Search Results (3,780)

SARS-CoV-2 undergoes frequent mutations that drive viral evolution and genomic diversity, influencing transmissibility, immune escape, and disease severity. In this study, we performed whole-genome sequencing on SARS-CoV-2 isolates from patients in New York City and identified several globally rare mutations across multiple viral lineages. The isolates analyzed for rare mutations belonged to three lineages: B.1.1.7 (Alpha), B.1.526 (Iota), and B.1.623. We identified 16 rare mutations (global incidence <1000) in non-structural protein genes, including nsp2, nsp3, nsp4, nsp6, nsp8, nsp13, nsp14, ORF7a, and ORF8. Three of these mutations—located in nsp2, nsp13, and ORF8—have been reported in fewer than 100 individuals worldwide. We also detected five rare mutations in structural proteins (S, M, and N), including two—one in M and one in N—previously reported in fewer than 100 cases globally. We present clinical profiles of three patients, each infected with genetically distinct viral isolates from the three lineages studied. Furthermore, we illustrate a local transmission chain inferred from unique mutation patterns identified in the Omicron genome. These findings underscore the importance of whole-genome sequencing for detecting rare mutations, tracking community spread, and identifying emerging variants with clinical and public health significance. Full article

Human cutaneous leishmaniasis (CL) caused by Leishmania (Viannia) braziliensis is a complex parasitic disease marked by dynamic host–parasite interactions and immunomodulation. Extracellular vesicles (EV) derived from immune cells have emerged as key mediators of intercellular communication and potential biomarkers in infectious diseases. In this study, we combined a modified lymphocyte proliferation assay with nano-flow cytometry to quantify and phenotype EV released by CD4⁺, CD8⁺, and CD14⁺ cells in PBMC cultures from CL patients at different clinical stages: before treatment (PBT), during treatment (PDT), and post-treatment (PET) with antimonial. Healthy individuals (HI) were included as physiological controls. Upon stimulation with L. (V.) braziliensis antigens, we observed a distinct modulation of EV subsets. In the PBT group, CD4⁺ and CD14⁺ EV were significantly reduced, while CD8⁺ EV remained elevated. During PDT and PET, EV concentrations were restored across all subsets. These findings suggest that L. (V.) braziliensis selectively modulates the release of immune cell–derived EV, possibly as an immune evasion mechanism. The restoration of EV release following antimonial therapy highlights their potential as sensitive biomarkers for disease activity and treatment monitoring. This study offers novel insights into the immunoregulatory roles of EV in CL and underscores their relevance in host–parasite interactions. Full article

Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs. These challenges are compounded by the dynamic nature of vehicular networks and the stringent requirements for real-time data processing and decision-making. Much research is on using novel technologies such as machine learning, blockchain, and cryptography to secure V2X communications. Our survey highlights the security challenges faced by V2X communications and assesses current ML and blockchain-based solutions, revealing significant gaps and opportunities for improvement. Specifically, our survey focuses on studies integrating ML, blockchain, and multi-access edge computing (MEC) for low latency, robust, and dynamic security in V2X networks. Based on our findings, we outline a conceptual framework that synergizes ML, blockchain, and MEC to address some of the identified security challenges. This integrated framework demonstrates the potential for real-time anomaly detection, decentralized data sharing, and enhanced system scalability. The survey concludes by identifying future research directions and outlining the remaining challenges for securing V2X communications in the face of evolving threats. Full article

