Search Results (202,728)

Background: The development of greener synthetic routes to active pharmaceutical ingredients (APIs) is a key challenge in sustainable chemistry. Methods: In this work, we explored the use of deep eutectic solvents (DESs) in the multi-step synthesis of a fluoroquinolone following the Grohe method. Results: Several steps of the synthetic sequence were successfully carried out using DESs, achieving moderate to good yields, while operating under mild reaction conditions and reducing purification requirements. Overall, the use of DESs led to an overall yield of up to 43%. A comprehensive greenness assessment, combining EcoScale scoring and the GSK and CHEM21 solvent selection guides, confirmed the superior sustainability profile of DESs, reflecting their lower toxicity, biodegradability, and reduced energy demands. Conclusions: These findings establish DESs as promising, eco-friendly alternatives to volatile and hazardous organic solvents for the synthesis of quinolone derivatives, offering a valuable step toward more sustainable pharmaceutical manufacturing. Full article

The non-destructive and chemical-free determination of anthocyanin content in single maize kernels is of great importance for plant-breeding programs. Previous studies have mainly relied on Near-Infrared Reflectance (NIR) spectroscopy and color-based approaches, often using conventional or randomly selected modeling techniques. In this study, an Automated Machine Learning (AutoML) framework was employed to predict anthocyanin content using spectral and digital image data obtained from individual maize kernels measured in two orientations (embryo-up and embryo-down). Forty colored maize genotypes representing diverse phenotypic characteristics were analyzed. Digital images were acquired in RGB, HSV, and LAB color spaces, together with NIR spectral data, from a total of 200 kernels. Reference anthocyanin content was determined using a colorimetric method. Ten datasets were constructed by combining different color space and spectral features and were grouped according to kernel orientation. AutoML was used to evaluate nine machine learning algorithms, while Partial Least Squares Regression (PLSR) served as a classical benchmark method, resulting in the development of 1918 predictive models. Kernel orientation had a notable effect on model performance and outlier detection. The best predictions were obtained from the RGB dataset for embryo-up kernels and from the combined RGB+HSV+LAB+NIR dataset for embryo-down kernels. Overall, AutoML outperformed conventional modeling by automatically identifying optimal algorithms for specific data structures, demonstrating its potential as an efficient screening tool for anthocyanin content at the single-kernel level. Full article

This study provides a detailed comparative analysis of a three-hybrid intrusion detection method aimed at strengthening network security through precise and adaptive threat identification. The proposed framework integrates an Autoencoder-Gaussian Mixture Model (AE-GMM) with two supervised learning techniques, XGBoost and Logistic Regression, combining deep feature extraction with interpretability and stable generalization. Although the downstream classifiers are trained in a supervised manner, the hybrid intrusion detection nature of the framework is preserved through unsupervised representation learning and probabilistic modeling in the AE-GMM stage. Two benchmark datasets were used for evaluation: NSL-KDD, representing traditional network behavior, and UNSW-NB15, reflecting modern and diverse traffic patterns. A consistent preprocessing pipeline was applied, including normalization, feature selection, and dimensionality reduction, to ensure fair comparison and efficient training. The experimental findings show that hybridizing deep learning with gradient-boosted and linear classifiers markedly enhances detection performance and resilience. The AE–GMM-XGBoost model achieved superior outcomes, reaching an F1-score above 0.94 ± 0.0021 and an AUC greater than 0.97 on both datasets, demonstrating high accuracy in distinguishing legitimate and malicious traffic. AE-GMM-Logistic Regression also achieved strong and balanced performance, recording an F1-score exceeding 0.91 ± 0.0020 with stable generalization across test conditions. Conversely, the standalone AE-GMM effectively captured deep latent patterns but exhibited lower recall, indicating limited sensitivity to subtle or emerging attacks. These results collectively confirm that integrating autoencoder-based representation learning with advanced supervised models significantly improves intrusion detection in complex network settings. The proposed framework therefore provides a solid and extensible basis for future research in explainable and federated intrusion detection, supporting the development of adaptive and proactive cybersecurity defenses. Full article

