to 13.9 mol %, and the methane concentration increased from 16.1 to 29.4 mol %. At the same temperature, the methane production increased from 34 to 63 g/kg_digestate. Full article