Background: Cardiac surgery patients with pre- or post-operative atrial fibrillation are at an increased risk for thromboembolic stroke, often due left atrial appendage (LAA) thrombus. Surgical LAA exclusion (LAAE) can be performed and must be complete to avoid increased thrombus formation. Methods: This prospective, multi-center, post-market study (NCT05101993) evaluated the long-term safety and performance of the epicardial V-shape AtriClip device. Patients ≥18 years who had received V-shape AtriClip devices during non-emergent cardiac surgery consented to a prospective 12-month follow-up visit and LAA imaging. The primary performance was LAAE without residual left atrium-LAA communication, assessed by imaging at the last follow-up visit. The primary safety was device- or implant procedure-related serious adverse events (SAEs) (death, major bleeding, surgical site infection, pericardial effusion requiring intervention, myocardial infarction) within 30 days. Results: Of 155 patients from 11 U.S. centers, 151 patients had evaluable imaging. Complete LAAE was obtained in all patients. Primary performance in the intent-to-treat population was met, with 97% (95% CI 93.52%, 99.29%; p = 0.0001) complete LAAE. Primary safety was met, with 100% (95% CI 97.75%, 100%; p < 0.0001) of patients free from pre-defined SAEs within 30 days. One device-related SAE was reported, which resolved intraprocedurally. Conclusions: AtriClip V-Clip showed safe and successful LAAE through 12 months of follow-up. Full article

This paper introduces PyBEP, a Python-based tool for the automated and optimized selection of open-circuit potential (OCP) curves and calculation of stoichiometric cycling ranges for lithium-ion battery electrodes based on open-circuit voltage (OCV) measurements. Thereby, it overcomes key challenges in traditional approaches, which are often time-intensive and susceptible to errors due to manual curve digitization, data inconsistency, and coding complexities. The originality of PyBEP arises from the systematic integration of automated electrode chemistry identification, quality-controlled database usage, refinement of the results using incremental capacity methodology, and simultaneous optimization of multiple electrode parameters. The PyBEP database leverages high-quality, curated OCP data and employs differential evolution optimization for precise OCP determination. Validation against literature data and experimental results confirms the robustness and accuracy of PyBEP, consistently achieving precision of 10 mV or better. PyBEP also offers features like electrode chemical composition identification and quality enhancement of measurement data, further extending the battery modeling functionalities without the need for battery disassembly. PyBEP is open-source and accessible on GitHub, providing a streamlined, accurate resource for the battery research community, making PyBEP a unique and directly applicable toolkit for electrochemical researchers and engineers. Full article

The purpose of this work was to obtain specialized enrichment cultures from an original extreme acidophilic consortium of extremely acidophilic microorganisms and to study their microbial community composition and biotechnological potential. At temperatures of 25, 35, 40 and 50 °C, distinct enrichments of extremely acidophilic microorganisms used in the processes of bioleaching sulfide ores were obtained using nutrient media containing ferrous sulfate, elemental sulfur and a copper sulfide concentrate as nutrient inorganic substrates, with and without the addition of 0.02% yeast extract. The microbial community composition was studied using the sequencing of the V3–V4 hypervariable region of the 16S rRNA genes. The different growth conditions led to changes in the microbial composition and relative abundance of mesophilic and moderately thermophilic, strict autotrophic and mixotrophic microorganisms in members of the genera Acidithiobacillus, Sulfobacillus, Leptospirillum, Acidibacillus, Ferroplasma and Cuniculiplasma. The dynamics of the oxidation of ferrous iron, sulfur, and sulfide minerals (pyrite and chalcopyrite) by the enrichments was also studied in the temperature range of 25 to 50 °C. The study of enrichment cultures using the molecular biological method using the metabarcoding method of variable V3–24 V4 fragments of 16S rRNA genes showed that enrichment cultures obtained under different conditions differed in composition, which can be explained by differences in the physiological properties of the identified microorganisms. Regarding the dynamics of the oxidation of ferrous ions, sulfur, and sulfide minerals (pyrite and chalcopyrite), each enrichment culture was studied at a temperature range of 25 to 50 °C and indicated that all obtained enrichments were capable of oxidizing ferrous iron, sulfur and minerals at different rates. The obtained enrichment cultures may be used in further work to increase bioleaching by using the suitable inoculum for the temperature and process conditions. Full article

