Neonicotinoids, sometimes abbreviated as neonics, represent a class of neuro-active insecticides with chemical similarities to nicotine. Neonicotinoids are the most widely adopted group of insecticides globally since their discovery in the late 1980s. Their physiochemical properties surpass those of previously established insecticides, contributing to their popularity in various sectors such as agriculture and wood treatment. The environmental impact of neonicotinoids, often overlooked, underscores the urgency to develop tools for their detection and understanding of their behavior. Conventional methods for pesticide detection have limitations. Chromatographic techniques are sensitive but expensive, generate waste, and require complex sample preparation. Bioassays lack specificity and accuracy, making them suitable as preliminary tests in conjunction with instrumental methods. Aptamer-based biosensor is recognized as an advantageous tool for neonicotinoids detection due to its rapid response, user-friendly nature, cost-effectiveness, and suitability for on-site detection. This comprehensive review represents the inaugural in-depth analysis of advancements in aptamer-based biosensors targeting neonicotinoids such as imidacloprid, thiamethoxam, clothianidin, acetamiprid, thiacloprid, nitenpyram, and dinotefuran. Additionally, the review offers valuable insights into the critical challenges requiring prompt attention for the successful transition from research to practical field applications.

The detection of biomarkers is of great significance for medical diagnosis, food safety, environmental monitoring, and agriculture. However, bio-detection technology at present often necessitates complex instruments, expensive reagents, specialized expertise, and prolonged procedures, making it challenging to fulfill the demand for rapid, sensitive, user-friendly, and economical testing. In contrast, lateral flow strip (LFS) technology offers simple, fast, and visually accessible detection modality, allowing real-time analysis of clinical specimens, thus finding widespread utility across various domains. Within the realm of LFS, the application of aptamers as molecular recognition probes presents distinct advantages over antibodies, including cost-effectiveness, smaller size, ease of synthesis, and chemical stability. In recent years, aptamer-based LFS has found extensive application in qualitative, semi-quantitative, and quantitative detection across food safety, environmental surveillance, clinical diagnostics, and other domains. This review provided a concise overview of different aptamer screening methodologies, selection strategies, underlying principles, and procedural, elucidating their respective advantages, limitations, and applications. Additionally, we summarized recent strategies and mechanisms for aptamer-based LFS, such as the sandwich and competitive methods. Furthermore, we classified LFSs constructed based on aptamers, considering the rapid advancements in this area, and discussed their applications in biological and chemical detection. Finally, we delved into the current challenges and future directions in the development of aptamer and aptamer-based LFS. Although this review was not thoroughly, it would serve as a valuable reference for understanding the research progress of aptamer-based LFS and aid in the development of new types of aptasensors.

OBJECTIVE: This study aims to systematically collect data on cost-effectiveness analyses that assess technologies to treat type I and II spinal muscular atrophy and evaluate their recommendations.
METHODS: A structured electronic search was conducted in 4 databases. Additionally, a complementary manual search was conducted. Complete economic studies that evaluated nusinersen, risdiplam, onasemnogene abeparvovec (OA), and the best support therapy (BST) from the health system\'s perspective were selected. The incremental cost-effectiveness ratios were compared with various thresholds for the analysis. The review was registered a priori in PROSPERO (CRD42022365391).
RESULTS: Twenty studies were included in the analyses. They were all published between 2017 and 2022 and represent the recommendations in 8 countries. Most studies adopted 5, 6, or 10-state Markov models. Some authors took part in multiple studies. Four technologies were evaluated: BST (N = 14), nusinersen (N = 19), risdiplam (N = 5), and OA (N = 9). OA, risdiplam, and nusinersen were considered inefficient compared with the BST. Risdiplam and OA were generally regarded as cost-effective when compared with nusinersen. Because nusinersen is not a cost-effective drug, no recommendation can be derived from this result. Risdiplam and OA were compared in 2 studies that presented opposite results.
CONCLUSIONS: Nusinersen, risdiplam, and OA are being adopted worldwide as a treatment for spinal muscular atrophy. Despite that, the pharmacoeconomic analyses show that the technologies are not cost-effective compared with the BST. The lack of controlled studies for risdiplam and OA hamper any conclusions about their face-to-face comparison.

Cell surface glycans (CSGs) are essential for cell recognition, adhesion, and invasion, and they also serve as disease biomarkers. Traditional CSG recognition using lectins has limitations such as limited specificity, low stability, high cytotoxicity, and multivalent binding. Aptamers, known for their specific binding capacity to target molecules, are increasingly being employed in the biosensing of CSGs. Aptamers offer the advantage of high flexibility, small size, straightforward modification, and monovalent recognition, enabling their integration into the profiling of CSGs on living cells. In this review, we summarize representative examples of aptamer-based CSG biosensing and identify two strategies for harnessing aptamers in CSG detection: direct recognition based on aptamer-CSG binding and indirect recognition through protein localization. These strategies enable the generation of diverse signals including fluorescence, electrochemical, photoacoustic, and electrochemiluminescence signals for CSG detection. The advantages, challenges, and future perspectives of using aptamers for CSG biosensing are also discussed.

Animal diseases often have significant consequences due to the unclear and time-consuming diagnosis process. Furthermore, the emergence of new viral infections and drug-resistant pathogens has further complicated the diagnosis and treatment of viral diseases. Aptamers, which are obtained through systematic evolution of ligands by exponential enrichment (SELEX) technology, provide a promising solution as they enable specific identification and binding to targets, facilitating pathogen detection and the development of novel therapeutics. This review presented an overview of aptasensors for animal virus detection, discussed the antiviral activity and mechanisms of aptamers, and highlighted advancements in aptamer-based antiviral research following the COVID-19 pandemic. Additionally, the challenges and prospects of aptamer-based virus diagnosis and treatment research were explored. Although this review was not exhaustive, it offered valuable insights into the progress of aptamer-based antiviral drug research, target mechanisms, as well as the development of novel antiviral drugs and biosensors.

