Search Results (893)

HIV-1 diversified for decades within the Democratic Republic of the Congo (DRC) before spreading globally in the early 1980s. Thus, the DRC is home to some of the most ancestral and diverse HIV-1 strains. Recent serosurveys conducted from 2017 to 2019 in Kinshasa, DRC, indicated high prevalence of HIV-1, yet sequence data is lacking from this period. Given the history of circulating rare HIV-1 subtypes in the DRC, a viral whole-genome sequencing study was conducted to determine current diversity in the greater Kinshasa area. Next-generation sequencing (NGS) through metagenomic and target enrichment methods was conducted on 197 specimens collected from 2017 to 2019. A large array of HIV subtypes (A, B, C, D, F1, G, H, J, and K), circulating recombinant forms (CRF01_AE, CRF02_AG, CRF05_DF, CRF11_cpx, CRF13_cpx, CRF25_cpx, CRF 45_cpx, and CRF92_C2U), unique recombinant forms, and unclassifiable sequences were observed, with many branching in basal positions within, or outside of, many subtypes on phylogenetic trees. Incorporating these new sequences into Bayesian inference of phylogeny pushes back the dates of the most recent common ancestors of HIV-1 group M and the rare subtypes G, H, and J by between 3 and 7 years each. The DRC continues to harbor diverse and rare HIV-1 subtypes that could challenge diagnostic tests, treatments, and vaccines. In addition to shifting subtype emergence dates, the sequences from our study are evidence that rare strains continue to circulate and should be regularly monitored. Full article

Fascioloides magna, an invasive trematode introduced to Europe in the 19th century, persists in two main foci: the Danube basin and La Mandria Natural Park (LMNP) in northern Italy. This study assessed whether the parasite has spread beyond LMNP and evaluated environmental and host-related risk factors. Between 2012 and 2023, 331 wild ruminant livers were examined, and faecal samples were analysed for fluke eggs. Gastropods from the LMNP were sampled using a predictive habitat suitability model and screened for F. magna DNA. Camera traps monitored ungulate movements across LMNP boundaries. Results confirmed the parasite’s presence in red and fallow deer within LMNP and sporadic cases in roe deer, but no evidence of infection in wildlife or gastropods outside the park. Molecular screening detected F. magna DNA in 9.2%% of snails inside LMNP only. Despite occasional crossings by potential definitive hosts, ecological conditions outside LMNP appear unsuitable for sustaining the parasite’s life cycle. These findings suggest a low current risk of spread but highlight the need for continued surveillance and barrier reinforcement. The integrated approach combining parasitology, molecular diagnostics, and GIS-based risk mapping provides a valuable framework for managing invasive parasitic diseases in wildlife. Full article

The rapid spread of diseases like COVID-19 highlights the need for adaptable monitoring systems to support public health measures such as mask compliance and social distancing. This study presents the CB-OWL-ViT framework: a Cluster-Based Open-World Localization Vision Transformer for mask detection and social distance estimation. It incorporates homography-based distance estimation for effective deployment with monocular cameras. The innovative integration of open-world vision-language detection with a clustering-based strategy enhances mask-wearing assessments, enabling adaptability without retraining. Evaluations on datasets including Kaggle, Roboflow, and a new dataset from the University of Waterloo show that CB-OWL-ViT improves mask detection precision by 0.37 and F1-score by 0.2 compared to the baseline. The homography module achieves a Mean Absolute Error of 0.1116 in distance estimation, and real-world tests demonstrate a recall of 0.98 for detecting noncompliance in the “Without Mask” class. This framework is a practical solution for large-scale disease monitoring across various settings. Full article

Near-field scanning microwave microscopy (NSMM) offers the ability to probe local electromagnetic properties beyond the classical Abbe diffraction limit, but achieving high resolution over practical scan areas remains challenging. In this work, we introduce a novel three-dimensional (3D) NSMM probe consisting of a split-ring resonator (SRR) coupled to a microstrip line and loaded with vertically extended metallic bars. The 3D loading enhances electric-field localization in the sensing region by introducing field singularities. Full-wave numerical simulations are used to extract the field-spread function ($FSF$) of the probe and to quantify how probe geometry, stand-off distance, and bar dimensions control the $FSF$ and its spatial-frequency (k-space) content. An imaging model is then developed in which the NSMM image is represented as a convolution between the object and $FSF$ in one and two dimensions. This framework demonstrates that progressively localized $FSFs$, obtained through 3D loading and resonator miniaturization, systematically improve image fidelity and preserve higher spatial frequencies. The probe is fabricated using printed circuit board technology (PCB) with vertically attached metallic bars, and its performance is validated by imaging a dielectric slab containing a cylindrical air-filled void. The measured line profiles and two-dimensional images are in good agreement in general characteristics with the convolution-based model, confirming that the proposed 3D SRR-based probe operates as a spatial filter whose engineered near-field distribution governs the achievable resolution in NSMM imaging. Full article