The Kuroshio Current’s flow velocity imposes exacting requirements on underwater vehicle propulsive systems. Ecological preservation necessitates low-noise propeller designs to mitigate operational disturbances. As technological evolution advances toward greater intelligence and system integration, intelligent unmanned systems are positioning themselves as a critical frontier in marine innovation. In recent years, the global research community has increased its efforts towards the development of high-maneuverability underwater vehicles. However, propeller design optimization ignores the key balance between acoustic performance and hydrodynamic efficiency, as well as the appropriate speed threshold for blade rotation. In order to solve this problem, the propeller design of the NACA 65A010 airfoil is optimized by using OpenProp v3.3.4 and XFlow 2022 software, aiming at innovating the propulsion system of shallow water agile submersibles. The study presents an integrated design framework combining lattice Boltzmann method (LBM) simulations synergized with fully Lagrangian-LES modeling, implementing rotational speed thresholds to detect cavitation inception, followed by advanced acoustic propagation analysis. Through rigorous comparative assessment of hydrodynamic metrics, we establish an optimization protocol for propeller selection tailored to littoral zone operational demands. Studies have shown that increasing the number of propeller blades can reduce the single-blade load and delay cavitation, but too many blades will aggravate the complexity of the flow field, resulting in reduced efficiency and noise rebound. It is concluded that the propeller with five blades, a diameter of 234 mm, and a speed of 500 RPM exhibits the best performance. Under these conditions, the water efficiency is 69.01%, and the noise is the lowest, which basically realizes the balance between hydrodynamic efficiency and acoustic performance. This paradigm-shifting research carries substantial implications for next-generation marine vehicles, particularly in optimizing operational stealth and energy efficiency through intelligent propulsion architecture. Full article

Microfluidic platforms offer a powerful approach for ultimately replicating vascularization in vitro, enabling precise microscale control and manipulation of physical parameters. Despite these advances, the real-time ability to monitor and quantify mechanical forces—particularly pressure—within microfluidic environments remains constrained by limitations in cost and compatibility across diverse device architectures. Our work presents an advanced experimental module for quantifying pressure within a vascularizing microfluidic platform. Equipped with an integrated Arduino microcontroller and image monitoring, the system facilitates real-time remote monitoring to access temporal pressure and flow dynamics within the device. This setup provides actionable insights into the hemodynamic parameters driving vascularization in vitro. In-line pressure sensors, interfaced through I2C communication, are employed to precisely record inlet and outlet pressures during critical stages of microvasculature tubulogenesis. Flow measurements are obtained by analyzing changes in reservoir volume over time (dV/dt), correlated with the change in pressure over time (dP/dt). This quantitative assessment of various pressure conditions in a microfluidic platform offers insights into their impact on microvasculature perfusion kinetics. Data acquisition can help inform and finetune functional vessel network formation and potentially enhance the durability, stability, and reproducibility of engineered in vitro platforms for organoid vascularization in regenerative medicine. Full article

Tropical sandy beaches are dynamic ecosystems where microbial communities play crucial roles in biogeochemical processes and tracking human impact. Despite their importance, these habitats remain underexplored. Here, using amplicon-based sequencing of bacterial (V3-V4 16S rRNA) and fungal (ITS2) markers, we first describe microbial communities inhabiting supralittoral–intertidal sediments of two contrasting sandy beaches in the Tadjoura Gulf (Djibouti Republic): Sagallou-Kalaf (SK, rural, siliceous sand) and Siesta Plage (SP, urban, calcareous sand). Sand samples were collected at low tide along 10 m transects perpendicular to the shoreline. Bacterial communities differed significantly between sites and along the sea-to-land gradient, suggesting an influence from both anthropogenic activity and sediment granulometry. SK was dominated by Escherichia-Shigella, Staphylococcus, and Bifidobacterium, associated with human and agricultural sources. SP showed higher richness, with enriched marine-associated genera such as Hoeflea, Xanthomarina, and Marinobacter, also linked to hydrocarbon degradation. Fungal diversity was less variable, but showed significant shifts along transects. SK communities were dominated by Kluyveromyces and Candida, while SP hosted a broader fungal assemblage, including Pichia, Rhodotorula, and Aureobasidium. The higher richness at SP suggests that calcium-rich sands, possibly due to their buffering capacity and greater moisture retention, offer more favorable conditions for microbial colonization. Full article

