Search Results (129)

Avian viruses formed the foundation of early retrovirology. The historical line extends from the discovery of the first sarcoma virus by Peyton Rous to the quantitative determination of oncogenic activity in cell culture by the focus assay. As a viral group, avian retroviruses offered exclusive advantages that allowed the assembly of a unique and powerful tool chest for the analysis of viral activity. Among the fundamental discoveries facilitated by these tools were viral and cellular oncogenes, cell surface receptors, virus-specific detection of inapparent infection, high-frequency genetic recombination between retroviruses, and the genetic maps of simple retroviruses. The work with avian viruses was soon complemented by research on mammalian retroviruses, and several oncogenes that became the basis of successful targeted therapies were defined. The field of cancer genes is at a point of transition. Future developments will be driven by new technologies and interpretations. They will also require a more comprehensive approach. Full article

This study provides the first updated checklist of Moroccan freshwater molluscs, synthesizing faunistic knowledge accumulated between 1795 and 2026. The dataset was primarily compiled from specialized literature, complemented by the authors’ expertise and recent field investigations. Taxonomic classifications at the family, genus, and species levels were revised in accordance with current systematic interpretations. In total, 106 freshwater molluscan species, belonging to 55 genera and 14 families, were documented. Chorological analysis reveals a clear dominance of Palearctic elements, particularly of Mediterranean affinity, alongside a high proportion of strictly endemic Moroccan taxa. Most of these endemics are associated with springs (crenobionts) and subterranean habitats (stygobionts), emphasizing the role of these environments as key centres of micro-endemism and diversification. A comprehensive database comprising 838 occurrence records was assembled, including GPS coordinates and sampling dates. The analysis identifies biodiversity hotspots mainly concentrated in the Mediterranean part of Morocco, particularly within the Middle Atlas Mountains, followed by the northeastern regions, where the highest species richness and citation rates were recorded. Despite this progress, significant gaps remain in the knowledge of Moroccan freshwater molluscs. Several regions still require further exploration, while ongoing threats—including pollution, habitat degradation driven by anthropogenic activities, global environmental change, and biological invasions—pose significant challenges. Addressing these gaps calls for intensified research efforts, including comprehensive field surveys, integrative taxonomic and molecular approaches, and long-term ecological monitoring. Overall, this study represents a significant step toward advancing the knowledge and conservation of freshwater molluscan diversity in Morocco. Full article

Liquid–liquid phase separation (LLPS) of RNA drives the formation of membraneless organelles, and its dysregulation is closely linked to major human diseases, including cancer, neurodegenerative disorders, and various rare genetic diseases. Current strategies for modulating LLPS often require the introduction of exogenous molecules or specific genetic modifications. Here, coarse-grained molecular dynamics (CGMD) simulations suggest that terahertz (THz) oscillatory fields may influence the condensation of pathogenic G4C2 RNA repeats under the simulated conditions. Oscillatory fields at 10 THz and 37.3 THz are shown to effectively counteract salt-induced condensate dissolution. At the molecular level, THz oscillatory fields are associated with reduced phosphate–sodium contacts at low ionic strengths and with faster water diffusion in the hydration layer at higher salt levels. These changes correlate with an increase in stable intermolecular contacts and a more compact RNA state, suggesting a field-driven shift in the balance of interactions. These findings provide a conceptual and mechanistic basis for understanding how oscillatory fields may influence biomolecular condensation, establishing a microscopic framework for using external variable fields to manipulate biomolecular assemblies. Full article

The railway track system is a complex assembly of rails, sleepers, and fastenings designed to ensure operational stability and safety. Within this framework, rail pads play a critical role in load transfer, vibration attenuation, and noise control. This study provides a comprehensive bibliometric analysis of research on railway components published between 2015 and 2024, based on 288 documents retrieved from Scopus, Elicit, and Web of Science. Publication trends reveal a steady increase in research output over the study period, primarily driven by Spain and China. Keyword co-occurrence analysis yielded 51 keywords organized into seven thematic clusters, with the highest frequency terms being “rail pad”, “noise”, “dynamic property”, and “MTHDRP”. The analysis highlights a significant focus on materials such as TPEs, EPDM, and EVA, with static preload and stiffness identified as the most scrutinized performance factors. Findings indicate a clear thematic shift from traditional field testing toward advanced material science and sensor-integrated monitoring technologies. Ultimately, this review outlines future research trajectories emphasizing sustainability, smart sensor integration, and predictive maintenance. By synthesizing a decade of academic contributions, this study serves as a strategic roadmap for optimizing the long-term durability and efficiency of modern railway infrastructure. Full article