Background: Dengue virus (DENV) is becoming a global public health problem, but the immunogenicity of DENV structural proteins is not fully understood. Methods: We predicted the epitope-based immunogenicity of DENV proteins from four serotypes in silico and evaluated their efficacy in vitro (T-cell proliferation assays) and in vivo (ELISpot, qRT-PCR, and plaque reduction neutralization tests using murine splenocytes). We focused on the envelope protein, which contains envelope domain III. Immunogenic B-cell epitopes were predicted using BepiPred-2.0, and regions that induce T cell-mediated immune responses were analyzed using the immune epitope database (IEDB), which validates peptides presented on HLA class I. Results: Nine-amino-acid peptide candidates were selected based on a score of >0.1. The best peptide candidates were tested in T-cell proliferation assays to confirm the in silico data. Subsequently, BALB/c mice were vaccinated with candidate peptides showing immunity in the proliferation assay, and their splenocytes were analyzed. ELISpot and qRT-PCR data showed that some candidate peptides highly regulated cytokines, including interferon-γ, tumor necrosis factor-α, and interleukin-4. Murine sera were collected after peptide boosting 2 weeks apart. Stimulation of cellular immunity was confirmed for some candidates in plaque reduction neutralization tests. Full article

Background: Developmental dysplasia of the hip (DDH) is a common orthopedic disorder characterized by abnormal development of the hip joint, which can lead to pain, instability, and early-onset osteoarthritis if left untreated. Its etiology is multifactorial, involving both genetic and environmental factors. Methods: This study investigated the association between selected single-nucleotide polymorphisms (SNPs) related to joint and bone development and the occurrence of DDH. It assessed potential copy number variations (CNVs) in key skeletal genes using MLPA. A total of 125 individuals were examined, including 43 patients with DDH and 82 healthy controls. Six SNPs were genotyped using real-time PCR with TaqMan assays: TGFB1 (rs1800470), CX3CR1 (rs3732378, rs3732379), GDF5 (rs143384), COL1A1 (rs113647555), and MMP24 (rs12479765). Allele and genotype distributions were compared between cases and controls, and CNVs in COL1A1, COL2A1, LRP5, DKK1, FZD4, and NDP genes were analyzed using Multiplex Ligation-Dependent Probe Amplification. Results: Among the examined variants, only GDF5 rs143384 showed a nominally significant association with DDH (p = 0.040), with the A allele more common in affected individuals. However, after correcting for multiple testing, this result no longer remained significant. No significant associations were detected for TGFB1, CX3CR1, COL1A1, or MMP24. Although CX3CR1 rs3732378 allele frequencies differed slightly from international reference data, no link to DDH was confirmed. Conclusions: MLPA analysis did not identify pathogenic CNVs in the analyzed loci, which indicates that the studied genes have no association with DDH in the Slovak population. Similarly, SNPs in the studied genes yielded no significant results, apart from rs143384 in GDF5, which requires further investigation to confirm our findings. Full article

Background: Root canal sealers may come into direct contact with periapical tissues, particularly in cases of apical extrusion, potentially influencing periapical healing and treatment outcomes. Cytotoxicity assessment represents a clinically relevant parameter when selecting endodontic sealers. However, evidence derived from in vitro studies remains heterogeneous and challenging to interpret from a clinical perspective. Therefore, the aim of this systematic review was to critically evaluate the in vitro cytotoxicity of all root canal sealers that have been commercially marketed over the years, excluding experimental materials, and to contextualize the findings in relation to clinically relevant experimental conditions. Methods: This systematic review was conducted according to PRISMA guidelines and preregistered on the Open Science Framework. PubMed, Scopus, and the Cochrane Library were searched up to 30 November 2025. In vitro studies evaluating the cytotoxicity of commercially available root canal sealers using validated cell viability or proliferation assays were included. Data extraction focused on sealer composition, setting condition, extraction protocols, exposure parameters, and cytotoxic outcomes. Due to marked methodological heterogeneity, a qualitative synthesis was performed. Results: Ninety-eight in vitro studies were included. All categories of root canal sealers demonstrated some degree of cytotoxicity, particularly when tested in freshly mixed conditions, at higher extract concentrations, or after prolonged exposure. Bioactive and calcium silicate-based sealers generally showed a more favorable cytotoxicity profile compared with conventional materials, especially after complete setting and at diluted concentrations, although cytotoxic effects were reported under specific experimental conditions. Resin-based sealers, including AH Plus, exhibited condition-dependent cytotoxicity, while zinc oxide–eugenol and glass ionomer sealers tended to display higher cytotoxic potential. Conclusions: In vitro cytotoxicity of root canal sealers varies according to material composition and experimental conditions. Bioactive sealers generally exhibit a more favorable biological profile, which may be clinically relevant in situations involving sealer extrusion or prolonged tissue contact. Standardized testing protocols and further translational studies are required to support evidence-based clinical material selection. Full article

