Search Results (844)

The global spread of Mpox virus (MPXV) underscores the urgent need for rapid, field-deployable diagnostic tools, especially in low-resource settings. We evaluated a loop-mediated isothermal amplification (LAMP) assay, termed LAMPOX, developed by Coris BioConcept. The assay was tested in three formats—two liquid versions and a dried, ready-to-use version—targeting only the ORF F3L (Liquid V1) or both the ORF F3L and N4R (Liquid V2 and dried) genomic regions. Analytical sensitivity and specificity were assessed using 60 clinical samples from confirmed MPXV-positive patients. Sensitivity on clinical samples was 81.7% for Liquid V1 and 88.3% for Liquid V2. The dried LAMPOX assay demonstrated a sensitivity of 88.3% and a specificity of 100% in a panel of 112 negative controls, with most positive samples detected in under 7 min. Additionally, a simplified sample lysis protocol was developed to facilitate point-of-care use. While this method showed slightly reduced sensitivity compared to standard DNA extraction, it proved effective for samples with higher viral loads. The dried format offers key advantages, including ambient-temperature stability and minimal equipment needs, making it suitable for point-of-care testing. These findings support LAMPOX as a promising tool for rapid MPXV detection during outbreaks, especially in resource-limited settings where traditional PCR is impractical. Full article

The Kindlin family of scaffold proteins plays key roles in integrin-mediated processes. Kindlin-1 and -2, encoded by the FERMT1 and FERMT2 genes, respectively, are expressed in the epidermis. Kindlin-1 plays protective roles against the development of cutaneous squamous cell carcinomas (cSCCs) in epidermal keratinocytes. However, the role of Kindlin-2 in transformed epidermal keratinocytes has remained virtually unexplored. In this study, we used siRNA approaches to generate Kindlin-2-depleted cells in three isogenic transformed keratinocyte lines. PM1, MET1, and MET4 cells model, respectively, a precancerous lesion, a primary cSCC, and a metastatic lesion of the latter. MET1 cells express both Kindlin-1 and -2. However, Kindlin-1 was not detectable in PM1 and MET4 cells. FERMT2 silencing in PM1 and MET4, but not in MET1 cells, reduced proliferation and the ability to adhere to culture surfaces and spreading. Furthermore, Kindlin-2-depleted PM1 and MET4, but not MET1 cells, exhibited decreased numbers of focal adhesions, as well as an altered F-actin and microtubule cytoskeletal organization. Significantly, FERMT2 silencing reduced the directional migration in all three cell types. These findings are consistent with the concept that, in the absence of other Kindlin orthologues, Kindlin-2 plays a prominent role in the modulation of the proliferation, spreading, focal adhesion assembly, and motility of transformed keratinocytes, as exemplified by PM1 and MET4 cells. Full article

Brain ischemia is a severe condition caused by reduced cerebral blood flow, leading to the disruption of ion gradients in brain tissue. This imbalance triggers spreading depolarizations, which are waves of neuronal and glial depolarization propagating through the gray matter. Microelectrode arrays (MEAs) are essential for real-time monitoring of these electrophysiological processes both in vivo and in vitro, but their sensitivity and signal quality are critical for accurate detection of extracellular brain activity. In this study, we evaluate the performance of a flexible microelectrode array based on gold-coated zinc oxide nanorods (ZnO NRs), referred to as nano-fMEA, specifically for high-fidelity electrophysiological recording under pathological conditions. Acute mouse brain slices were tested under two ischemic models: oxygen–glucose deprivation (OGD) and hyperkalemia. The nano-fMEA demonstrated significant improvements in event detection rates and in capturing subtle fluctuations in neural signals compared to flat fMEAs. This enhanced performance is primarily attributed to an optimized electrode–tissue interface that reduces impedance and improves charge transfer. These features enabled the nano-fMEA to detect weak or transient electrophysiological events more effectively, making it a valuable platform for investigating neural dynamics during metabolic stress. Overall, the results underscore the promise of ZnO NRs in advancing electrophysiological tools for neuroscience research. Full article