Cancer metastasis, the spread of tumour cells from the primary site to distant organs, is responsible for over 90% of cancer deaths, yet effective treatments remain elusive due to incomplete understanding of the molecular drivers involved. Podocalyxin (PODXL), a protein overexpressed in many aggressive cancers, links the cell membrane to the internal skeleton through its interaction with Ezrin, an actin cytoskeleton cross-linker. Despite its therapeutic relevance, the PODXL–Ezrin interface remains structurally uncharacterised and pharmacologically intractable. Here, we employed an integrated computational approach combining protein–protein docking, molecular dynamics (MD) simulations, and virtual screening to investigate the structural basis of the PODXL–Ezrin interaction. Using AlphaFold-predicted structures, we modelled PODXL and Ezrin complexes, revealing that PODXL’s cytoplasmic domain stabilises upon Ezrin binding, with Arg495 mediating temporally distinct electrostatic interactions essential for initial complex assembly. Particularly, we characterised the R495W missense mutation in PODXL’s Ezrin-binding domain, demonstrating that substitution of arginine with bulky, hydrophobic tryptophan may allosterically destabilise Ezrin’s dormant conformation. This mutation slightly increases the intramolecular distance between the F3 subdomain and C-terminal domain from 2.59 Å to 3.40 Å, thus leading to potential partial unmasking of the Thr567 phosphorylation site that could plausibly prime Ezrin for activation. Molecular dynamics simulations in the WT state with a total simulation time of 100 ns revealed enhanced structural rigidity and reduced radius of gyration fluctuations in the mutant complex, consistent with a potential “locked,” activation-prone state that amplifies oncogenic signalling. Through virtual screening, we identified NSC305787 as a selective destabiliser of the R495W mutant complex by disrupting key Trp495–pre-C-terminal loop Ezrin interactions and causing steric hindrance to PIP2 recruitment. Our findings identified mutation-dependent changes in drug binding that can guide the development and repurposing of compounds for targeting PODXL-related cancers and improve patient outcomes in PODXL-altered malignancies. Full article

This study addresses the need for effective bamboo monitoring in smart forestry as UAV imagery and AI-based methods continue to advance. Bambusa stenostachya (thorny bamboo), commonly found in the badland regions of southern Taiwan, spreads rapidly due to its strong reproductive capacity and extensive rhizome system, often causing forestland degradation and challenges to sustainable management. An automated detection approach is therefore required to capture bamboo dynamics and support forest resource assessment. We use a dual-component framework for detecting bamboo forests and individual bamboo clumps from high-resolution UAV orthomosaic imagery. The first component performs semantic segmentation using U-Net or SegFormer to extract bamboo forest areas and generate a corresponding forest mask. The second component independently applies instance segmentation using YOLOv8-Seg and Mask R-CNN to delineate and localize individual bamboo clumps. The dataset was collected from Compartment 43 of the Qishan Working Circle in Kaohsiung, Taiwan. Experimental results show strong model performance: bamboo forest segmentation achieved an F1-score of 0.9569, while bamboo clump instance segmentation reached a precision of 0.8232. These findings demonstrate the promising potential of deep learning-based segmentation techniques for improving bamboo detection and supporting operational forest monitoring. Full article

Droplet impact and spreading on spherical surfaces, often accompanied by heat transfer, are crucial in both industrial and natural settings. This study investigates droplet impact dynamics on a heated spherical surface under gravity at low Weber numbers. A new experimental setup was developed to capture the droplet spreading process, which was combined with a volume-of-fluid-based direct numerical simulation incorporating multiphase heat transfer. This hybrid experimental–numerical approach validated the simulation accuracy and enabled a quantitative analysis of key parameters—including spherical surface temperature, diameter ratio, and Weber number—on droplet spreading behavior. Parametric analyses reveal that an increase in spherical surface temperature slightly enhances the maximum spread coefficient. The maximum spread coefficient grows significantly with the Weber number but remains largely unaffected by the particle-to-droplet size ratio. Furthermore, the total heat flux strongly correlates with the droplet spreading area, reaching a peak at the maximum spread length. Full article

