Search Results (617)

The complex pathological mechanisms of atherosclerosis (AS) involve lipid metabolism disorders, inflammatory responses, and plaque instability, resulting in significant challenges to effective clinical management. Current therapeutic approaches, such as statins and stent implantation, suffer from issues including single-target action, notable side effects, and the risk of restenosis. Nanoparticle-based drug delivery systems have demonstrated considerable promise by enabling the codelivery of multiple agents directly to atherosclerotic lesions, thereby improving therapeutic efficacy and minimizing systemic toxicity. Among various nanomaterials, organic nanoparticles have recently emerged as a research hotspot in the field of AS treatment due to their excellent biocompatibility, degradability, and potential for targeted modification. This review systematically summarizes the recent advances and emerging trends in the application of organic nanoparticles for AS treatment, employing bibliometric analysis to delineate research frontiers. We employed bibliometric tools to analyze 1999 articles on organic nanocarriers for AS therapy indexed in the Web of Science Core Collection. The analysis included co-occurrence and clustering techniques to explore influential keywords and key contributors. Temporal analysis was applied to identify emerging research hotspots and track the evolution of this field. The literature reveals three major current focal areas: (1) the development of engineered biomimetic organic nanoparticles; (2) the design of multifunctional polymer-based organic nanocarriers; and (3) the innovation of organic-coated stents. This article not only provides a comprehensive overview of cutting-edge organic nanotechnologies for AS therapy, but also critically discusses the challenges in clinical translation, offering insights into future directions for the development of safe, effective, and personalized nanomedicine strategies against AS. Full article

Achieving the full potential of wind energy in the global renewable transition depends critically on enhancing the performance and reliability of polymer composite components. This review synthesizes recent advances from 2022 to 2025, including the development of next-generation hybrid composites and the application of high-fidelity computational methods—finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI)—to optimize structural integrity and aerodynamic performance. It also explores the transformative role of artificial intelligence (AI) in structural health monitoring (SHM) and the integration of Internet of Things (IoT) systems, which are becoming essential for predictive maintenance and lifecycle management. Special focus is given to harsh offshore environments, where polymer composites must withstand extreme wind and wave conditions. This review further addresses the growing importance of circular economy strategies for managing end-of-life composite blades. While innovations such as the geometric redesign of floating platforms and the aerodynamic refinement of blade components have yielded substantial gains—achieving up to a 30% mass reduction in PLA prototypes—more conservative optimizations of internal geometry configurations in GFRP blades provide only around 7% mass reduction. Nevertheless, persistent challenges related to polymer composite degradation and fatigue under severe weather conditions are driving the adoption of real-time hybrid predictive models. A bibliometric analysis of over 1000 publications confirms more than 25 percent annual growth in research across these interconnected areas. This review serves as a comprehensive reference for engineers and researchers, identifying three strategic frontiers that will shape the future of wind turbine blade technology: advanced composite materials, integrated computational modeling, and scalable recycling solutions. Full article

Cancer remains a leading global health challenge, with conventional diagnostic and treatment methods often lacking precision and adaptability. This review explores transformative advancements that are reshaping oncology by addressing these limitations. It begins with an overview of cancer’s complexity, emphasizing the shortcomings of conventional tools such as imaging and chemotherapy, which frequently fail to deliver targeted care. The discussion then shifts to biomarkers, which represent a groundbreaking frontier in early detection, enabling the identification of unique biological signatures that signal the presence of cancer with heightened sensitivity. Building on this foundation, the review examines personalized molecular therapies, which target the specific genetic and molecular vulnerabilities of tumors. These therapies not only enhance treatment efficacy but also minimize adverse effects, offering patients improved outcomes and quality of life. By integrating biomarker-driven diagnostics with tailored therapeutic strategies, a new paradigm of precision oncology emerges, bridging the gap between early detection and effective intervention. Real-world case studies highlight both successes, such as significantly improved survival rates, and persistent challenges, including accessibility and cost barriers. Looking ahead, the review outlines pathways by which to scale these innovations, emphasizing the critical need for robust infrastructure, sustained research investment, and equitable healthcare policies. It concludes by envisioning a future where biomarkers and personalized therapies converge to redefine cancer care, offering earlier detection, precise interventions, and better patient experiences. This work underscores the urgency of adopting cutting-edge approaches to overcome cancer’s persistent threats, paving the way for a more effective and humane era in oncology. Full article