The leaf diseases of Panax notoginseng (Panax notoginseng (Burk) F. H. Chen) are mainly spread by spores. To enable rapid and sensitive detection of spores for early warning of disease spread, we developed a carbon dot-based fluorescent probe encapsulated by MIL-101 using wax apple as a green carbon source (WA-CDs@MIL-101). The WA-CDs@MIL-101 was thoroughly characterized, and the detection conditions were optimized. The interaction mechanism between WA-CDs@MIL-101 and spores was investigated. The fluorescence of WA-CDs@MIL-101 was recovered due to electrostatic adsorption between spores and WA-CDs@MIL-101. Under the optimized detection conditions, the probe exhibited excellent sensing performance, showing a strong linear relationship (R² = 0.9978) between spore concentration (0.0025–5.0 mg/L) and fluorescence recovery ratio, with a detection limit of 5.15 μg/L. The WA-CDs@MIL-101 was successfully applied to detect spores on Panax notoginseng leaves, achieving satisfactory recoveries (94–102%) with relative standard deviations of 1.3–3.4%. The WA-CDs@MIL-101 shows great promise for detecting spores on Panax notoginseng leaves. Full article

Social media has become a platform for the rapid spread of persuasion techniques that can negatively affect individuals and society. Propaganda detection, a crucial task in natural language processing, aims to identify manipulative content in texts, particularly in news media, by assessing propagandistic intent. Although extensively studied in English, Arabic propaganda detection remains challenging because of the language’s morphological complexity and limited resources. Furthermore, most research has treated propaganda detection as an isolated task, neglecting the influence of sentiments and emotions. The current study addresses this gap by introducing the first multi-task learning (MTL) models for Arabic propaganda detection, integrating sentiment analysis and emotion detection as auxiliary tasks. Three MTL models are introduced: (1) MTL combining all tasks, (2) PSMTL (propaganda and sentiment), and (3) PEMTL (propaganda and emotion) based on transformer architectures. Additionally, seven task-weighting schemes are proposed and evaluated. Experiments demonstrated the superiority of our framework over state-of-the-art methods, achieving a Macro-F1 score of 0.778 and 79% accuracy. The results highlight the importance of integrating sentiment and emotion for enhanced propaganda detection; demonstrate that MTL improves model performance; and provide valuable insights into the interaction among sentiment, emotion, and propaganda. Full article

Microplastic particles (MPs) are an emerging global pollutant of increasing concern due to their widespread occurrence, persistence, and multifaceted impact on aquatic ecosystems. This study provides a comprehensive review of peer-reviewed literature from 2011 to 2025, analysing the presence, distribution, and microbiological associations of MPs in surface waters across five continents. The findings confirm that MPs are present in both marine and freshwater systems, with concentrations varying by region, hydrology, and proximity to anthropogenic sources. Polyethylene and polypropylene were identified as the most common polymers, often enriched in river mouths, estuaries, and aquaculture zones. A key focus of this review is the plastisphere—microbial biofilms colonizing MPs—which includes both environmental and pathogenic bacteria such as Vibrio, Pseudomonas, and Acinetobacter. Notably, MPs serve as vectors for the spread of antibiotic resistance genes (ARGs), including sul1, tetA and ermF, and β-lactamase genes like blaCTX-M. This highlights their role in enhancing horizontal gene transfer and microbial dissemination. The results emphasize the need for standardized monitoring protocols and further interdisciplinary research. In light of the One Health approach, understanding the microbial dimension of MP pollution is essential for managing risks to environmental and public health. Full article

Migrastatic strategies are considered as candidate therapeutic approaches to suppress cancer invasion into local surrounding tissues and metastatic spread. The F-actin cytoskeleton is responsible for key properties regulating (cancer) cell migration. The cortical F-actin network controls cell stiffness, which, in turn, determines cell migration strategies and efficiency. Moreover, the dynamic remodeling of F-actin networks mediating filopodia, lamellipodia, and F-actin stress fibers is crucial for cell migration. Here, we have used a conditional knockout approach to delete cofilin, an F-actin-binding protein that controls severing. We find that the deletion of cofilin prevents the migration of cancer cells from tumoroids into the surrounding extracellular matrix without affecting their viability. This identifies cofilin as a candidate target to suppress metastatic spread. Pharmacological inhibitors interfering with F-actin dynamics have been developed but their effects are pleiotropic, including severe toxicity, and their impact on 3D tumor cell migration has not been tested or separated from this toxicity. Using concentration ranges of a panel of inhibitors, we select cytochalasins based on the suppression of 2D migration at non-toxic concentrations. We then show that these attenuate the escape of tumor cells from tumoroids and their migration into the surrounding extracellular matrix without toxicity in 3D cultures. This effect is accompanied by suppression of cell stiffness at such non-toxic concentrations, as measured by acoustic force spectroscopy. These findings identify cytochalasins B and D as candidate migrastatic drugs to suppress metastatic spread. Full article

