Search Results (242)

Background/Objectives: Comparative analysis of antimicrobial resistomes in hospital and community wastewater can provide valuable insights into the diversity and distribution of antimicrobial resistance genes (ARGs), contributing to the advancement of the One Health approach. This study aimed to characterize and compare the resistome profiles of wastewater sources from a hospital and community. Methods: Longitudinal metagenomic analysis was conducted on wastewater samples collected from the National Center for Global Health and Medicine (hospital) and a shopping mall (community) in Tokyo, Japan, between December 2019 and September 2023. ARG abundance was quantified using reads per kilobase per million mapped reads (RPKM) values, and comparative analyses were performed to identify the significantly enriched ARGs in the two sources. Results: A total of 46 monthly wastewater samples from the hospital yielded 825 unique ARGs, with a mean RPKM of 2.5 across all detected genes. In contrast, 333 ARGs were identified in the three shopping mall wastewater samples, with a mean RPKM of 2.1. Among the ARGs significantly enriched in the hospital samples, 23, including genes conferring resistance to aminoglycosides (nine groups) and β-lactam antibiotics (eight groups), exhibited significantly high RPKM values. No ARGs were found to be significantly enriched in the community wastewater samples. Conclusions: This study highlights the higher diversity and abundance of ARGs, particularly those conferring resistance to aminoglycosides and β-lactam antibiotics including carbapenems, in hospital wastewater than in community wastewater. These findings underscore the importance of continuous resistome monitoring of hospital wastewater as part of the integrated One Health surveillance strategy. Full article

Understanding complex change scenes is a crucial challenge in remote sensing field. Remote sensing image change captioning (RSICC) task has emerged as a promising approach to translate appeared changes between bi-temporal remote sensing images into textual descriptions, enabling users to make accurate decisions. Current RSICC methods frequently encounter difficulties in consistency for contextual awareness and semantic prior guidance. Therefore, this study explores difference semantic prior guidance network to reason context-rich sentence for capturing appeared vision changes. Specifically, the context-aware difference module is introduced to guarantee the consistency of unchanged/changed context features, strengthening multi-level changed information to improve the ability of semantic change feature representation. Moreover, to effectively mine higher-level cognition ability to reason salient/weak changes, we employ difference comprehending with shallow change information to realize semantic change knowledge learning. In addition, the designed parallel cross refined attention in Transformer decoder can balance vision difference and semantic knowledge for implicit knowledge distilling, enabling fine-grained perception changes of semantic details and reducing pseudochanges. Compared with advanced algorithms on the LEVIR-CC and Dubai-CC datasets, experimental results validate the outstanding performance of the designed model in RSICC tasks. Notably, on the LEVIR-CC dataset, it reaches a CIDEr score of 143.34%, representing a 3.11% improvement over the most competitive SAT-cap. Full article

Background: Hospitals are recognized as point sources of antimicrobials in urban wastewater systems; however, comprehensive evaluations of their discharge profiles have not yet been conducted. Methods: This study presents a multi-site investigation of residual antimicrobial concentrations in effluents from five general hospitals and a commercial facility in the metropolitan area of Japan. Over a 12-week period (December 2023–March 2024), extensive sampling was conducted. Fifteen antimicrobials from multiple classes were quantified using high-throughput analysis. Results: The results revealed consistently higher concentrations in hospital effluents, particularly for levofloxacin, vancomycin, and ampicillin, than in non-clinical sites. Distinct facility-specific and temporal patterns suggest strong links between local prescribing practices and the effluent composition. Some compounds, such as clarithromycin and minocycline, showed dual contributions from both hospital and commercial sources. Conclusions: These findings highlight the need for source-targeted monitoring and antimicrobial pollution control strategies and provide a foundation for expanding surveillance efforts and informing environmental policies related to antimicrobial resistance (AMR). Full article

Traditional road traffic accident analysis has long relied on structured data, making it difficult to integrate high-dimensional heterogeneous information such as remote sensing imagery and leading to an incomplete understanding of accident scene environments. This study proposes a road traffic accident analysis framework based on Multimodal Large Language Models. The approach integrates high-resolution remote sensing imagery with structured accident data through a three-stage progressive training pipeline. Specifically, we fine-tune three open-source vision–language models using Low-Rank Adaptation (LoRA) to sequentially optimize the model’s capabilities in visual environmental description, multi-task accident classification, and Chain-of-Thought (CoT) driven causal reasoning. A multimodal dataset was constructed containing remote sensing image descriptions, accident classification labels, and interpretable reasoning chains. Experimental results show that the fine-tuned model achieved a maximum improvement in the CIDEr score for image description tasks. In the joint classification task of accident severity and duration, the model achieved an accuracy of 71.61% and an F1-score of 0.8473. In the CoT reasoning task, both METEOR and CIDEr scores improved significantly. These results validate the effectiveness of structured reasoning mechanisms in multimodal fusion for transportation applications, providing a feasible path toward interpretable and intelligent analysis for real-world traffic management. Full article

