Search Results (15,912)

The flavivirus NS1 protein is a component of the viral replication complex and plays diverse, yet poorly understood, roles in the viral life cycle. To enable real-time visualization of the developing replication organelle and biochemical analysis of tagged NS1 and its interacting partners, we engineered a replication-competent yellow fever virus (YFV) replicon encoding a C-terminal fusion of NS1 with green fluorescent protein (NS1–GFP). The initial variant was non-viable in the absence of trans-complementation with wild-type NS1; however, viability was partially restored through the introduction of co-adaptive mutations in GFP (Q204R/A206V) and NS4A (M108L). Subsequent cell culture adaptation generated a 17-nucleotide frameshift within the NS1–GFP linker, resulting in a more flexible and less hydrophobic linker sequence. The optimized genome, in the form of a replicon, replicates in packaging cells that produce YFV structural proteins, as well as in naive BHK-21 cells. In the packaging cells, the adapted NS1–GFP replicon produces titers of infectious particles of approximately 10^6 FFU/mL and is genetically stable over five passages. The expressed NS1–GFP fusion protein localizes to the endoplasmic reticulum and co-fractionates with detergent-resistant heavy membranes, a hallmark of flavivirus replication organelles. This NS1–GFP replicon provides a novel platform for studying NS1 functions and can be further adapted for proximity-labeling strategies aimed at identifying the still-unknown protease responsible for NS1–NS2A cleavage. Full article

Flammulina filiformis is the key industrial edible fungus that requires elevated CO₂ to promote the growth of long stipe and small pileus fruiting bodies. Heat shock transcription factors (HSFs) play vital roles in stress response and development regulation; yet the HSF gene family and its expression dynamics during fruiting body development in F. filiformis remain uncharacterized. This study aims to identify and characterize the HSF gene family in F. filiformis and to investigate their expression patterns during fruiting body development and in response to CO₂ treatments. In this study, 7 FfHSFs were identified, and their structures, sequence features, and phylogenetics were further analyzed. Expression patterns under CO₂ regulation were examined via qRT-PCR. The FfHSFs exhibited CDS lengths of 618–2298 bp, encoding 301–765 hydrophilic amino acids, with molecular weights ranging from 23.4 to 83.8 kDa and theoretical pI values between 4.75 and 9.15. All were predicted to be nuclear-localized. Cis-element analysis revealed motifs associated with growth regulation and stress responses such as low temperature, drought, and hypoxia. Phylogenetically, fungal HSFs were grouped into five clusters, with FfHSFs distributed across four. In this study, we examined the expression levels at four time points (0 h, 2 h, 12 h, and 36 h), under three different carbon dioxide concentrations (0.1%, 5%, and 20%) and in two types of tissues (pileus and stipe) for each six biological replicates. CO₂ treatments showed that 5% CO₂ significantly suppressed pileus expansion but not stipe elongation, while 20% CO₂ inhibited both. Under 20% CO₂ treatment, the pileus diameter decreased by approximately 40%, and simultaneously, the expression level of FfHSF1 decreased by about 70%. qRT-PCR indicated that FfHSF1 decreased with pileus expansion, whereas FfHSF4 increased. All FfHSFs were highly expressed in the stipe elongation zone. Elevated CO₂ down-regulated FfHSF1 in pileus and FfHSF6 in stipes. Based on these findings, it could be proposed that FfHSF1 and FfHSF6 might be candidate regulators in CO₂-mediated morphogenesis, providing insights into hormonal and environmental control of fruiting body development in F. filiformis. Full article

Traffic state estimation (TSE) is a core task in intelligent transportation systems (ITSs) that seeks to infer key operational parameters—such as speed, flow, and density—from limited observational data. Existing methods often face challenges in practical deployment, including limited estimation accuracy, insufficient physical consistency, and weak generalization capability. To address these issues, this paper proposes a hybrid estimation framework that integrates multi-agent reinforcement learning (MARL) with the Lighthill–Whitham–Richards (LWR) traffic flow model. In this framework, each roadside detector is modeled as an agent that adaptively learns fundamental diagram (FD) parameters—the free-flow speed and jam density—by fusing local detector measurements with global CAV trajectory sequences via an interactive attention mechanism. The learned parameters are then passed to an LWR solver to perform sequential (rolling) prediction of traffic states across the entire road segment. We design a reward function that jointly penalizes estimation error and violations of physical constraints, enabling the agents to learn accurate and physically consistent dynamic traffic state estimates through interaction with the physics-based LWR environment. Experiments on simulated and real-world datasets demonstrate that the proposed method outperforms existing models in estimation accuracy, real-time performance, and cross-scenario generalization. It faithfully reproduces dynamic traffic phenomena, such as shockwaves and queue waves, demonstrating robustness and practical potential for deployment in complex traffic environments. Full article