Artisanal and small-scale gold mining (ASGM) in Burkina Faso increasingly relies on cyanide, intensifying concerns about environmental contamination and human exposure. This study assessed free cyanide levels in water and soil across three ASGM sites—Zougnazagmiline, Guido, and Galgouli. Water samples (surface and groundwater) and topsoil (0–20 cm) were analyzed using the pyridine–pyrazolone method. Data were statistically and spatially processed using SPSS version 29.0 and the Google Earth Engine in conjunction with QGIS version 3.34, respectively. A site conceptual model (SCM) was also developed, based on the literature review, field observations, and validation by multidisciplinary experts in public health, toxicology, ecotoxicology, environmental engineering, and the mining sector, through a semi-structured survey. The results showed that 9.26% of the water samples exceeded the WHO guideline (0.07 mg/L), with peaks of 1.084 mg/L in Guido and 2.42 mg/L in Galgouli. At Zougnazagmiline, the water type differences were significant (F = 64.13; p < 0.001), unlike the other sites. In the soil, 29.36% of the samples exceeded 0.5 mg/kg, with concentrations reaching 9.79 mg/kg in Galgouli. A spatial analysis revealed pollution concentrated near the mining areas but spreading to residential and agricultural zones. The validated SCM integrates pollution sources, transport mechanisms, exposure routes, and vulnerable populations, offering a structured tool for environmental monitoring and health risk assessment in cyanide-impacted mining regions. Full article

Deaths occur during the culture of sea bass, and if timely harvesting is not carried out, it will lead to water pollution and the continued spread of sea bass deaths. Therefore, it is necessary to promptly detect dead fish and take countermeasures. Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. To overcome these limitations, this study introduces YOLOv8n-Deadfish, a lightweight and high-precision detection model. First, the homemade sea bass death recognition dataset was expanded to enhance the generalization ability of the neural network. Second, the C2f-faster–EMA (efficient multi-scale attention) convolutional module was designed to replace the C2f module in the backbone network of YOLOv8n, reducing redundant calculations and memory access, thereby more effectively extracting spatial features. Then, a weighted bidirectional feature pyramid network (BiFPN) was introduced to achieve a more thorough integration of deep and shallow features. Finally, in order to compensate for the weak generalization and slow convergence of the CIoU loss function in detection tasks, the Inner-CIoU loss function was used to accelerate bounding box regression and further improve the detection performance of the model. The experimental results show that the YOLOv8n-Deadfish model has an accuracy, recall, and mean precision of 90.0%, 90.4%, and 93.6%, respectively, which is an improvement of 2.0, 1.4, and 1.3 percentage points, respectively, over the original base network YOLOv8n. The number of model parameters and GFLOPs were reduced by 23.3% and 18.5%, respectively, and the detection speed was improved from the original 304.5 FPS to 424.6 FPS. This method can provide a technical basis for the identification of dead sea bass in the process of intelligent aquaculture. Full article

Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding fake news in Urdu is difficult because there are not many effective systems for this. This study aims to solve this problem by creating a detailed process and training models using machine learning, deep learning, and large language models (LLMs). The research uses methods that look at the features of documents and classes to detect fake news in Urdu. Different models were tested, including machine learning models like Naïve Bayes and Support Vector Machine (SVM), as well as deep learning models like Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM), which used embedding techniques. The study also used advanced models like BERT and GPT to improve the detection process. These models were first evaluated on the Bend-the-Truth dataset, where CNN achieved an F1 score of 72%, Naïve Bayes scored 78%, and the BERT Transformer achieved the highest F1 score of 79% on Bend the Truth dataset. To further validate the approach, the models were tested on a more diverse dataset, Ax-to-Grind, where both SVM and LSTM achieved an F1 score of 89%, while BERT outperformed them with an F1 score of 93%. Full article