Largemouth bass (LMB; Micropterus nigricans) are popular both as a sportfish and an aquaculture species. At present, six described viruses are associated with LMB, of which two are typically considered in cases of LMB mortality events. Advances in discovery and diagnostic capabilities using next-generation sequencing have augmented surveillance efforts and subsequently led to the discovery of novel cryptogenic viruses. Here, we present evidence of three novel viruses from a single skin sample collected from a hyperpigmented melanistic lesion of an LMB with blotchy bass syndrome associated with MnA-1 co-infection. These viruses represent recently described groups of viruses (adomaviruses and nackednaviruses) that infect fish. Both are markedly understudied and of unknown significance to fish health. This work highlights the diversity of viruses associated with LMB and further advances our understanding of the LMB virome. Application of de novo sequencing approaches presents an opportunity to explore a new frontier of host–pathogen relationships and microbes associated with changing environments. Full article

The environmental challenges posed by global warming have significantly increased the global pursuit of renewable and clean energy sources. Among these, solar energy stands out due to its abundance, renewability, low environmental impact, and favorable long-term economic viability. However, its intermittent nature and dependence on weather conditions hinder consistent and efficient utilization. To address these limitations, nanoparticle-enhanced phase change materials (NPCMs) have emerged as a promising solution for enhancing thermal energy storage in solar thermal systems. NPCMs incorporate superior-performance nanoparticles within traditional phase change material matrices, resulting in improved thermal conductivity, energy storage density, and phase change efficiency. This review systematically examines the recent advances in NPCMs for solar energy applications, covering their classification, structural characteristics, advantages, and limitations. It also explores in-depth analytical approaches, including mechanism-oriented analysis, simulation-based modelling, and algorithm-driven optimization, that explain the behavior of NPCMs at micro and macro scales. Furthermore, the techno-economic implications of NPCM integration are evaluated, with particular attention to cost-benefit analysis, policy incentives, and market growth potential, which collectively support broader adoption. Overall, the findings highlight NPCMs as a frontier in materials innovation and enabling technology for achieving low-carbon, environmentally responsible energy solutions, contributing significantly to global sustainable development goals. Full article

The study compares the overall sustainability of two organic and two conventional rice farming systems during the 2022 drought. The research aimed to develop an experiment exploring the ability of an integrated methodological approach to identify tradeoffs and provide actionable insights for a sustainable agricultural transition under extreme climate stress. To this aim, the study employed economic analysis, Life Cycle Assessment (LCA) for environmental impact, and the OASIS framework for broader social and resilience indicators. The study revealed tradeoffs between the economic efficiency of conventional rice farming and the ecological resilience of organic systems, a conclusion made possible only through its integrated assessment methodology. By combining different methods, the research suggested that while conventional farms achieved clear financial superiority and greater efficiency per ton of rice, organic systems showcased superior ecological performance per hectare, greater biodiversity, and enhanced resilience. This highlights a crucial research frontier focused on designing hybrid systems or new economic models that can translate the environmental resilience of organic methods into tangible market value, effectively resolving the very tradeoffs this comprehensive assessment suggested. Full article

MRNA-based therapeutics and vaccines represent a rapidly expanding frontier in biomedical innovation, with lipid nanoparticles (LNPs) serving as a clinically validated delivery platform. This study explores critical quality attributes of LNP-mRNA formulations, with a particular focus on in vitro biological activity, a key quality attribute of vaccine activity and batch-to-batch consistency. We discuss the importance of optimizing both LNP components and mRNA structure, highlighting recent advances in formulation strategies. Furthermore, we examine the influence of factors such as cell-line selection, experimental design, storage conditions, and targeted cellular delivery on transduction efficiency. Our findings underscore the need for standardized in vitro assays and process-integrated monitoring to support the scalable development and regulatory assessment of mRNA-based therapies. Full article