Perinatal antibiotic exposure poses a significant risk to maternal-offspring immune programming and infant gut microbiota development. This study investigated the time-specific effects of maternal cefoperazone sodium (CPZ) administration on IgG transfer and offspring gut microbiota in a murine model. Pregnant C57BL/6J mice were assigned to control (CON), gestational (G-CPZ), lactational (L-CPZ), and combined gestational/lactational (GL-CPZ) treatment groups. Results showed that all CPZ treatments significantly reduced IgG and its subtype levels in maternal serum, colostrum, and offspring serum (p < 0.05). Concurrently, mRNA expression of the neonatal Fc receptor (FcRn), critical for IgG transport, was downregulated in both maternal breast and offspring intestinal tissues (p < 0.05). Furthermore, 16S rRNA sequencing revealed that CPZ exposure altered offspring gut microbiota diversity and composition. Alpha diversity was reduced, particularly in the G-CPZ group, while beta diversity showed significant separation in L-CPZ and GL-CPZ groups (p < 0.05). Taxonomic shifts included decreased Bacteroidetes and Lactobacillus, and in the GL-CPZ group, a marked increase in Firmicutes and potential pathobionts like Enterococcus and Hungatella (p < 0.05). These findings demonstrate that perinatal antibiotic exposure, depending on its timing, impairs maternal-offspring IgG transfer via the FcRn pathway and induces distinct, persistent alterations in the offspring’s gut microbiota, which may have implications for neonatal immunity and long-term health. Full article

Porcine circovirus 3 (PCV3), first reported in 2016, is associated with diverse clinical conditions, including porcine dermatitis and nephropathy syndrome, reproductive disorders, and systemic inflammation, and affects pigs of all ages. To investigate the prevalence and genetic evolution of PCV3 in Hunan Province, China, 700 lymph node tissue specimens were collected from slaughterhouses and hazard-free disposal centers across 14 prefecture-level cities between 2021 and 2024 and screened using real-time quantitative PCR (qPCR). Epidemiological investigation revealed an overall PCV3 positivity rate of 29.4% (206/700) in the province. The highest prevalence was observed in Yiyang City (56%, 28/50), whereas no positive samples were detected in Zhuzhou City (0/30). Among the positive samples, 34 specimens from different cities with Ct values < 25 were selected for Cap gene amplification and sequencing. Phylogenetic analysis showed that PCV3c was the predominant genotype (67.6%, 23/34), followed by PCV3a (32.4%, 11/34), while PCV3b was not detected. We identified twelve amino acid substitution sites within Cap proteins. Furthermore, B-cell linear epitope prediction and homology modeling of the Cap protein identified seven linear epitopes, with ten amino acid variation sites located within these epitopic regions. This study enriches the molecular epidemiological data of PCV3 in southern China and provides a reference for future PCV3 control strategies. Full article

African swine fever (ASF) continues to spread, threatening the global swine industry and endangered swine species. Sri Lanka is a tropical island situated south of India in the Indian Ocean. Here, we report the first detection of ASF in Sri Lanka. In September 2024, increased pig mortality was reported across the country, with initial confirmation of porcine reproductive and respiratory syndrome (PRRS). Despite vaccination for PRRS, the mortalities continued to increase and therefore, tissue samples collected from dead pigs were subjected to ASF real-time PCR. ASFV genomic material was detected in most of the samples. The real-time PCR-positive samples were then subjected to genotyping by partial genome sequencing. All p72 and p54 sequences were found to be aligned with ASFV genotype II viruses, and CD2v sequences were found to be aligned with ASFV serogroup 8 viruses. The real-time PCR-positive samples were inoculated onto primary porcine leukocytes for virus isolation, and a selected number of tissues collected from dead pigs were subjected to histopathology. Histopathological studies revealed widespread loss of lymphocytes together with inflammation and extensive staining of ASFV antigens in tissue samples. Hemadsorption (HAD)-positive isolates were obtained from seven clinical samples, and three of them were subjected to whole-genome sequencing. Phylogeographic analysis of the whole-genome sequences showed that the virus is closely related to ASFV strains circulating in China and Hong Kong. Full article