Rhizosphere microbiome engineering is a promising approach that can enhance crop resilience and input use efficiency by redirecting plant–microbe–soil interactions toward predictable functions. Here, we review the mechanistic bases underlying rhizosphere assembly and stability, including root exudate-mediated selection, priority effects, keystone taxa, and metabolite-driven signaling, and connect these principles to proposed design rules for microbial inoculants. We present a generalizable Design–Build–Test–Learn (DBTL) framework for engineering synthetic microbial consortia, covering trait-to-module mapping (nutrient acquisition, phytohormone modulation, ACC deaminase activity, stress-protective metabolites, and biocontrol), compatibility screening, minimal yet robust community architectures, and iterative optimization driven by multi-omics and high-throughput phenotyping. Translation to field settings is framed as an engineering challenge defined by formulation and administration limitations, including carrier type, seed coating and encapsulation methods, shelf life, strain invasiveness, and permanence of colonization amid environmental diversity. We also summarize how integrative measurement pipelines (amplicon and shotgun sequencing, transcriptomics, metabolomics, and network or causal analyses) can advance microbiome studies from correlation to actionability. We describe how precision agriculture (sensors, remote sensing, and variable-rate inputs) and AI/ML (split-sample comparisons, transfer learning, and active learning) approaches can accelerate strain discovery, mixture optimization, and adaptive experimentation, driven by the need for stringent controls, metadata-rich reporting, and cross-site comparability. Use cases focus on stress conditions (drought, salinity, thermal extremes, and biotic stress) to demonstrate how microbial functions translate to agronomic outcomes and to highlight critical bottlenecks for reproducible, scalable microbiome products. Full article

Magnetizing living cells with superparamagnetic iron oxide nanoparticles (SPIONs) enables their remote manipulation using external magnetic field. This lays the foundation for magnetically assembling tissue precursors within cell-friendly, proliferation-permissive environments and holds considerable promise for biomedical applications, particularly in the development of complex single- and multicellular tissue constructs for bone and organ reconstruction. However, progress in this field is limited by the lack of robust mathematical tools for accurate control of ensembles of magnetic nano- and micro-objects. In practical printing scenarios, collective behavior and unavoidable statistical heterogeneity—such as variations in SPION size and shape or deviations in cell magnetization—render traditional equation-based modeling inadequate. We developed a hybrid modeling framework integrating conventional physics-based simulations with artificial intelligence-driven image analysis. Dynamic parameters were extracted from video recordings of magnetized cells moving within model microfluidic devices exposed to well-defined magnetic fields and gradients. The AI-based analysis enabled quantitative characterization of ensemble behavior under heterogeneous conditions. The proposed framework successfully captured the collective dynamics of magnetized cell ensembles and enabled accurate control of their spatial organization under external magnetic actuation. The integration of simulation and data-driven analysis provided robust parameter identification despite statistical heterogeneity within the system. This integrated modeling approach provides a practical and effective tool for controlling the three-dimensional magnetic assembly of living cells, with strong potential for applications in tissue engineering. Full article

Disentangling the joint effects of resource availability and disturbance on plant diversity is fundamental to understanding community assembly. We developed a stochastic extension of the Lotka–Volterra model that explicitly incorporates resource facilitation and disturbance-induced mortality, both mediated by species-specific trait responses. Combining simulations with a long-term field experiment manipulating nitrogen addition and mowing, we show that mowing consistently increased species diversity, whereas nitrogen addition reduced it, with no significant interaction between the two factors. Notably, mowing increased evenness, suggesting that higher diversity can coincide with more even abundance distributions. Simulations reproduced these patterns and revealed a non-linear resource–disturbance relationship: diversity declined under high-resource, low-disturbance conditions but was maintained at intermediate disturbance and moderate-to-low resource levels. This pattern was further supported by shifts in evenness and dominance across environmental gradients. Our results demonstrate that plant diversity emerges from a balance between resource-driven competitive exclusion and disturbance-mediated coexistence, modulated by species-specific traits. Full article