It is imperative to investigate the behavior of the droplet superimposed condensation of deltamethrin reagent on strawberry leaf surface, as well as the dynamic variation rule of its contact angle. A microinjector was utilized to conduct the experiment of droplet superposition and condensation. The surface tension of deltamethrin droplets was measured by means of an optical contact angle meter, and the wetting parameters, such as contact angle, volume, and spreading diameter, were obtained by observing the leaf surfaces of various parts of strawberries during the dynamic process of superimposed condensation. A model was constructed by establishing the relationship between the contact angle and the coordinates of the observation point and time through the spatial fitting interpolation method. This model is a three-dimensional dynamic trend surface model of contact angle for droplet superposition and condensation. The findings indicated that the surface tension of the deltamethrin drop was 28.92 ± 0.2 mN·m⁻¹. The interval between the superposition of two droplets and the subsequent condensation of a new droplet was found to be within 0.5 s. The time taken for a new droplet to form was found to be between 0.0356 and 0.0476 s. The change in contact angle during the processes of superposition and coalescence can be broadly categorized into three distinct stages: namely, sharp oscillation, slight decrease, and gentle stabilization. The volume of the new droplet formed by the superposition and condensation was found to be 1.05 to 1.93 times that of a lying droplet. The maximum increase in the spreading diameter of the superimposed and condensed droplets was 40.29%. The three-dimensional dynamic trend surface model can reflect the overall spatial–temporal change trend of the contact angle in the process of superposition and coalescence. The model successfully passed the overall significance F-test and each coefficient of the statistical t-test, and demonstrated a satisfactory time interpolation effect. The experimental verification demonstrates that the predicted contact angle value of the model is consistent with the measured value. Full article

Respiratory syncytial virus (RSV) is a major human respiratory pathogen, particularly affecting infants, the elderly, and immunocompromised individuals. RSV exists in both spherical and filamentous forms, with the filamentous morphology associated with enhanced infectivity and cell-to-cell spread. Here, we demonstrate that RhoA, a small GTPase involved in cytoskeletal regulation, is essential for filamentous RSV morphogenesis through its role in organizing lipid raft microdomains. Rhosin, a selective RhoA inhibitor developed through structure-guided screening, disrupts GEF–RhoA interactions to block RhoA activation. The pharmacological inhibition of RhoA with Rhosin significantly reduced filamentous virion formation, disrupted RSV fusion (F) protein colocalization with lipid rafts, and diminished cell-to-cell fusion, without affecting overall viral replication. Scanning electron microscopy revealed that Rhosin-treated infected HEp-2 cells exhibited fewer and shorter filamentous projections compared to the extensive filament formation seen in untreated cells. β-galactosidase-based fusion assays confirmed that reduced filamentation corresponded with decreased cell-to-cell fusion. The biophysical separation of RSV spherical and filamentous particles by sucrose gradient velocity sedimentation, coupled with fluorescence and transmission electron microscopy, showed that Rhosin treatment shifted virion morphology toward spherical forms. This suggests that RhoA activity is critical for filamentous virion assembly, which may enhance viral spread. Immunofluorescence microscopy using lipid raft-selective dyes (DiIC₁₆) and fusion protein-specific antibodies revealed the strong co-localization of RSV proteins with lipid rafts. Importantly, the pharmacological inhibition of RhoA with Rhosin disrupted F protein partitioning into raft domains, underscoring the requirement for intact lipid rafts in assembly. These findings highlight a novel role for host RhoA signaling in regulating viral assembly through raft microdomain organization, offering a potential target for host-directed antiviral intervention aimed at altering RSV structural phenotypes and limiting pathogenesis. Full article

Background/Objective: The global spread of Monkeypox (Mpox) has highlighted the urgent need for rapid, accurate diagnostic tools. Traditional methods like polymerase chain reaction (PCR) are resource-intensive, while skin image-based detection offers a promising alternative. This study evaluates the effectiveness of vision transformers (ViTs) for automated Mpox detection. Methods: By fine-tuning a pre-trained ViT model on an Mpox lesion image dataset, a robust ViT-based transfer learning (TL) model was created. Performance was assessed relative to convolutional neural network (CNN)-based TL models and ViT models trained from scratch across key metrics: accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). Furthermore, a transferability measure was utilized to assess the effectiveness of feature transfer to Mpox images. Results: The results show that the ViT model outperformed a CNN, achieving an AUC of 0.948 and an accuracy of 0.942 with a p-value of less than 0.05 across all metrics, highlighting its potential for accurate and scalable Mpox detection. Moreover, the ViT models yielded a better hypothesis margin-based transferability measure, highlighting its effectiveness in transferring useful learning weights to Mpox images. Gradient-weighted Class Activation Mapping (Grad-CAM) visualizations also confirmed that the ViT model attends to clinically relevant features, supporting its interpretability and reliability for diagnostic use. Conclusions: The results from this study suggest that ViT offers superior accuracy, making it a valuable tool for Mpox early detection in field settings, especially where conventional diagnostics are limited. This approach could support faster outbreak response and improved resource allocation in public health systems. Full article