Lithium-ion batteries (LIBs) are essential for electric vehicles, consumer electronics, and grid storage, but their rapidly increasing demand is paralleled by growing waste volumes. Current disposal methods remain costly, complex, energy-intensive, and environmentally unsustainable. This pilot study investigates a scalable, low-impact disposal method by incorporating LIB waste into concrete, evaluating both the structural and environmental effects of LIB waste on concrete performance. Several cement–mortar cube specimens were cast and tested under compression using the cement–mortar mix with varying battery waste components, such as black mass and varied metals. All mortar mixes maintained an identical water-to-cement ratio. The compressive strength of the cubes was measured at 3, 7, 14, 21, and 28 days after casting and compared. The mix containing black mass exhibited a 35% reduction in compressive strength on day 28, whereas the mix containing varied metals showed a 55% reduction relative to the control mix without LIB waste. A case study was conducted to evaluate the combined structural and environmental performance of a concrete specimen incorporating LIB waste by estimating the embodied carbon (EC) for each mix and comparing the strength-to-net EC ratio. Selective incorporation of LIB waste into concrete provides a practical, low-carbon upcycling pathway, reducing both embodied carbon and landfill burden while enabling greener, non-structural construction materials. This sustainable approach simultaneously mitigates battery waste and lowers cement-related CO₂ emissions, delivering usable concrete for non-structural and low-strength structural applications. Full article

Background/Objectives: Cerebral angiography is a cornerstone diagnostic and therapeutic procedure for cerebrovascular diseases; however, its potential effects on vascular integrity and cellular homeostasis remain incompletely elucidated. This systematic review aims to comprehensively evaluate endothelial and histopathological alterations induced by cerebral angiographic procedures, with particular emphasis on oxidative stress, inflammation, endothelial dysfunction, and blood–brain barrier disruption. Methods: This systematic review was conducted in accordance with the PRISMA 2020 guidelines. PubMed, Scopus, and Web of Science databases were systematically searched for studies published between 1981 and 2025 using predefined keywords related to cerebral angiography, endothelial injury, oxidative stress, inflammation, and histopathological changes. A total of 1142 records were identified, and 216 duplicates were removed. Following title and abstract screening, 312 full-text articles were assessed for eligibility, of which 112 were excluded due to irrelevance or insufficient endothelial or histopathological data. Ultimately, 200 studies were included in the qualitative synthesis. The literature identification, screening, and selection process are summarized in the manuscript. The review protocol was not prospectively registered. Results: The included studies demonstrated that cerebral angiographic procedures induce endothelial and microvascular alterations through both mechanical and contrast-mediated mechanisms. Iodinated contrast agents were consistently associated with increased reactive oxygen species production, reduced endothelial nitric oxide bioavailability, mitochondrial dysfunction, and activation of pro-inflammatory signaling pathways, including nuclear factor kappa B (NF-κB). Histopathological findings revealed endothelial swelling, vacuolization, apoptosis, microthrombus formation, inflammatory cell infiltration, and disruption of endothelial junctions, leading to increased vascular permeability and blood–brain barrier impairment. Mechanical factors related to catheter manipulation and high-pressure contrast injection further exacerbated endothelial injury by altering shear stress and promoting leukocyte adhesion. The severity of endothelial damage and inflammatory responses was consistently greater in patients with comorbid conditions such as diabetes mellitus, hypertension, and atherosclerotic disease. Conclusions: Cerebral angiography may induce endothelial dysfunction and histopathological vascular injury predominantly through oxidative and inflammatory mechanisms. Optimization of contrast agent selection, refinement of procedural techniques, and implementation of endothelial-protective strategies may mitigate vascular injury and improve procedural safety. Further translational and clinical studies are warranted to identify biomarkers and protective interventions targeting angiography-induced endothelial damage. Full article

Non-Intrusive Load Monitoring is an effective method for disaggregating the power consumption of individual appliances from the aggregate load data of a building. The advent of smart meters, Internet of Things devices, and artificial intelligence technologies has significantly advanced the capabilities of non-intrusive load monitoring. However, challenges such as varying sampling frequencies and measurement sensitivities remain. This paper introduces an innovative model incorporating an Adaptive Multi-Scale Attention Integration Module (AMSAIM) to address these issues. The model leverages deep learning and attention mechanisms to improve the accuracy and real-time performance of non-intrusive load monitoring. Validated on the standard UK-DALE dataset, the model consistently demonstrated superior performance. In seen scenarios, our model achieved average F1-scores approximating 0.94 and notably reduced Mean Absolute Error (MAE) values. For washing machines, it achieved an F1-score of 0.99 and MAE of 41.64, outperforming the next best method’s F1-score by 1 percentage point. In challenging unseen scenarios, the model showcased strong generalization, achieving an F1-score of 0.91 for washing machines and reducing MAE to 7.66. Furthermore, an ablation study rigorously confirmed the necessity of the AMSAIM module, showing that the synergistic integration of the efficient multi-scale attention (EMA) and the selective kernel (SK) adaptive receptive field unit is crucial for enhancing model robustness and generalization. Our results highlight the model’s potential for enhancing energy efficiency and providing actionable insights for energy management across various conditions. Full article