Proton exchange membrane water electrolysis is a promising technology for large-scale green hydrogen production due to its high efficiency, compact design, and rapid dynamic response. However, its commercialization is strictly limited by high material costs, durability issues, and complex multiphysics coupling within the membrane electrode assembly. This work provides a comprehensive and critical review of key physicochemical processes and advanced predictive modeling approaches for PEMWEs. To capture recent paradigm shifts, we introduce an innovative multi-dimensional classification framework—incorporating spatial resolution, temporal dynamics, and methodological paradigms—to critically evaluate lumped-parameter, continuum, microscale, and multiscale models, explicitly defining their applicability bounds and inherent limitations. The fundamental mechanisms governing electrode kinetics, membrane water transport, and gas–liquid two-phase flow are analyzed, establishing state-of-the-art quantitative benchmarks for microstructural parameters and advanced 3D flow field topologies under high-current-density and high-pressure regimes. Furthermore, we systematically examine model validation rigor, typical prediction errors, and the critical failure of static models in capturing dynamic property shifts during extreme bubble breakthrough. Recent breakthroughs integrating in situ diagnostics, pore-scale simulations, density functional theory, and Physics-Informed Neural Networks are extensively discussed. Future efforts must prioritize mechanical–electrochemical–thermal coupling, transient degradation prognostics, and machine learning-driven predictive digital twin technologies to overcome current empirical limitations and accelerate the gigawatt-scale deployment of PEMWE systems. Full article

Integrated die-cast components reduce machining/assembly steps and improve mechanical dynamic characteristics, eliminating joint loosening/fracture risks after long-term use. However, the highly variable geometries and random spatial distributions of burrs, flash, parting lines, and risers in castings invalidate pre-programmed or teach-in robotic grinding methods. This paper reviews recent progress and future trends in robotic grinding, analyzing four core aspects: force control stability/adaptability (e.g., adaptive impedance control can reduce average force-tracking error to 0.38 N), trajectory planning/path generation (e.g., error-driven compensation can lower contour error by 34.2–55.1%), process parameter optimization, and challenges of sensing latency/quality evaluation (e.g., deep learning models achieve 97.64% accuracy in identifying abrasive belt wear states). The key enabling technologies are summarized, including active/passive compliant force control, model-/data-driven adaptive trajectory planning, intelligent process parameter optimization integrating physical mechanisms and data-driven approaches, and multi-modal state monitoring with online quality assessment. Representative applications (metal castings, aero-engine blades, thin-walled components, weld seams) are presented, and prospective research directions are proposed. This paper provides a comprehensive reference for theoretical research and engineering practice in this field. Full article

Magnetic photonic crystal microspheres (MPCMs) have emerged as a versatile platform for intelligent sensing and display applications, owing to their integration of magnetic actuation with structural coloration. However, their practical implementation is limited by a fundamental structural constraint: most reported MPCMs adopt anisotropic architectures, resulting in angle-dependent optical responses that require continuous magnetic alignment to maintain uniform coloration. Herein, we propose a different structural paradigm based on non-close-packed, optically isotropic MPCMs. Driven by electrostatic repulsion in solutions, monodisperse Fe₃O₄@tannic acid (TA) core–shell nanoparticles spontaneously assemble into non-close-packed amorphous colloidal arrays, also known as photonic glasses, which are subsequently immobilized within stimuli-responsive polymer networks via emulsification-assisted thermal polymerization. By integrating poly(2-hydroxyethyl methacrylate-co-N-vinylpyrrolidone) (HEMA–NVP) or poly(N-isopropylacrylamide) (PNIPAM) as responsive matrices, the resulting MPCMs exhibit sensitive solvent- or thermo-dependent optical responses. Crucially, structural isotropy ensures angle-independent coloration, eliminating the need for continuous magnetic alignment during optical readout. As evidenced by the unchanged structural color and reflection peak under various magnetic field orientations, this design effectively decouples optical sensing from magnetic actuation. The intrinsic free volume of the non-close-packed architecture allows for isotropic lattice expansion and contraction, leading to broad spectral tunability. Collectively, this work establishes a promising design framework for magnetic photonic microsensors. Full article