Airway management is central to the care of critically ill patients, yet it remains one of the most challenging interventions in emergency departments and intensive care units. Patients often present with severe physiological instability, limited cardiopulmonary reserve, and high acuity, while clinicians often work under constraints related to time for preparation, equipment availability, trained workforce, monitoring, and access to advanced rescue techniques. These challenges are particularly pronounced in low- and middle-income countries and other resource-limited or austere environments, where the margin for error is narrow and delays or repeated attempts in airway management may rapidly precipitate hypoxemia, hemodynamic collapse, or cardiac arrest. Although contemporary airway guidelines emphasize structured preparation and rescue pathways, many assume resources that are not consistently available in such settings. This narrative review discusses pragmatic, context-adapted strategies for airway management in constrained environments, with emphasis on physiology-first preparation, appropriate oxygenation and induction techniques, simplified rapid-sequence intubation, and the judicious use of basic airway adjuncts, supraglottic devices, and video laryngoscopy, where available. Adapted difficult airway algorithms, front-of-neck access in the absence of surgical backup, human factors, team training, and ethical considerations are also addressed. This review aims to support safer and effective airway management for critically ill patients in resource-limited emergency and intensive care settings. Full article

Atomic Layer Deposition (ALD) is a key thin-film fabrication technique that enables the growth of ultra-thin, conformal, and compositionally controlled layers for applications in nanoelectronics, optoelectronics, and energy devices. However, the high cost and operational complexity of commercial ALD systems limit their accessibility in academic and emerging research environments. In this work, a low-cost, automated thermal ALD system is designed, assembled, and experimentally validated for the deposition of zinc oxide (ZnO) thin films. The developed system enables precise control of precursor dosing, purge sequences, and substrate temperature via an integrated LabVIEW–Arduino control architecture, allowing reproducible and stable thin-film growth. The design allows the use of various precursors through high-precision three-way diaphragm valves. In addition, the system allows continuous purge gas flow in the reaction chamber, which enhances the drag velocity of the precursor gas, reducing dosage requirement, accelerating chamber saturation time and lowering the total consumption of precursors per deposition cycle. ZnO thin films were successfully grown on silicon and glass substrates at 200 °C using diethylzinc (DEZ) as the metal precursor and hydrogen peroxide (H₂O₂) as the oxidant. The process exhibited self-limiting growth characteristics typical of ALD, yielding a growth per cycle of approximately 0.8 Å. The deposited ZnO films exhibited optical transparency of 70–80% in the visible region, a refractive index of approximately 1.9, and an optical bandgap close to 3.4 eV, which are consistent with values reported for high-quality ZnO films grown in commercial ALD systems. These results demonstrate that the proposed low-cost platform is capable of producing functional ZnO thin films with properties comparable to those obtained with conventional commercial reactors. Overall, this work presents an accessible and scalable thermal ALD system that significantly reduces equipment costs while maintaining reliable process control and film quality, offering a practical framework for expanding thin-film research capabilities across microelectronics, optoelectronics, and nanotechnology laboratories. Full article

Ultraviolet (UV) radiation is a significant environmental stressor that exerts profound impacts on insect physiology, behaviour and survival. Although some insects can use UV light for spatial orientation and navigation, it can induce DNA damage, oxidative stress, and impair critical biological functions, ultimately reducing ecological fitness. Sclerodermus alternatusi Yang (Hymenoptera: Bethylidae) is a dominant ectoparasitoid of the early instar larvae of Monochamus alternatus and plays a key role in the biological control of this pest in forestry systems; however, it faces intense UV exposure in the field environment. Despite its ecological importance, the molecular mechanisms underlying its responses to UV-induced stress remain poorly understood. In this study, newly emerged adult wasps (within 24 h post-eclosion) were exposed to UVA (365 nm) and UVC (253.7 nm) radiation for 9 h under controlled laboratory conditions. Total RNA was extracted from treated and control individuals for transcriptomic analysis using RNA-Seq. A total of 505 differentially expressed genes (DEGs) were identified; gene ontology enrichment analysis revealed that UVA exposure significantly upregulated genes involved in cellular respiration and oxidative phosphorylation, suggesting an enhanced metabolic response. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that UV stress modulates energy metabolism through the activation of oxidative phosphorylation and thermogenesis-related pathways, highlighting the reallocation of energy resources in response to UV-induced stress. To validate the RNA-Seq data, four representative DEGs were selected for quantitative real-time PCR (RT-qPCR) analysis. The qPCR results were consistent with the transcriptomic trends, confirming the reliability of the sequencing data. Collectively, this study provides a comprehensive overview of the molecular response mechanisms of S. alternatusi to UV stress, offering novel insights into its environmental adaptability and laying a theoretical foundation for its application in biological pest control under field conditions. Full article