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, threatens global wheat production, with climate change intensifying its spread. This meta-analysis, following PRISMA protocol, evaluated chemical and biological control methods through a systematic review of literature (2005–2025), identifying 12 peer-reviewed studies with 156 experimental comparisons under various conditions. Random effects models assessed treatment impacts on disease severity and grain productivity using standardized mean differences (SMDs). Chemical control significantly reduced stripe rust severity (SMD = −1.04) and improved productivity (SMD = 1.30), with low to moderate variability and consistent yield responses. Effectiveness varied by active ingredients and wheat types, with the greatest benefits in highly susceptible varieties. Biological control agents, particularly Bacillus, Pseudomonas, and Trichoderma species, also reduced disease severity (SMD = −2.19) and increased yield (SMD = 2.39), though with greater heterogeneity reflecting strain-specific and environmental effects. Chemical fungicides provided more predictable disease control, while biological agents offered significant yield increases with agroecological benefits. This meta-analysis demonstrates complementary roles for both approaches, strongly supporting integrated disease management combining plant resistance, optimal fungicide use, and strategic biological control to enhance resilience and sustainability of global cereal production systems. Full article

Background/Objectives: Pseudomonas aeruginosa is one of the leading causes of ventilator-associated pneumonia (VAP) and ventilator-associated tracheobronchitis (VAT), with a worldwide spread of difficult-to-treat high-risk clones. This study aimed to investigate the virulence potential and to characterize phenotypic and genotypic antimicrobial resistance (AMR) in P. aeruginosa causing VAP/VAT in the Intensive Care Unit (ICU), University Hospital of Split, Croatia. Methods: The study included P. aeruginosa isolates obtained from ICU patients who met the criteria for VAP or VAT, between January 2023 and January 2024. Isolates were identified using MALDI-TOF MS and tested for antimicrobial susceptibility (AST). A subset of phenotypically multidrug-resistant (MDR) isolates was further analyzed using whole-genome sequencing (WGS) and multilocus sequence typing. Results: A high rate of resistance was detected to ceftazidime (23.4%), imipenem (39.6%), and meropenem (43.8%). WGS confirmed the presence of multiple AMR genes, including the bla_VIM-2 gene, whose genetic environment highlights a complex MDR locus integrating multiple AMR determinants and mobile genetic elements. All tested isolates possessed genes for class C (bla_PDC34, bla_PDC374 or bla_PDC16) and class D (bla_OXA-2, bla_OXA-10 or bla_OXA-50) β-lactamases, fosA, aph(3′)-IIb and crpP genes. Additionally, WGS analysis revealed the presence of numerous virulence genes including those for adherence (Type IV pili and Fap protein production), motility (such as flgF), biofilm formation (e.g., algE and mucE), quorum sensing (lasI, lasR, rhlI and rhlR), exotoxin (toxA and plcH) and exoenzyme activity (exoU, exoT, exoS, exoY, pcrV, hcp1 and lasA). The isolates belonged to four different sequence types: ST235, ST446, the high-risk ST253 and the widely distributed ST395. Phylogenomic comparison demonstrated that the isolates from this study do not originate from a single clonal source, but instead represent multiple globally distributed high-risk P. aeruginosa lineages introduced into the clinical setting. Conclusions: Due to the emergence of high-risk clones with broad AMR and strong virulence potential, ineffectiveness of standard empirical therapy may be anticipated, highlighting the urgent need for new therapeutic approaches (including those targeting major virulence factors). Full article