Fermented fruit beverages enriched with probiotic microorganisms are gaining increasing interest due to their potential to combine sensory appeal with functional properties. In this study, apple and pear juices were fermented using Saccharomyces cerevisiae var. boulardii and the reference wine strain S. cerevisiae RV002, followed by sweetening with xylitol, erythritol, or stevia. The aim was to evaluate the fermentative performance of the probiotic yeast, the chemical composition of the resulting beverages, and the influence of sweeteners on the results of sensory evaluation. Both yeast strains efficiently produced ethanol within typical ranges for cider and perry. The highest ethanol concentration was observed in apple juice fermented with S. boulardii (49.01 ± 0.60 g/L), while the lowest occurred in pear juice fermented with S. boulardii (41.28 ± 1.00 g/L). Total phenolic content (TPC) decreased after apple juice fermentation but remained largely unchanged in pear juice. Notably, S. boulardii use resulted in the highest post-fermentation TPC value in pear juice (0.34 ± 0.002 g/L), while the lowest value was obtained in apple juice fermented with RV002 strain (0.27 ± 0.005 g/L). Our findings highlight the potential of S. boulardii for producing novel functional alcoholic beverages. Future work should examine long-term probiotic viability and optimise formulations for commercial application. Full article

This paper presents a new image captioning system which contains facial expression recognition as a way to provide better emotional and contextual comprehension of the captions generated. A combination of affective cues and visual features is made, which enables semantically full and emotionally conscious descriptions. Experiments were carried out on two created datasets, FlickrFace11k and COCOFace15k, with standard benchmarks such as BLEU, METEOR, ROUGE-L, CIDEr, and SPICE to analyze their effectiveness. The suggested model produced better results in all metrics as compared to baselines, like Show-Attend-Tell and Up-Down, remaining consistently better on all the scores. Remarkably, it has reached gains of 2.5 points on CIDEr and 1.0 on SPICE, which means a closer correlation to the prompt captions made by people. A 5-fold cross-validation confirmed the model’s robustness, with minimal standard deviation across folds (<±0.2). Qualitative results further demonstrated its ability to capture fine-grained emotional expressions often missed by conventional models. These findings underscore the model’s potential in affective computing, assistive technologies, and human-centric AI applications. The pipeline is designed for on-prem/edge deployment with lightweight interfaces to IoT middleware (MQTT/OPC UA), enabling smart-factory integration. These characteristics align the method with Industry 4.0 sensor networks and human-centric analytics. Full article

Background/Objectives: Phytotherapy, the use of plant-derived bioactive compounds for therapeutic purposes, has gained increasing attention in dentistry as a natural, well-tolerated, and culturally acceptable adjunct to conventional treatments. In pediatric dentistry, its potential relevance lies in its antimicrobial, anti-inflammatory, and antioxidant properties, which may support oral health, caries prevention, pulp vitality, and gingival health. This narrative review aimed to summarize the current clinical evidence regarding the application of phytotherapeutic agents in pediatric oral care. Methods: A narrative review was conducted according to SANRA guidelines, including clinical studies on plant-based products used for preventive or therapeutic purposes in children and adolescents. Results: Forty-three clinical studies met the inclusion criteria. The most commonly investigated agents included licorice, green tea, cocoa husk, cranberry, pomegranate, Aloe vera, and miswak. These agents demonstrated antimicrobial activity against cariogenic bacteria, reduction in plaque and gingival indices, and favorable healing in pulp therapies. In endodontics, Aloe vera-derived acemannan and Ankaferd Blood Stopper^® showed outcomes comparable to conventional materials, while pomegranate and apple cider vinegar exhibited partial antibacterial effects as irrigants. Conclusions: Phytotherapy shows promise as a complementary approach in pediatric dentistry, contributing to caries prevention, gingivitis control, and pulp healing. However, current evidence remains limited by small sample sizes, short-term follow-ups, and heterogeneity in formulations. Further trials are required to confirm efficacy, ensure safety, and standardize phytotherapeutic applications in pediatric oral care. Full article