This paper proposes a compact, broadband, and low-profile filtering antenna designed for Sub-6 GHz communication. By applying characteristic mode analysis to the radiating elements, the operational mechanism of the antenna is clearly elucidated. The current cancellation among different radiating elements results in two radiation nulls in the primary radiation direction, effectively enhancing the filtering effect. The antenna achieves a wide operational bandwidth ($S_{11}\le -10$ dB) of 35.9% (4.3–6.4 GHz), making it highly suitable for Sub-6 GHz communication systems. Despite its compact size of 25 × 25 mm², the antenna consistently maintains stable broadside radiation patterns, with a peak gain of 6.14 dBi and a minimal gain fluctuation of less than 1 dBi at 4.6–6.45 GHz. This design ensures reliable and robust communication performance for V2V systems operating in the designated frequency band. Full article

Vermicomposting is a sustainable biotechnological process that transforms organic waste through the synergistic activity of earthworms, such as Eisenia fetida, and their associated microbiota. This study evaluated bacterial and physicochemical dynamics during the vermicomposting of bovine manure by analyzing the microbial composition of the substrate and the gut of E. fetida at three time points (weeks 0, 6, and 12). The V3–V4 region of the 16S rRNA gene was sequenced, and microbial diversity was characterized using QIIME2. Significant differences in alpha diversity (observed features, Shannon index, and phylogenetic diversity) and beta diversity indicated active microbial succession. Proteobacteria, Bacteroidota, and Actinobacteriota were the dominant phyla, with abundances varying across habitats and over time. A significant enrichment of Proteobacteria, Bacteroidota, and the genera Chryseolinea, Flavobacterium, and Sphingomonas was observed in the manure treatments. In contrast, Actinobacteriota, Firmicutes, and the genera Methylobacter, Brevibacillus, Enhygromyxa, and Bacillus, among others, were distinctive of the gut samples and contributed to their dissimilarity from the manure treatments. Simultaneously, the physicochemical parameters indicated progressive substrate stabilization and nutrient enrichment. Notably, the organic matter and total organic carbon contents decreased (from 79.47% to 47.80% and from 46.10% to 27.73%, respectively), whereas the total nitrogen content increased (from 1.70% to 2.23%); these effects reduced the C/N ratio, which is a recognized indicator of maturity, from 27.13 to 12.40. The macronutrient contents also increased, with final values of 1.41% for phosphorus, 1.50% for potassium, 0.89% for magnesium, and 2.81% for calcium. These results demonstrate that vermicomposting modifies microbial communities and enhances substrate quality, supporting its use as a biofertilizer for sustainable agriculture, soil restoration, and agrochemical reduction. Full article

The swift advancements in autonomous vehicle systems have facilitated their implementation across various industries, including agriculture. However, studies primarily focus on passenger vehicles, with fewer examining autonomous trucks. Therefore, this study reviews autonomous truck systems implementation in North Dakota’s agricultural industry to develop comprehensive technology readiness frameworks and strategic deployment approaches. The review integrates systematic literature review and event history analysis of 52 studies, categorized using Social–Ecological–Technological Systems framework across six dimensions: technological, economic, social change, legal, environmental, and implementation challenges. The Technology Readiness Level (TRL) analysis reveals 39.5% of technologies achieving commercial readiness (TRL 8–9), including GPS/RTK positioning and V2V communication demonstrated through Minn-Dak Farmers Cooperative deployments, while gaps exist in TRL 4–6 technologies, particularly cold-weather operations. Nonetheless, challenges remain, including legislative fragmentation, inadequate rural infrastructure, and barriers to public acceptance. The study provides evidence-based recommendations that support a strategic three-phase deployment approach for the adoption of autonomous trucks in agriculture. Full article