Background/Objectives: Iron-deficiency anemia (IDA) is a common condition in children and is frequently attributed to nutritional causes. However, gastrointestinal (GI) pathology may be present even in the absence of overt GI symptoms. The diagnostic value of endoscopic evaluation in asymptomatic pediatric patients with IDA remains debated. This systematic review aimed to synthesize available evidence on endoscopic and histologic findings in asymptomatic children with IDA and to assess their clinical implications. Methods: A systematic review was conducted in accordance with the PRISMA 2020 guidelines, and the protocol was registered in PROSPERO. MEDLINE (via PubMed) and Scopus were searched for studies involving children and adolescents (0–18 years) with confirmed iron-deficiency anemia and no gastrointestinal symptoms who underwent endoscopic evaluation. Results: Six studies met the inclusion criteria, comprising a total of 455 pediatric patients. Upper GI endoscopy was the most commonly performed procedure. Clinically significant findings were frequently identified, including histologic features consistent with celiac disease, Helicobacter pylori-associated gastritis, and chronic inflammatory gastric changes. Histologic abnormalities were often present despite minimal or absent macroscopic endoscopic findings. The diagnostic yield of endoscopy was particularly high in older children and adolescents and in those with severe or refractory IDA. Conclusions: This systematic review demonstrates that asymptomatic children with IDA may harbor significant GI pathology detectable by endoscopic and histologic evaluation. These findings support the consideration of targeted endoscopic assessments in selected pediatric patients with unexplained or persistent IDA, even in the absence of GI symptoms. Full article

This study investigates the vegetation dynamics and phenotypic differentiation of five triticale (×Triticosecale Wittm.) varieties under the region-specific agroecological conditions of Southern Dobruja, Bulgaria, across two growing seasons (2024–2025), with the aim of evaluating how local climatic variability shapes vegetation index patterns. UAV-based multispectral imaging was employed throughout key phenological stages to obtain reflectance indices, including NDVI, SAVI, EVI2, and NIRI, which served as indicators of canopy development and physiological status. NDVI was used as the primary reference index, and a baseline value (NDVIbase), defined as the mean NDVI across all varieties on a given date, was applied to evaluate relative varietal deviations over time. Multiple linear regression analyses were performed to assess the relationship between NDVI and baseline biometric parameters for each variety, revealing that varieties 22/78 and 20/52 exhibited reflectance dynamics most closely aligned with expected developmental trends in 2025. In addition, the relationship between NDVI and meteorological variables was examined for the variety Kolorit, demonstrating that relative humidity exerted a pronounced influence on index variability. The findings highlight the sensitivity of triticale vegetation indices to both varietal characteristics and short-term climatic fluctuations. Overall, the study provides a methodological framework for integrating UAV-based multispectral data with meteorological information, emphasizing the importance of region-specific, time-resolved monitoring for improving precision agriculture practices, optimizing crop management, and supporting informed variety selection. Full article

The irrational or excessive use of antibiotics causes the emergence of bacterial resistance, making antibiotics less effective or ineffective. As the number of resistant antibiotics increases, it is crucial to develop new strategies and innovative approaches to potentiate the efficacy of existing antibiotics. Prior to this, we discovered that some of the traditional antibiotics produce reactive oxygen species (ROS) under specific light exposure. In this paper, we report a multifunctional polymeric nanoparticle (F8IC NPs-PME) that combines targeted and photodynamic–photothermal therapy (PDT-PTT) in one device. The PME on the surface of F8IC enables the selective binding of F8IC NPs-PME to the surface of Gram-negative bacteria. In addition, PME and F8IC can generate ROS and photothermia under near-infrared light excitation, respectively. The results showed that the sterilization efficiency of F8IC NPs-PME at a concentration of 8 μg/mL was as high as 94.7% against kanamycin-resistant E. coli under 808 nm near-infrared light irradiation (0.8 W/cm², 10 min). This antimicrobial strategy can achieve efficient bacteria killing with a low dosage of antibiotics and opens up a new avenue for fighting bacterial resistance. Full article