Cider fermentation is strongly influenced by yeast metabolism, which determines both fermentation dynamics and aroma complexity. While Saccharomyces species remain the standard choice, increasing attention has been directed toward non-Saccharomyces yeasts such as Hanseniaspora uvarum, known for their high ester formation and positive impact on sensory attributes. In this study, three native H. uvarum strains were compared with Saccharomyces bayanus in cider production. Fermentation kinetics, physicochemical parameters, and volatile and sensory profiles were assessed. All H. uvarum strains depleted sugars effectively, but strain-specific differences were evident: Kr-4 exhibited the highest ethanol (4.92% v/v) and glycerol (2.88 g/L) production, while Kd-13 showed reduced fermentative vigor. GC–MS analysis revealed higher alcohols as the dominant volatiles, with 3-methyl-1-butanol and phenylethyl alcohol most abundant. The highest concentration of phenylethyl alcohol was found in cider fermented with H. uvarum Kd-13. Ester diversity was also strain-dependent, with H. uvarum Kd-13 producing increased levels of monoethyl succinate and ethyl phenylacetate. Sensory evaluation identified ciders produced with H. uvarum Kd-13 and Kr-4 as the most complex, whereas the control sample was perceived to have a lighter body and intensive acidity. These findings highlight significant strain-level variability within H. uvarum, underlining its potential for tailoring cider aroma and sensory quality. Full article

Comprehensive highway scene understanding and robust traffic risk inference are vital for advancing Intelligent Transportation Systems (ITS) and autonomous driving. Traditional approaches often struggle with scalability and generalization, particularly under the complex and dynamic conditions of real-world environments. To address these challenges, we introduce a novel structured prompting and multi-agent collaborative knowledge distillation framework that enables automatic generation of high-quality traffic scene annotations and contextual risk assessments. Our framework orchestrates two large vision–language models (VLMs): GPT-4o and o3-mini, using a structured Chain-of-Thought (CoT) strategy to produce rich, multiperspective outputs. These outputs serve as knowledge-enriched pseudo-annotations for supervised fine-tuning of a much smaller student VLM. The resulting compact 3B-scale model, named VISTA (Vision for Intelligent Scene and Traffic Analysis), is capable of understanding low-resolution traffic videos and generating semantically faithful, risk-aware captions. Despite its significantly reduced parameter count, VISTA achieves strong performance across established captioning metrics (BLEU-4, METEOR, ROUGE-L, and CIDEr) when benchmarked against its teacher models. This demonstrates that effective knowledge distillation and structured role-aware supervision can empower lightweight VLMs to capture complex reasoning capabilities. The compact architecture of VISTA facilitates efficient deployment on edge devices, enabling real-time risk monitoring without requiring extensive infrastructure upgrades. Full article

Fermented beverages are drinks that undergo a fermentation process involving yeasts, bacteria, or other microbial groups, leading to the conversion of natural sugars into alcohol, acids, and gases. Beer, wine, kombucha, kefir, and cider are examples of fermented beverages produced and consumed worldwide, representing a rapidly growing market. However, demands for these products have expanded beyond aspects such as size, shape, and storage conditions. There is an increasing demand for eco-sustainable, fresh products tailored to individuals with dietary restrictions and/or enriched with nutrients and health-promoting compounds. In this context, the market has witnessed a surge in alternative fermented beverages made from nutrient-rich or exotic-flavored raw materials, highlighting their versatility. A noteworthy example is the application of Amazonian fruits, which, despite being primarily consumed fresh by local populations, have been extensively characterized in scientific studies for their abundance of molecules with beneficial effects and their use in products like juices, ice creams, and fermented beverages. Thus, this review aims to explore the nutritional composition and microbiological aspects of different fermented beverages produced from several Amazonian fruits. Full article

The identification of cotton diseases and pests is crucial for maintaining cotton yield and quality. However, conventional manual methods are inefficient and prone to high error rates, limiting their practicality in real-world agricultural scenarios. Furthermore, Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) models are insufficient in generating fine-grained and semantically rich image captions, particularly for complex disease and pest features. To overcome these challenges, we introduce CottonCapT6, a novel multi-task image captioning framework based on the Cross Vision Transformer (CrossViT-18-Dagger-408) and Text-to-Text Transfer Transformer (T5). We also construct a new dataset containing annotated images of seven common cotton diseases and pests to support this work. Experimental results demonstrate that CottonCapT6 achieves a Consensus-based Image Captioning Evaluation (CIDEr) score of 197.2% on the captioning task, demonstrating outstanding performance. Notably, the framework excels in providing more descriptive, coherent, and contextually accurate captions. This approach has strong potential to be deployed in cotton farms in the future, helping pest control personnel and farmers make precise judgments on cotton diseases and pests. However, its generalizability to other crops and environmental conditions remains an area for future exploration. Full article

This study investigates the evolution of the chemical components of kombucha aroma during refrigerated storage. Two preparation methods (MT1 and MT2) were used to produce kombucha from a 1:1 mixture of black and green tea. The bottled beverages were stored at 4 °C for three months, and changes in headspace (HS) volatiles were monitored at different time points using solid-phase microextraction (SPME) and GC-MS. A total of 68 volatile substances were identified, with alcohols, acids, and esters dominating the aroma profile. The study revealed significant changes in flavor composition during cold storage, particularly in the first two weeks, with an increase in the number of esters, acids, ketones and terpenoids, as well as the total amount of esters and alkanols. While some changes contribute to the desirable “cider-like” characteristics, others, like certain volatile acids, aliphatic aldehydes and ketones, are associated with off-flavors. These findings suggest that refrigeration alone is not sufficient to completely inhibit microbial activity in freshly prepared kombucha, highlighting the need for further research to correlate chemical changes with sensory properties to establish optimal organoleptic standards and shelf life. Full article