Y₅F₃[AsO₃]₄ crystallizes needle-shaped in the tetragonal space group P4/ncc with the lattice parameters a = 1143.80(8) pm, c = 1078.41(7) pm and c/a = 0.9428 for Z = 4. The yttrium-fluoride substructure linked via secondary contacts forms a three-dimensional network $\begin{array}{c}3\\ \infty \end{array}${[Y₅F₃]¹²⁺} and the remaining part consists of ψ¹-tetrahedral [AsO₃]³⁻ units, which leave lone-pair channels along [001]. In contrast, platelet-shaped Y₅Cl₃[AsO₃]₄ crystals adopt the monoclinic space group C2/c with the lattice parameters a = 1860.56(9) pm, b = 536.27(3) pm, c = 1639.04(8) pm and β = 105.739(3)° for Z = 4. Condensation of [(Y1,2)O₈]¹³⁻ polyhedra via four common edges each leads to fluorite-like $\begin{array}{c}2\\ \infty \end{array}$ {[(Y1,2)O $\begin{array}{c}e\\ 8/2\end{array}$ ]⁵⁻} layers spreading out parallel to the (100) plane. Their three-dimensional linkage occurs via the (Y3)³⁺ cations with their Cl⁻ ligands on the one hand and the As³⁺ cations with their lone-pairs of electrons on the other, which also form within [AsO₃]³⁻ anions lone-pair channels along [010]. Both colorless compounds can be obtained by solid-state reactions from corresponding mixtures of the binaries (Y₂O₃, As₂O₃ and YX₃ with X = F and Cl) at elevated temperatures of 825 °C, most advantageously under halide-flux assistance (CsBr for Y₅F₃[AsO₃]₄ and ZnCl₂ for Y₅Cl₃[AsO₃]₄). By replacing a few percent of YX₃ with EuX₃ or TbX₃, Eu³⁺- or Tb³⁺-doped samples are accessible, which show red or green luminescence upon excitation with ultraviolet radiation. Full article

When lithium-ion batteries experience thermal runaway, a large amount of heat rapidly accumulates inside, causing the internal pressure to rise sharply. Once the pressure exceeds the battery’s safety valve design capacity, the valve activates and releases flammable gas. If ignited in a high-temperature environment, the escaping gas can cause a jet fire containing high-temperature substances. Effectively controlling the internal temperature of the jet fire, especially rapidly cooling the core area of the flame during the jet process, is important to prevent the spread of lithium-ion battery fires. Therefore, this work proposes a strategy of a synergistic effect using microcapsule fire extinguishing agents and fine water mist to achieve an external barrier and an internal attack. The microcapsule fire extinguishing agents are prepared by using melamine–urea–formaldehyde resin as the shell and 1,1,1,2,2,3,3,4,4-nonafluoro-4-methoxybutane (C₅H₃F₉O) and 1,1,2,2,3,3,4-heptafluorocyclopentane (C₅H₃F₇) as the composite core. During the process of lithium-ion battery thermal runaway, the microcapsule fire extinguishing agents can enter the inner area of the jet fire under the protection of the fine water mist. The microcapsule shell ruptures at 100 °C, releasing the highly effective composite fire suppressant core inside the jet fire. The fine water mist significantly blocks the transfer of thermal radiation, inhibiting the spread of the fire. Compared to the suppression with fine water mist only, the time required to reduce the battery temperature from the peak value to a low temperature is reduced by 66 s and the peak temperature of the high-temperature substances above the battery is reduced by 228.2 °C. The propagation of the thermal runaway is suppressed, and no thermal runaway of other batteries around the faulty unit will occur. This synergistic suppression strategy of fine water mist and microcapsule fire extinguishing agent (FWM@M) effectively reduces the adverse effects of jet fires on the propagation of thermal runaway (TR) of lithium-ion batteries, providing a new solution for efficiently extinguishing lithium-ion battery fires. Full article