Orbea is a morphologically diverse lineage within the subtribe Stapeliinae, yet plastome evolution in Arabian taxa remains insufficiently characterized. This study reports the first complete chloroplast genomes of Orbea sprengeri subsp. commutata and O. wissmannii var. eremastrum and investigates plastome structure, sequence variability, and phylogenetic relationships across tribe Ceropegieae. Chloroplast genomes were assembled, annotated, and compared with 13 published plastomes representing major Ceropegieae lineages. Both Arabian plastomes displayed the typical quadripartite structure and identical gene content of 114 unique genes, including 80 protein-coding genes, 30 transfer RNA genes, and four ribosomal RNA genes. However, O. wissmannii var. eremastrum exhibited pronounced structural divergence, possessing the largest plastome recorded for the tribe (170,054 bp), an 8.9 kb expansion of the inverted repeat regions, and an 8.4 kb inversion spanning the ndhG–ndhF region. Comparative analyses revealed conserved gene order across Ceropegieae but identified six highly variable loci (accD, clpP, ndhF, ycf1, psbM–trnD, and rpl32–trnL) as potential DNA barcodes. Selection pressure analyses indicated strong purifying selection across most genes, with localized adaptive signals in accD, ndhE, ycf1, and ycf2. Phylogenomic reconstruction consistently resolved the two Arabian Orbea taxa as a distinct clade separate from the African O. variegata. This study fills a gap in Ceropegieae plastid genomics and underscores the importance of sequencing additional Orbea species to capture the full extent of genomic variation within this diverse genus. Full article

Atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF) coexist in 40–60% of cases and mutually reinforce each other through adverse electrical, cellular, and functional remodelling. There is considerable overlap in signs and symptoms, and diagnosis may be challenging due to nonspecific clinical presentations and chronic course. AF is clearly linked with worsening morbidity and mortality in HFpEF with higher rates of HF hospitalizations, HF progression, stroke, systemic embolism, and all-cause death. Optimal management of HFpEF-AF patients requires aggressive treatment of comorbidities and risk factor modification. Sodium-glucose cotransporter 2 (SGLT2) inhibitors have demonstrated consistent benefit with respect to HF hospitalizations, symptoms and exercise haemodynamics, and potential to reduce AF burden. Gastric inhibitory polypeptide (GIP)/glucagon-like peptide-1 (GLP-1) agonists, mineralocorticoid receptor antagonists (MRAs), angiotensin receptor-neprilysin inhibitors (ARNIs), and statins may provide benefit in selected phenotypes, though evidence remains heterogeneous. A rhythm control strategy in the early clinical course of HFpEF might be a reasonable strategy to improve symptoms and delay both AF and HFpEF disease progression. Catheter ablation appears to improve exercise haemodynamics and quality of life, and observational data suggest it may reduce mortality and HF hospitalization, though current evidence is inconsistent and not yet definitive. Emerging device-based and molecular therapies could represent promising avenues for future research. Overall, early detection of AF, comprehensive risk-factor modification, and tailored rhythm-control strategies are central to improving outcomes in the HFpEF-AF overlap syndrome. Full article

The Internet of Things (IoT) is increasingly deployed at the edge under resource and environmental constraints, which limits the practicality of traditional intrusion detection systems (IDSs) on IoT hardware. This paper presents two IDS configurations. First, we develop a baseline IDS with fixed hyperparameters, achieving 99.20% accuracy and ~0.002 ms/sample inference latency on a desktop machine; this configuration is suitable for high-performance platforms but is not intended for constrained IoT deployment. Second, we propose a lightweight, edge-oriented IDS that applies ANOVA-based filter feature selection and uses a genetic algorithm (GA) for the bounded hyperparameter tuning of the classifier under stratified cross-validation, enabling efficient execution on Raspberry Pi-class devices. The lightweight IDS achieves 98.95% accuracy with ~4.3 ms/sample end-to-end inference latency on Raspberry Pi while detecting both low-volume and high-volume (DoS/DDoS) attacks. Experiments are conducted in a Raspberry Pi-based real lab using an up-to-date mixed-modal dataset combining system/network telemetry and heterogeneous physical sensors. Overall, the proposed framework demonstrates a practical, hardware-aware, and reproducible way to balance detection performance and edge-level latency using established techniques for real-world IoT IDS deployment. Full article