Background/Objectives: Osteoarthritis (OA) is a progressive joint disease characterized by inflammation, cartilage degradation, and subchondral bone changes, for which effective disease-modifying therapies are lacking. Messenger RNA (mRNA)-based therapeutics offer a versatile approach to modulate joint pathology, but their application to OA remains limited. Methods: We evaluated intra-articular delivery of therapeutic mRNAs using polyplex nanomicelles, a non-inflammatory and minimally invasive carrier system, in a rat model of inflammation-driven OA induced by monosodium iodoacetate (MIA). Results: IL-1 receptor antagonist (IL-1Ra) mRNA reduced synovial inflammation and alleviated pain and swelling. RUNX1 mRNA, a transcription factor critical for chondrogenesis, supported chondrocyte viability, type II collagen expression, and cartilage structure. Under conditions of pronounced inflammation, however, the protective effects of RUNX1 mRNA alone were modest. Notably, combined administration of IL-1Ra and RUNX1 mRNAs produced synergistic therapeutic benefits, with enhanced chondroprotection and preservation of subchondral bone integrity. Conclusions: These findings suggest that while RUNX1 is essential for maintaining cartilage homeostasis, effective control of joint inflammation is required for its therapeutic activity. Dual mRNA therapy delivered by polyplex nanomicelles therefore represents a promising strategy to address the multifactorial pathology of OA. Full article

The aim of this study was to investigate the effects of apple cider vinegar (ACV), various mouthwashes and bleaching on the color and surface roughness of fiber strip-reinforced and unreinforced restorative materials. The materials were resin composite (RC), resin-nanoceramic (RNC), and polymer-infiltrated ceramic network (PICN); the mouthwashes were chlorhexidine with alcohol (CXA), chlorhexidine without alcohol (CX), herbal with alcohol (HRA), and herbal without alcohol (HR). Measurements were performed at T0 (baseline), T1 (1 day), T2 (2.5 days) and T3 (after bleaching). Analysis of variance (ANOVA) and Bonferroni analyses revealed that roughness from T0–T3 was highest for RNC and lowest for PICN. Regarding the solutions, the highest increase was in ACV and lowest in artificial saliva (p < 0.001). At T0–T2, color change (ΔE₀₀) and whiteness index change (ΔWI_D) were highest in CXA and lowest in HR. At T2–T3, ΔE₀₀ was highest in ACV, while ΔWI_D was highest in CXA (p < 0.001). Although the roughness exceeded the bacterial adhesion threshold, the effect of bleaching was not considerable. Color and whiteness changes generally did not exceed the acceptability threshold. Fiber strip position did not affect roughness. However, a strip in the middle layer had higher impact on color and whiteness than the one in the top layer. Full article

Background: Apple cider vinegar (ACV) is a naturally fermented beverage with potential metabolic health benefits; however, its effects on weight loss remain controversial. This systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to assess the effect of ACV on anthropometric measurements in adults. Methods: We performed a systematic search of PubMed, Web of Science, Scopus, and CENTRAL up to March 2025 for randomized controlled trials (RCTs) in adults (≥18 years) evaluating the effects of ACV for ≥4 weeks on body composition parameters. Primary outcomes included changes in body weight, BMI, waist circumference, and other anthropometric measures. Risk of bias was assessed using the Revised Cochrane Risk-of-bias tool. Results: Out of 2961 reports screened, 10 RCTs comprising a total of 789 participants were eligible for inclusion in this meta-analysis. The pooled results using a random-effects model showed that daily ACV intake significantly reduced body weight [SMD: −0.39; 95% CI: −0.63, −0.15; p = 0.001; I² = 62%], BMI [SMD: −0.65; 95% CI: −1.05, −0.26; p = 0.001; I² = 83%], and WC [SMD: −0.34; 95% CI: −0.67, −0.02; p = 0.04; I² = 61%]. However, no significant effects of ACV were observed on the other body composition parameters analyzed. Sensitivity analyses excluding high-risk-of-bias studies confirmed the robustness of ACV’s beneficial effects on body weight and BMI. Subgroup analyses suggested that ACV consumption significantly improved anthropometric parameters when administered for up to 12 weeks, at a dose of 30 mL/day, and in adults who were overweight, obese, or had type 2 diabetes. Conclusions: Overall, this meta-analysis suggests that ACV supplementation may be a promising and accessible adjunctive strategy for short-term weight management in adults with excess body weight or metabolic complications. Full article