Cancer patients are highly vulnerable to severe COVID-19, requiring models that capture tumor–virus interactions. We investigated tumor- and variant-specific effects of SARS-CoV-2 Gamma and Delta infections using patient-derived organoids (PDOs) from metastatic breast, lung, and colorectal cancers. Viral infection was quantified by Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) 24 h post-infection, and morphological changes and immune mediators were profiled. Genomic analysis using whole-exome sequencing was performed to identify contributing host-related gene alterations. The Delta variant produced consistently higher viral loads in lung and breast PDOs, while colorectal PDOs showed variable susceptibility. Infection led to reduced area and perimeter and increased circularity across all tumor types. Immune profiling revealed distinct responses: Gamma decreased Interferon alpha (IFNα) in lung PDOs and increased E-selectin in colorectal PDOs. Delta broadly reduced inflammatory mediators in lung [10 kDa interferon gamma-induced protein (IP-10) and Intercellular adhesion molecule 1 (ICAM-1)] and breast [Interleukin-6 (IL-6), Interleukin-13 (IL-13), and Interleukin-17A (IL-17A)] PDOs, while increasing Macrophage inflammatory protein 1-beta (MIP-1β) in colorectal PDOs. Host gene variants involved in trafficking (FYCO1 and RAB7A) and immune signaling (FOXA2, SFTPD, STAT3, and TET2) were associated with differential infection profiles. These findings show that SARS-CoV-2 induces variant- and tumor-specific morphological and immunological changes in cancer PDOs, highlighting the potential of this model to unravel host–virus interactions and identify genetic factors that shape infection outcomes in cancer. Full article

In fish gut microbiome studies, there are no standardized protocols regarding sampling region or post-feeding time, nor clear consensus on whether analyses should target resident (autochthonous) or transient (allochthonous) bacteria. This study examined the dynamics and interactions of both microbial communities in the anterior and posterior intestine of farmed gilthead sea bream and evaluated the resident microbiome at 24 and 48 h post-feeding. Microbial DNA was sequenced using the Oxford Nanopore Technology platform. Data were analyzed through statistical and discriminant approaches, as well as a Bayesian network framework to assess bacterial interactions. Transient communities showed higher richness and diversity, regardless of intestinal section, suggesting a more specialized and stable microbial environment in the mucus layer. The two communities differed markedly in structure and composition. Variations associated with intestinal region were less pronounced, particularly for autochthonous bacteria, and post-feeding fluctuations in the resident microbiome were minimal. Functionally, results indicated relevant synergies between communities. Protein metabolism pathways were enriched in autochthonous bacteria, whereas allochthonous microorganisms contributed mainly to bile acid and carbohydrate metabolism. Overall, resident and transient bacteria constitute distinct communities in the gut of gilthead sea bream, with numerous genera present in both but most being differentially represented and interconnected. Full article

The Sındırgı earthquake sequence, with moment magnitudes of 6.1 on 10 August and 27 October 2025, respectively, occurred within the Simav Fault Zone in western Türkiye, rupturing nearby but structurally distinct fault segments. In this study, we combine Sentinel-1 InSAR time-series measurements with seismological data, geomorphic observations, and post-event field surveys to examine how deformation evolved between and after these events. InSAR results indicate coseismic line-of-sight displacements of 6–7 cm, followed by post-seismic deformation that persisted for months at 8–10 mm/yr. This behavior signifies that deformation continued well beyond the initial rupture. The estimated displacement does not align with a single fault plane. Instead, it corresponds to a network of early-mapped and previously unrecognized fault segments. Seismicity patterns and stress tensor inversions show that activity migrated spatially after 10 August and that the faulting mechanism altered before the second earthquake. When synthesized, observations indicate stress transfer within a modular, segmented fault system, thought to have been influenced by regional structural complexity. Field investigations after the October earthquake reported new surface cracks and fault traces, providing evidence of shallow deformation. The collected results indicate that post-seismic stress redistribution played a leading role in modulating the 2025 Sındırgı earthquake sequence. Full article