Heavy metal ion contamination poses significant environmental and health risks, necessitating rapid and efficient detection methods. In the last decade, colorimetric aptasensors have emerged as powerful tools for heavy metal ion detection, owing to their notable attributes such as high specificity, facile synthesis, adaptability to modifications, long-term stability, and heightened sensitivity. This comprehensive overview summarizes the key developments in this field over the past ten years. It discusses the principles, design strategies, and innovative techniques employed in colorimetric aptasensors using nanomaterials. Recent advancements in enhancing sensitivity, selectivity, and on-site applicability are highlighted. The review also presents application studies of successful heavy metal ion detection using colorimetric aptasensors, underlining their potential for environmental monitoring and health protection. Finally, future directions and challenges in the continued evolution of these aptasensors are outlined.

Mycotoxins are toxic metabolites produced by fungi in the process of infecting agricultural products, posing serious threat to the health of human and animals. Thus, sensitive and reliable analytical techniques for mycotoxin detection are needed. Biosensors equipped with antibodies or aptamers as recognition elements and core-shell nanoparticles (NPs) for the pre-treatment and detection of mycotoxins have been extensively studied. By comparison with monocomponent NPs, core-shell nanostructures exhibit unique optical, electric, magnetic, plasmonic, and catalytic properties due to the combination of functionalities and synergistic effects, resulting in significant improvement of sensing capacities in various platforms, such as surface-enhanced Raman spectroscopy, fluorescence, lateral flow immunoassay and electrochemical sensors. This review focused on the development of core-shell NPs based biosensors for the sensitive and accurate detection of mycotoxins in food samples. Recent developments were categorised and summarised, along with detailed discussion of advantages and shortcomings. The future potential of utilising core-shell NPs in food safety testing was also highlighted.

Computational analysis of RNA sequences constitutes a crucial step in the field of RNA biology. As in other domains of the life sciences, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction in recent years. Historically, thermodynamics-based methods were widely employed for the prediction of RNA secondary structures; however, machine learning-based approaches have demonstrated remarkable advancements in recent years, enabling more accurate predictions. Consequently, the precision of sequence analysis pertaining to RNA secondary structures, such as RNA-protein interactions, has also been enhanced, making a substantial contribution to the field of RNA biology. Additionally, artificial intelligence and machine learning are also introducing technical innovations in the analysis of RNA-small molecule interactions for RNA-targeted drug discovery and in the design of RNA aptamers, where RNA serves as its own ligand. This review will highlight recent trends in the prediction of RNA secondary structure, RNA aptamers and RNA drug discovery using machine learning, deep learning and related technologies, and will also discuss potential future avenues in the field of RNA informatics.

Since cells are the basic structural and functional units of organisms, the detection or quantitation of cells is one of the most common basic problems in life science research. The established cell detection techniques mainly include fluorescent dye labeling, colorimetric assay, and lateral flow assay, all of which employ antibodies as cell recognition elements. However, the widespread application of the established methods generally dependent on antibodies is limited, because the preparation of antibodies is complicated and time-consuming, and unrecoverable denaturation is prone to occur with antibodies. By contrast, aptamers that are generally selected through the systematic evolution of ligands by exponential enrichment can avoid the disadvantages of antibodies due to their controllable synthesis, thermostability, and long shelf life, etc. Accordingly, aptamers may serve as novel molecular recognition elements like antibodies in combination with various techniques for cell detection. This paper reviews the developed aptamer-based cell detection methods, mainly including aptamer-fluorescent labeling, aptamer-isothermal amplification assay, electrochemical aptamer sensor, aptamer-based lateral flow analysis, and aptamer-colorimetric assay. The principles, advantages, progress of application in cell detection and future development trend of these methods were specially discussed. Overall, different assays are suitable for different detection purposes, and the development of more accurate, economical, efficient, and rapid aptamer-based cell detection methods is always on the road in the future. This review is expected to provide a reference for achieving efficient and accurate detection of cells as well as improving the usefulness of aptamers in the field of analytical applications.

Among polysaccharides of environmental and economic interest, chitosan (CS) is receiving much attention, particularly in the food and biotechnology industries to encapsulate active food ingredients and immobilize enzymes. CS nanoparticles (CS NPs) combine the intrinsic beneficial properties of both natural polymers and nanoscale particles such as quantum size effect, biocompatibility, biodegradability, and ease of modification, possessing enhanced capacity for bioimaging, drug delivery, and biosensing applications. Aptamers are single-stranded oligonucleotides that can fold into predetermined structures and bind to the corresponding biomolecules. They are mainly used as targeting ligands in biosensors, disease diagnostic kits, and treatment strategies. They can deliver contrast agents and drugs into cancer cells and tissues, control microorganism growth, and also precisely target pathogens. Aptamer-conjugated CS NPs can significantly improve the efficacy of conventional therapies, minimize their side effects on normal tissues, and overcome the enhanced permeability retention (EPR) effect. Further, aptamer-conjugated carbohydrate-based nanobiopolymers have shown excellent antibacterial and antiviral properties and can be used to develop novel biosensors for the efficient detection of antibiotics, toxins, and other biomolecules. This updated review aims to provide a comprehensive overview of the bioapplications of aptamer-conjugated CS NPs used as innovative diagnostic and therapeutic platforms, their limitations, and potential future directions.