Heracleum sosnowskyi is considered to be a dangerous invasive plant species that has successfully naturalized within a variety of plant communities across numerous countries. As a result of its superior competitiveness, the alien species is able to displace the indigenous species from their native habitats, thus changing the ecosystems and decreasing biodiversity. The phytochemicals present in the H. sosnowskyi aqueous extracts were revealed using GC/MS and HPLC/DAD/TOF techniques. Isopsoralen, methoxsalen, (iso)pimpinellin and/or bergapten were determined to be major compounds in the leaf, inflorescence and root extracts. Glutaric, quinic, linolenic, (iso)chlorogenic and other polyphenolic acids were identified in the extracts. Furthermore, a number of furanocoumarins, including hermandiol, bakuchicin, candinols (A and C) and candibirin F, and coumarins, umbelliferone and yunngnins (A and B), were identified in the roots. Additionally, the presence of flavonoids, including astragalin, quercetin 7,3,4-trimethyl ether, nicotiflorin and rutin, has been detected in the flower and leaf extracts. Allelopathic effects of H. sosnowskyi aqueous extracts were tested on four model plants, lettuce (Lactuca sativa L.) and three native Lithuanian meadow herbs, perennial ryegrass (Lolium perenne L.), timothy (Phleum pratense L.) and white clover (Trifolium repens L.), using the Petri dish method. H. sosnowskyi flower and leaf extracts demonstrated the strongest inhibitory effects on the germination and growth of the tested plant seeds. At the highest relative concentrations, 0.5 and 1.0, extracts of Sosnowsky’s hogweed inflorescences inhibited timothy seedling growth by 95.47% (from 19.64 ± 2.57 mm to 0.89 ± 0.73 mm) and 100%, respectively. The leaf extracts exhibited the strongest inhibitory effects on white clover seedlings. The highest relative concentrations tested (0.5 and 1.0) suppressed clover seedling growth by 94.66% (from 41.22 ± 2.53 mm to 2.20 ± 0.63 mm) and 100%, respectively. Additionally, the germination rate and vigor index of model plants were assessed. The research is of significance for the regulation and monitoring of the spreading of aggressive H. sosnowskyi plants. Moreover, it is important for the development of natural herbicides based on active phytotoxic compounds from these plants. Full article

Methicillin-resistant Staphylococcus aureus (MRSA) is a significant pathogen in both healthcare-associated (HA-MRSA) and community-associated (CA-MRSA) infections, posing major challenges due to its evolving antimicrobial resistance (AMR) and genetic diversity. This study investigates the prevalence, antimicrobial resistance patterns, and molecular characteristics of HA-MRSA and CA-MRSA isolates in Saudi Arabia. A retrospective analysis was conducted on 178 MRSA isolates obtained from clinical samples. MRSA identification was performed using cefoxitin disk diffusion, and antimicrobial susceptibility testing for vancomycin, linezolid, and ciprofloxacin was conducted using the BD Phoenix M50 system. Molecular characterization included SCCmec typing, spa typing, and PCR-based detection of virulence genes (pvl, tst, eta, etb, lukS, lukF). Statistical analysis was carried out using SPSS, with a significance threshold of p < 0.05. Among 1496 S. aureus isolates, 178 (11.9%) were confirmed as MRSA, with HA-MRSA (61.8%) being more prevalent than CA-MRSA (38.2%). Notably, 7.8% of HA-MRSA isolates exhibited heteroresistant vancomycin-intermediate S. aureus (hVISA). Ciprofloxacin resistance was significantly higher in HA-MRSA (85.0%) compared to CA-MRSA (38.9%). SCCmec type V was the predominant genotype (87.1%), suggesting increased infiltration of CA-MRSA strains into hospital settings. Spa typing revealed high genetic diversity, with t037 being the most common (27%). Virulence genes were detected in 6% of isolates, indicating limited dissemination of these factors. The findings highlight the increasing prevalence of MRSA, the emergence of hVISA, and shifts in clonal distribution, underscoring the need for ongoing molecular surveillance and stringent antimicrobial stewardship programs to control MRSA spread in both healthcare and community environments. Full article

Background: Pseudomonas aeruginosa is one of the leading agents causing healthcare-associated infections (HAIs) due to its intrinsic resistance, its capacity to acquire resistance mechanisms, and its persistence in hospital environments. In Mexico, it ranks among the most frequently reported pathogens in national surveillance systems. The aim of this study was to characterize antimicrobial resistance profiles and the genetic determinants associated with MDR/XDR phenotypes in P. aeruginosa strains from HAIs at Hospital Juárez de México (HJM). Methods: Sixty-three strains from patients with HAIs were analyzed. Identification was confirmed by 16S rRNA gene sequencing. Antimicrobial susceptibility testing followed CLSI guidelines. MDR/XDR phenotypes were classified according to the Latin American consensus for categorizing MDR, XDR, and PDR pathogens. Screening for resistance mechanisms was carried out by PCR for the main β-lactamases circulating at HJM. Finally, mutations in the oprD gene were detected in imipenem-resistant isolates through amino acid sequence alignment. Results: Resistant phenotypes allowed the identification of MDR and XDR profiles. Only the metallo-β-lactamase bla_VIM was detected. Analysis of oprD porin sequences revealed recurrent mutations (S103T, T115K, L170F, G186P, and T189V) associated with imipenem resistance. Conclusions: In P. aeruginosa, the presence of bla_VIM and structural alterations in OprD confirms the multifactorial nature of carbapenem resistance. These findings underscore the need to strengthen microbiological surveillance programs and antimicrobial stewardship strategies to mitigate the impact and spread of MDR/XDR isolates. Full article