Unmanned aerial vehicles (UAVs) increasingly share low-altitude airspace with birds, making early distinguishing between drones and biological targets critical for safety and security. This work addresses long-range scenarios where objects occupy only a few pixels and appearance-based recognition becomes unreliable. We develop a model-driven simulation pipeline that generates synthetic data with a controlled camera model, atmospheric background and realistic motion of three aerial target types: multicopter, fixed-wing UAV and bird. From these sequences, each track is encoded as a time series of image-plane coordinates and apparent size, and a bidirectional long short-term memory (LSTM) network is trained to classify trajectories as drone-like or bird-like. The model learns characteristic differences in smoothness, turning behavior and velocity fluctuations, and to achieve reliable separation between drone and bird motion patterns on synthetic test data. Motion-trajectory cues alone can support early distinguishing of drones from birds when visual details are scarce, providing a complementary signal to conventional image-based detection. The proposed synthetic data and sequence classification pipeline forms a reproducible testbed that can be extended with real trajectories from radar or video tracking systems and used to prototype and benchmark trajectory-based recognizers for integrated surveillance solutions. The proposed method is designed to generalize naturally to real surveillance systems, as it relies on trajectory-level motion patterns rather than appearance-based features that are sensitive to sensor quality, illumination, or weather conditions. Full article

Background: Port digital transition is central to competitiveness and sustainability, yet existing frameworks devoted to such transition toward smart port are descriptive, technology-centered, or weak on data governance. This study designs and empirically refines a comprehensive and novel ten-step roadmap relative to existing Port/Industry 4.0 models, synthesized from 14 partial frameworks that each cover only subsets of the transition, by considering data governance and consolidating cost, time, and impact in the selection step. Methods: We synthesized recent Industry 4.0 and smart port-related frameworks into a normalized sequence of steps embedded in the so-called roadmap, then examined it in an exploratory case of a technology deployment project in a Canadian port using stakeholder interviews and project documents. Evidence was coded with a step-aligned scheme, and stakeholder feedback and implementation observations assessed whether each step’s outcomes were met. Results: The sequence proved useful yet revealed four recurrent hurdles: limited maturity assessment, uneven stakeholder engagement, ad hoc technology selection and integration, and under-specified data governance. The refined roadmap adds a diagnostic maturity step with target-state setting and gap analysis, a criteria-based selection worksheet, staged deployment with checkpoints, and compact indicators of transformation performance, such as reduced logistics delays, improved energy efficiency, and technology adoption. Conclusions: The work couples theory-grounded synthesis with empirical validation and provides decision support to both ports and public authorities to prioritize investments, align stakeholders, propose successful policies and digitalization supporting programs, and monitor outcomes, while specifying reusable steps and indicators for multi-port testing and standardized metrics. Full article

Fibrin clots with strain-hardening characteristics exhibit pronounced material nonlinearity and acoustic dispersion under ultrasound, leading to waveform distortion and shock formation during finite-amplitude wave propagation. However, peak-shock stress is limited by viscoelastic dissipation and dispersion, constraining the efficiency of ultrasound in applications such as thrombus ablation. To overcome this limitation, a shock wave amplification method using designed multi-wave-packet sequences is proposed. Based on a power-law model from quasi-static compression tests, shock generation under a single sinusoidal pulse was first simulated. The dual-wave-packet chasing strategy was then developed, in which the amplitude, frequency, and time delay of the second packet were tuned to achieve effective superposition with the precursor. The waveform superposition factor (WSF) was introduced for quantitative evaluation. Numerical results demonstrate that this strategy can significantly increase the peak-shock-wave stress, with a maximum gain of 22.7%. Parametric analysis further identified amplitude as the dominant factor influencing wavefront steepness and amplification effectiveness. This study provides a novel method and theoretical support for developing efficient and controllable ultrasonic sequences for thrombolysis. Full article