Air curtain systems have been proposed as a supplementary smoke control strategy for vehicle tunnels, particularly where structural constraints limit the installation or upgrading of conventional ventilation systems. However, most previous studies rely on numerical simulations or fixed experimental facilities, while flexible experimental platforms and the influence of vehicle obstruction on smoke behavior remain less explored. This study experimentally investigates the smoke confinement performance of an air curtain using a 1:18 modular detachable scaled vehicle tunnel model. The modular configuration enables flexible assembly and adjustment of the experimental setup for different test conditions. A series of laboratory experiments was conducted using a liquefied petroleum gas (LPG) burner to simulate a vehicle fire. Temperature measurements and smoke visualization were performed under different air curtain jet velocities and vehicle obstruction conditions to analyze the interaction between the air curtain jet and buoyancy-driven smoke flow. The results show that the air curtain significantly restricts the upstream propagation of hot smoke and modifies the thermal field inside the tunnel. When the jet velocity reached approximately 5 m/s, the temperature in the protected region decreased by about 25–35% compared with the case without an air curtain. In addition, the presence of vehicle models altered the airflow structure and increased heat accumulation in the middle region of the tunnel cross-section. These results demonstrate that the proposed modular tunnel model provides a reliable experimental platform for tunnel fire research and highlights the importance of considering vehicle obstruction effects in tunnel smoke control studies. Full article

Large-scale aerospace components (e.g., wings, fuselage sections, wing boxes, and rocket segments) feature large dimensions, low stiffness, complex interfaces, and strict assembly tolerances. Traditional rigid tooling and manual alignment struggle to meet the demands of high precision, efficiency, and flexibility in modern aerospace manufacturing. This paper presents a structured literature review on the automated assembly of large-scale aerospace components, summarizing advances in three core domains: pose adjustment and positioning mechanisms, digital measurement technologies, and trajectory planning and control. Particular emphasis is placed on two cross-cutting themes: measurement uncertainty analysis and flexible assembly, which are critical for high-quality docking. The review classifies pose adjustment mechanisms into four categories (NC positioners, parallel kinematic machines, industrial robots, and novel mechanisms) and digital measurement into five branches (vision metrology, large-scale metrology, measurement field construction, uncertainty analysis, and auxiliary techniques). It also outlines five trajectory planning and control routes, covering traditional methods, multi-sensor fusion, digital twins, flexible assembly, and emerging intelligent approaches. The analysis reveals that current research suffers from fragmentation among mechanism design, metrology, and control, with insufficient integration of uncertainty propagation and flexible deformation modeling. Future systems will rely on heterogeneous equipment collaboration, uncertainty-aware closed-loop control, high-fidelity flexible modeling, and digital twin-driven decision-making. This review provides a unified framework and a technical reference for developing reliable, flexible, and scalable automated assembly systems for next-generation aerospace structures. Full article