Scene text understanding, serving as a cornerstone technology for autonomous navigation, document digitization, and accessibility tools, has witnessed a paradigm shift from traditional methods relying on handcrafted features and multi-stage processing pipelines to contemporary deep learning frameworks capable of learning hierarchical representations directly from raw image inputs. This survey distinctly categorizes modern scene text recognition (STR) methodologies into three principal paradigms: two-stage detection frameworks that employ region proposal networks for precise text localization, single-stage detectors designed to optimize computational efficiency, and specialized architectures tailored to handle arbitrarily shaped text through geometric-aware modeling techniques. Concurrently, an in-depth analysis of text recognition paradigms elucidates the evolutionary trajectory from connectionist temporal classification (CTC) and sequence-to-sequence models to transformer-based architectures, which excel in contextual modeling and demonstrate superior performance. In contrast to prior surveys, this work uniquely emphasizes several key differences and contributions. Firstly, it provides a comprehensive and systematic taxonomy of STR methods, explicitly highlighting the trade-offs between detection accuracy, computational efficiency, and geometric adaptability across different paradigms. Secondly, it delves into the nuances of text recognition, illustrating how transformer-based models have revolutionized the field by capturing long-range dependencies and contextual information, thereby addressing challenges in recognizing complex text layouts and multilingual scripts. Furthermore, the survey pioneers the exploration of critical research frontiers, such as multilingual text adaptation, enhancing model robustness against environmental variations (e.g., lighting conditions, occlusions), and devising data-efficient learning strategies to mitigate the dependency on large-scale annotated datasets. By synthesizing insights from technical advancements across 28 benchmark datasets and standardized evaluation protocols, this study offers researchers a holistic perspective on the current state-of-the-art, persistent challenges, and promising avenues for future research, with the ultimate goal of achieving human-level scene text comprehension. Full article

Background/Objectives: Despite advances in diagnosis and treatment, colorectal cancer (CRC) remains one of the most prevalent and challenging malignancies worldwide. The dysregulation of microRNAs (miRNAs) has emerged as a critical factor in CRC onset, progression, and therapeutic resistance. This study aims to provide an overview of global research trends on miRNAs in CRC, (i) identifying the most studied miRNAs, (ii) exploring under-investigated areas, and (iii) highlighting emerging themes and potential future directions. Methods: To assess the evolution of the global miRNA–CRC research trends, we conducted a bibliometric analysis of 828 CRC–miRNA-focused articles published between 2008 and 2024, sourced from the Scopus database. Bibliometric mapping was performed using the R/Bibliometrix package and by leveraging a customized Python-based pipeline, which is useful for extracting and validating miRNA identifiers (miRNA IDs) based on the miRBase database. This miRNA ID-related approach enabled us to systematically identify the most frequently studied miRNAs over time while highlighting underexplored miRNA. Results: The analysis revealed a substantial and accelerating publication growth rate, delineating three major phases in CRC–miRNA research. China emerged as the leading contributor in terms of the publication volume. miR-21, miR-34a, and miR-195-5p were among the most frequently studied miRNAs, underscoring their relevance to CRC biology and therapy. Keyword and citation analyses identified key thematic areas, such as cell proliferation, epithelial–mesenchymal transition, and chemoresistance, especially to oxaliplatin and 5-fluorouracil. Emerging research frontiers included ferroptosis, ceRNA networks, and exosome-mediated miRNA transport. An analysis of the collaborations indicated strong intra-national collaborations, with room for expanding international research networks. Conclusions: This study provides an in-depth bibliometric landscape of the CRC-related miRNA research by highlighting influential studies and journals while identifying gaps and underexplored topics. These insights offer valuable guidance for future translational and clinical research on this topic. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent chronic hepatopathy and a leading precursor of hepatocellular carcinoma (HCC) worldwide. Initially attributed to insulin resistance (IR)-driven metabolic imbalance, recent insights highlight a multifactorial pathogenesis involving oxidative stress (OS), chronic inflammation, and immune dysregulation. The hepatic accumulation of free fatty acids (FFAs) initiates mitochondrial dysfunction and excessive reactive oxygen species (ROS) production, culminating in lipotoxic intermediates and mitochondrial DNA damage. These damage-associated molecular patterns (DAMPs), together with gut-derived pathogen-associated molecular patterns (PAMPs), activate innate immune cells and amplify cytokine-mediated inflammation. Kupffer cell activation further exacerbates OS, while ROS-induced transcriptional pathways perpetuate inflammatory gene expression. Traditional immunity refers to the well-established dichotomy of innate and adaptive immune responses, where innate immunity provides immediate but non-specific defense, and adaptive immunity offers long-lasting, antigen-specific protection. However, a paradigm shift has occurred with the recognition of trained immunity (TI)—an adaptive-like memory response within innate immune cells that enables enhanced responses upon re-exposure to stimuli. Following non-specific antigenic stimulation, TI induces durable epigenetic and metabolic reprogramming, leading to heightened inflammatory responses and altered functional phenotypes. These rewired cells acquire the capacity to produce lipid mediators, cytokines, and matrix-modifying enzymes, reinforcing hepatic inflammation and fibrogenesis. In this context, the concept of immunometabolism has gained prominence, linking metabolic rewiring with immune dysfunction. This literature review provides an up-to-date synthesis of emerging evidence on immunometabolism and trained immunity as pathogenic drivers in MASLD. We discuss their roles in the transition from hepatic steatosis to steatohepatitis, fibrosis, and cirrhosis, and explore their contribution to the initiation and progression of MASLD-related HCC. Understanding these processes may reveal novel immunometabolic targets for therapeutic intervention. Full article