In the era of smart agriculture, accurate identification of plant species is critical for effective crop management, biodiversity monitoring, and the sustainable use of medicinal resources. However, existing deep learning approaches often underperform when applied to fine-grained plant classification tasks due to the lack of domain-specific, high-quality datasets and the limited representational capacity of traditional architectures. This study addresses these challenges by introducing a novel, well-curated leaf image dataset consisting of 39 classes of medicinal and aromatic plants collected from the Aromatic and Medicinal Plant Research Station in Odakkali, Kerala, India. To overcome performance bottlenecks observed with a baseline Convolutional Neural Network (CNN) that achieved only 44.94% accuracy, we progressively enhanced model performance through a series of architectural innovations. These included the use of a pre-trained VGG16 network, data augmentation techniques, and fine-tuning of deeper convolutional layers, followed by the integration of Squeeze-and-Excitation (SE) attention blocks. Ultimately, we propose a hybrid deep learning architecture that combines VGG16 with Batch Normalization, Gated Recurrent Units (GRUs), Transformer modules, and Dilated Convolutions. This final model achieved a peak validation accuracy of 95.24%, significantly outperforming several baseline models, such as custom CNN (44.94%), VGG-19 (59.49%), VGG-16 before augmentation (71.52%), Xception (85.44%), Inception v3 (87.97%), VGG-16 after data augumentation (89.24%), VGG-16 after fine-tuning (90.51%), MobileNetV2 (93.67), and VGG16 with SE block (94.94%). These results demonstrate superior capability in capturing both local textures and global morphological features. The proposed solution not only advances the state of the art in plant classification but also contributes a valuable dataset to the research community. Its real-world applicability spans field-based plant identification, biodiversity conservation, and precision agriculture, offering a scalable tool for automated plant recognition in complex ecological and agricultural environments. Full article

Introduction: Breakfast has emerged as a critical factor in preventing cardiovascular diseases, driven not only by its nutritional content but also by its alignment with circadian rhythms. However, gaps remain in the literature regarding its clinical impact and thematic evolution. Objective: To characterize the global scientific output on the relationship between breakfast quality and cardiovascular health through a systematic bibliometric analysis. Methodology: The PRISMA 2020 protocol was applied to select 1436 original articles indexed in Scopus and Web of Science (1957–2025). Bibliometric tools, including R (v4.4.2) and VOSviewer (v1.6.19) were used to map productivity, impact, collaboration networks, and emerging thematic areas. Results: Scientific output has grown exponentially since 2000. The most influential journals are the American Journal of Clinical Nutrition, Nutrients, and Diabetes Care. The United States, United Kingdom, and Japan lead in publication volume and citations, with increasing participation from Latin American countries. Thematic trends have shifted from traditional clinical markers to innovative approaches such as chrononutrition, digital health, and personalized nutrition. However, methodological gaps persist, including a predominance of observational studies and an underrepresentation of vulnerable populations. Conclusions: Breakfast is a dietary practice with profound implications for cardiometabolic health. This study provides a comprehensive overview of scientific literature, highlighting both advancements and challenges. Strengthening international collaboration networks, standardizing definitions of a healthy breakfast, and promoting evidence-based interventions in school, clinical, and community settings are recommended. Full article

As a new generation of mobile communication networks, 6G security faces many new security challenges. Vehicle to Everything (V2X) will be an important part of 6G. In V2X, connected and automated vehicles (CAVs) need to frequently share data with other vehicles and infrastructures. Therefore, identity revocation technology in the authentication is an important way to secure CAVs and other 6G scenario applications. This paper proposes an efficient credential revocation scheme with a four-layer architecture. First, a rapid pre-filtration layer is constructed based on the cuckoo filter, responsible for the initial screening of credentials. Secondly, a directed routing layer and the precision judgement layer are designed based on the consistency hash and the dynamic RSA accumulator. By proposing the dynamic expansion of the RSA accumulator and load-balancing algorithm, a smaller and more stable revocation delay can be achieved when many users and terminal devices access 6G. Finally, a trusted storage layer is built based on the blockchain, and the key revocation parameters are uploaded to the blockchain to achieve a tamper-proof revocation mechanism and trusted data traceability. Based on this architecture, this paper also proposes a detailed identity credential revocation and verification process. Compared to existing solutions, this paper’s solution has a combined average improvement of 59.14% in the performance of the latency of the cancellation of the inspection, and the system has excellent load balancing, with a standard deviation of only 11.62, and the maximum deviation is controlled within the range of ±4%. Full article