Detecting botnets in IoT environments is difficult because most intrusion detection systems treat network events as independent observations. In practice, infections spread through device relationships and evolve through distinct temporal phases. A system that ignores either aspect will miss important patterns. This paper explores a hybrid architecture combining Graph Neural Networks with Long Short-Term Memory networks to capture both structural and temporal dynamics. The GNN component models behavioral similarity between traffic flows in feature space, while the LSTM tracks how patterns change as attacks progress. The two components are trained jointly so that relational context is preserved during temporal learning. We evaluated the approach on two datasets with different characteristics. N-BaIoT contains traffic from nine devices infected with Mirai and BASHLITE, while CICIoT2023 covers 105 devices across 33 attack types. On N-BaIoT, the model achieved 99.88% accuracy with F1 of 0.9988 and Brier score of 0.0015. Cross-validation on CICIoT2023 yielded 99.73% accuracy with Brier score of 0.0030. The low Brier scores suggest that probability outputs are reasonably well calibrated for risk-based decision making. Consistent performance across both datasets provides some evidence that the architecture generalizes beyond a single benchmark setting. Full article

The dynamic evolution of collective emotions across the news dissemination life-cycle is a powerful yet underexplored signal in affective computing. While phenomena like the spread of fake news depend on eliciting specific emotional trajectories, existing methods often fail to capture these crucial dynamic affective cues. Many approaches focus on static text or propagation topology, limiting their robustness and failing to model the complete emotional life-cycle for applications such as assessing veracity. This paper introduces C-STEER (Cycle-aware Sentiment-Temporal Emotion Evolution), a novel framework grounded in communication theory, designed to model the characteristic initiation, burst, and decay stages of these emotional arcs. Guided by Diffusion of Innovations Theory, C-STEER first segments an information cascade into its life-cycle phases. It then operationalizes insights from Uses and Gratifications Theory and Emotional Contagion Theory to extract stage-specific emotional features and model their temporal dependencies using a Bidirectional Long Short-Term Memory (BiLSTM). To validate the framework’s descriptive and predictive power, we apply it to the challenging domain of fake news detection. Experiments on the Weibo21 and Twitter16 datasets demonstrate that modeling life-cycle emotion dynamics significantly improves detection performance, achieving F1-macro scores of 91.6% and 90.1%, respectively, outperforming state-of-the-art baselines by margins of 1.6% to 2.4%. This work validates the C-STEER framework as an effective approach for the computational modeling of collective emotion life-cycles. Full article

Species of the orders Charadriiformes and Anseriformes serve as the primary long-distance disseminators of various avulaviruses. The most economically significant among them is Newcastle disease virus (NDV), or Avian orthoavulavirus 1 (AOAV-1), which causes diseases of varying severity in both domestic and wild birds. Other avulaviruses have been studied to a much lesser extent, and for most of them, only single isolates are known, which does not allow a comprehensive assessment of their potential threat. To evaluate the biological diversity and potential risks posed by avian paramyxoviruses spread by wild waterfowl during autumn migration, fecal samples from mallards (Anas platyrhynchos) (n = 3604) were collected at water bodies in Moscow and the Moscow Region between 2008 and 2024. From these samples, AOAV-1 (n = 4) and Avian paraavulavirus 4 (APMV-4) (n = 9) were isolated and partially sequenced. Phylogenetic analysis revealed that all AOAV-1 isolates belong to genotype 1 of class II, while all APMV-4 isolates belong to the Eurasian subgenotype of genotype 1. Analysis of the F protein cleavage site motif indicated conformity with the consensus sequences characteristic of lentogenic and non-pathogenic avian paramyxoviruses in all isolates. Full article