Against the backdrop of global sustainable development and environmental governance, research on contractors’ green behavior has received increasing attention. However, the research progress and knowledge structure within this field remain unclear. This study, therefore, reviews the literature published between 1985 and 2005 in the Web of Science Core Collection and Scopus databases. It aims to reveal the current state of research, identify gaps, and propose future research directions. First, through bibliometric analysis, this study explores research trends, journal distribution, country distribution, author distribution, institutional distribution, and collaboration patterns. Second, social network analysis of keyword co-occurrence is conducted to identify emerging research hotspots and frontier topics. Third, content analysis complements the quantitative findings by synthesizing theoretical foundations, methodological approaches, and influencing factors. Finally, potential future research directions are outlined regarding collaboration models, thematic integration, theoretical frameworks, research methods, factors, research boundaries, contextual applications, and behavioral outcome variables. By systematically reviewing the literature on contractors’ green behavior, this study offers valuable insights for future research as well as management practices. Full article

The accelerating threat of antimicrobial resistance (AMR) demands transformative strategies that go beyond conventional antibiotic therapies. Nanoparticles (NPs) have emerged as versatile antimicrobial agents, offering a combination of physical, chemical, and immunological mechanisms to combat multidrug-resistant (MDR) pathogens. Their small size, surface tunability, and ability to disrupt microbial membranes, generate reactive oxygen species (ROS), and deliver antibiotics directly to infection sites position them as powerful tools for infection control. This narrative review explores the major classes, mechanisms of action, and biomedical applications of antimicrobial NPs—including their roles in wound healing, implant coatings, targeted drug delivery, inhalation-based therapies, and the treatment of intracellular infections. We also highlight the current landscape of clinical trials and evolving regulatory frameworks that govern the translation of these technologies into clinical practice. A distinctive feature of this review is its focus on the interplay between NPs and the human microbiota—an emerging frontier with significant implications for therapeutic efficacy and safety. Addressing this bidirectional interaction is essential for developing microbiota-informed, safe-by-design nanomedicines. Despite promising advances, challenges such as scalability, regulatory standardization, and long-term biosafety remain. With interdisciplinary collaboration and continued innovation, antimicrobial NPs could reshape the future of infectious disease treatment and help curb the growing tide of AMR. Full article