Marine-derived bioactive peptides have attracted increasing attention as value-added functional ingredients. In this study, peptides (<3 kDa) were prepared from yellowfin tuna processing by-products and further fractionated by Sephadex G-25 gel filtration. The major fraction (TBP-MF) exhibited markedly improved compositional homogeneity compared with the unfractionated hydrolysate (TBP), providing a well-defined peptide system for subsequent characterization and biological evaluation. Physicochemical analyses demonstrated that TBP-MF possessed enhanced thermal stability and a more ordered secondary structure, characterized by pronounced β-sheet enrichment, as revealed by TGA/DSC, FTIR, and circular dichroism analyses. Morphological and colloidal characterization further showed that TBP-MF formed relatively uniform lamellar and fibrous assemblies with a narrower particle size distribution and reduced electrostatic stabilization, indicating a higher tendency toward ordered self-association. Peptidomic profiling combined with in silico analysis revealed that TBP-MF was enriched in short peptides with relatively higher PeptideRanker scores and a functional motif distribution containing relatively more neuro-related annotations, although angiotensin-converting enzyme (ACE)- and dipeptidyl peptidase IV (DPP-IV)-related motifs remained predominant in both groups. In differentiated PC12 cells, TBP-MF exhibited excellent cytocompatibility and induced a stable, concentration-dependent increase in the Cell Counting Kit-8 (CCK-8) readout (OD₄₅₀), indicating enhanced cellular metabolic activity and/or increased cell number. In addition, TBP-MF significantly increased intracellular levels of key neurochemical factors associated with sleep-related regulation, including tetrahydrobiopterin (BH4), serotonin (5-HT), and γ-aminobutyric acid (GABA). Overall, this study highlights yellowfin tuna by-products as a promising marine resource for bioactive peptides and suggests that fractionation-driven structural refinement is associated with neuro-related biological activity in differentiated PC12 cells. These findings support the potential application of marine by-product-derived peptides as functional ingredients in health-related fields. Full article

The rapid electrification of road vehicles has fundamentally reshaped the priorities of noise, vibration, and harshness (NVH) engineering. In the absence of combustion-related broadband masking, tonal and order-related phenomena originating from the electric machine, inverter switching, and high-speed reduction gearing have become clearly perceptible and, in many cases, acoustically dominant. Consequently, drivetrain noise in electric vehicles can no longer be assessed at component level alone; it must be understood as a coupled system response shaped by excitation mechanisms, structural dynamics, transfer paths, radiation efficiency, and ultimately human perception. This review adopts a source-to-perception perspective and consolidates the principal physical mechanisms governing vibro-acoustic behavior in integrated electric drive units. Electromagnetic force harmonics and torque ripple are discussed alongside transmission-error-driven gear mesh excitation, while bearing and shaft nonlinearities are examined in the context of high-speed operation. In addition, ancillary thermoacoustic and aerodynamic contributions are considered, reflecting the increasingly integrated packaging of modern e-axle architectures. On this mechanism-oriented basis, dominant excitation types are linked to frequency-appropriate modeling strategies, spanning electromagnetic force extraction, multibody drivetrain simulation, structural finite element analysis, transfer path analysis, and acoustic radiation prediction. Particular attention is given to workflow integration across domains. Finally, the paper identifies research challenges that predominantly arise at system level, including multi-source interaction effects, installation-dependent transfer-path variability, emergent resonances in assembled structures, manufacturing-induced tonal artifacts, and the still limited correlation between predicted vibration fields and perceived sound quality. Full article

The reference genome serves as a fundamental resource for sheep genetic research and molecular breeding, and iterative improvements in assembly quality have directly driven advances in these fields. A systematic literature review was conducted by retrieving relevant studies from major scientific databases using predefined keywords related to sheep reference genomes and genome assembly technologies, followed by structured screening and comparative analysis of eligible publications. This review systematically summarizes the developmental trajectory of the sheep reference genome from early fragmented assemblies to telomere-to-telomere (T2T) genome assembly approaches. Different genome versions are comparatively analyzed from multiple perspectives, including assembly strategies, quality metrics, and functional annotation. Importantly, we propose a genome-resolution-driven analytical framework that explicitly links successive improvements in reference genome completeness with paradigm shifts in sheep genetic analysis, ranging from marker-based studies to structural variation- and multi-omics-enabled trait dissection. Particular emphasis is placed on the potential applications and biological research value of T2T genomes in assembly methodologies and multi-omics integrative analyses. Furthermore, the practical significance of different reference genome versions in genetic dissection, trait mapping, and breeding applications is reviewed, and future directions for sheep genome research are discussed. This review provides both a systematic synthesis and a forward-looking conceptual roadmap for advancing sheep molecular genetics and precision breeding in the T2T genomics era. Full article