Background/Objectives: Messenger RNA (mRNA) modifications regulate key steps in gene expression, including splicing, translation, and stability. Despite over 300 known RNA modifications, the relatively small subset occurring in mRNA remains understudied compared with tRNA and rRNA. This review aims to systematically evaluate 15 known naturally occurring mRNA-specific modifications, rank them by publication frequency, and highlight emerging frontiers in epitranscriptomics, including discovering new naturally occurring mRNA modifications and environmental RNA (eRNA) epitranscriptomics. Methods: We conducted a structured literature review of PubMed-indexed publications to rank mRNA modifications by citation prevalence. Key modifications such as m⁶A, m⁵C, Ψ, and m¹A were analyzed in terms of enzymatic machinery (“writers,” “erasers,” and “readers”), molecular functions, and physiological relevance. We also reviewed technological advances, with a focus on nanopore sequencing for detection of RNA modifications in native and environmental contexts. Results: The modification m⁶A was identified as the most studied mRNA modification, followed by Ψ, m⁵C, and A-to-I editing (inosine). These modifications influence diverse mRNA processes, including translation efficiency, localization, and immune evasion. Cap-specific modifications such as Cap0, Cap1, and Cap2 were also described, highlighting their role in transcript stability and innate immune regulation. Advances in nanopore sequencing have enabled direct detection of RNA modifications and offer promise for eRNA (environmental RNA) surveys. The potential for nanopore sequencing of many other of the 335 known RNA modifications in the MODOMICS database using existing nanopore technologies is also discussed. Conclusions: mRNA modifications represent a critical, yet incompletely mapped, layer of gene regulation. Continued research—especially using nanopore and machine learning technologies—will help uncover their full biological significance. Exploration of eRNA and identifying new mRNA modifications will redefine our understanding of RNA biology. Full article

Efficient autonomous exploration in unknown obstacle cluttered environments with interior obstacles remains a challenging task for mobile robots. In this work, we present a novel exploration process for a non-holonomic agent exploring 2D spaces using onboard LiDAR sensing. The proposed method generates velocity commands based on the calculation of the solution of an elliptic Partial Differential Equation with Dirichlet boundary conditions. While solving Laplace’s equation yields collision-free motion towards the free space boundary, the agent may become trapped in regions distant from free frontiers, where the potential field becomes almost flat, and consequently the agent’s velocity nullifies as the gradient vanishes. To address this, we solve a Poisson equation, introducing a source point on the free explored boundary which is located at the closest point from the agent and attracts it towards unexplored regions. The source values are determined by an exponential function based on the shortest path of a Hybrid Visibility Graph, a graph that models the explored space and connects obstacle regions via minimum-length edges. The computational process we apply is based on the Walking on Sphere algorithm, a method that employs Brownian motion and Monte Carlo Integration and ensures efficient calculation. We validate the approach using a real-world platform; an AmigoBot equipped with a LiDAR sensor, controlled via a ROS-MATLAB interface. Experimental results demonstrate that the proposed method provides smooth and deadlock-free navigation in complex, cluttered environments, highlighting its potential for robust autonomous exploration in unknown indoor spaces. Full article

Spinal muscular atrophy (SMA) is a rare, autosomal recessive neuromuscular disorder and a leading genetic cause of infant mortality. The past decade has witnessed a paradigm shift in SMA management with the advent of disease-modifying drugs (DMDs). This narrative review aims to (i) summarize pivotal randomized controlled trials (RCTs) that led to the approval of DMDs for SMA Types 1 and 2; (ii) synthesize real-world evidence on their safety and effectiveness; and (iii) explore emerging therapeutic frontiers, including gene modifiers, predictive biomarkers, prenatal interventions, and combination strategies. Pivotal RCTs and real-world studies demonstrate that onasemnogene abeparvovec (a single-dose gene therapy), nusinersen (an intrathecal antisense oligonucleotide), and risdiplam (an oral SMN2 splicing modifier) each significantly improve survival and motor function milestones compared to natural history in Type 1 and Type 2 SMA, with the majority of treated patients achieving independent sitting and prolonged ventilator-free survival, while safety profiles are generally manageable and distinct for each therapy. Similar outcomes have been demonstrated for presymptomatic patients with SMA. The introduction of DMDs has transformed the prognosis of SMA, particularly for early-onset forms, with robust evidence supporting their efficacy and safety. Continued real-world monitoring and exploration of adjunctive therapies are essential to optimize outcomes across the SMA setting and address unmet needs in non-responders and older patients. Full article