In recent years, nanoscale detection has played an increasingly important role in the research on viruses, exosomes, small bacteria, and organelles. The small size and complex biological natures of these particles, with the smallest known virus particle measuring only 17 nm in diameter and exosomes ranging from 30 nm to 150 nm in size, pose challenges to the classical large-scale (typically micron-scale) characterization methods, which has become a major obstacle in the research. The emergence of nanoscale detection and analysis technologies has filled the gap of optical microscopy, a conventional technique in this field. These technologies enable the sensitive and robust detection of objects that exceed the lower limit of optical detection, revealing the molecular composition and biological roles simultaneously. Currently, several commercialized instruments based on nanotechnology have emerged, providing complete single-particle detection solutions and achieving unique functionality based on their respective technological advantages. However, it is inevitable that these technologies have limitations in terms of application and detection capabilities, as they continue to evolve. This paper offers a thorough overview of the principles, advantages, limitations, and future development trends of several mainstream commercial instruments, aiming to serve researchers in selecting and utilizing these technologies.

Objective.Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children. While numerous intelligent methods are applied for its subjective diagnosis, they seldom consider the consistency problem of ADHD biomarkers. In practice, these data-driven approaches lead to varying learned features for ADHD classification across diverse ADHD datasets. This phenomenon significantly undermines the reliability of identified biomarkers and hampers the interpretability of these methods.Approach.In this study, we propose a cross-dataset feature selection (FS) module using a grouped SVM-based recursive feature elimination approach (G-SVM-RFE) to enhance biomarker consistency across multiple datasets. Additionally, we employ connectome gradient data for ADHD classification. In details, we introduce the G-SVM-RFE method to effectively concentrate gradient components within a few brain regions, thereby increasing the likelihood of identifying these regions as ADHD biomarkers. The cross-dataset FS module is integrated into an existing binary hypothesis testing (BHT) framework. This module utilizes external datasets to identify global regions that yield stable biomarkers. Meanwhile, given a dataset which waits for implementing the classification task as local dataset, we learn its own specific regions to further improve the performance of accuracy on this dataset.Main results.By employing this module, our experiments achieve an average accuracy of 96.7% on diverse datasets. Importantly, the discriminative gradient components primarily originate from the global regions, providing evidence for the significance of these regions. We further identify regions with the high appearance frequencies as biomarkers, where all the used global regions and one local region are recognized.Significance.These biomarkers align with existing research on impaired brain regions in children with ADHD. Thus, our method demonstrates its validity by providing enhanced biological explanations derived from ADHD mechanisms.

Biomarkers are crucial physiological and pathological indicators in the host. Over the years, numerous detection methods have been developed for biomarkers, given their significant potential in various biological and biomedical applications. Among these, the detection system based on functionalized DNA origami has emerged as a promising approach due to its precise control over sensing modules, enabling sensitive, specific, and programmable biomarker detection. We summarize the advancements in biomarker detection using functionalized DNA origami, focusing on strategies for DNA origami functionalization, mechanisms of biomarker recognition, and applications in disease diagnosis and monitoring. These applications are organized into sections based on the type of biomarkers - nucleic acids, proteins, small molecules, and ions - and concludes with a discussion on the advantages and challenges associated with using functionalized DNA origami systems for biomarker detection.

Porous organic frameworks (POFs) represent a significant subclass of nanoporous materials in the field of materials science, offering exceptional characteristics for advanced applications. Covalent organic frameworks (COFs), as a novel and intriguing type of porous material, have garnered considerable attention due to their unique design capabilities, diverse nature, and wide-ranging applications. The unique structural features of COFs, such as high surface area, tuneable pore size, and chemical stability, render them highly attractive for various applications, including targeted and controlled drug release, as well as improving the sensitivity and selectivity of electrochemical biosensors. Therefore, it is crucial to comprehend the methods employed in creating COFs with specific properties that can be effectively utilized in biomedical applications. To address this indispensable fact, this review paper commences with a concise summary of the different methods and classifications utilized in synthesizing COFs. Second, it highlights the recent advancements in COFs for drug delivery, including drug carriers as well as the classification of drug delivery systems and biosensing, encompassing drugs, biomacromolecules, small biomolecules and the detection of biomarkers. While exploring the potential of COFs in the biomedical field, it is important to acknowledge the limitations that researchers may encounter, which could impact the practicality of their applications. Third, this paper concludes with a thought-provoking discussion that thoroughly addresses the challenges and opportunities associated with leveraging COFs for biomedical applications. This review paper aims to contribute to the scientific community\'s understanding of the immense potential of COFs in improving drug delivery systems and enhancing the performance of biosensors in biomedical applications.

Conventional molecularly imprinted polymers (MIPs) perform their functions principally depended on their three dimensional (3D) imprinted cavities (recognition sites) of templates. Here, retaining the function of recognition sites resulted from the imprinting of template molecules, the role of functional monomers is explored and expanded. Briefly, a class of dual-functional renin imprinted poly(methyldopa) (RMIP) is prepared, consisting of a drug-type function monomer (methyldopa, clinical high blood pressure drug) and a corresponding disease biomarker (renin, biomarker for high blood pressure disease). To boost target-to-receptor binding ratio and sensitivity, the microstructure of recognition sites is beforehand calculated and designed by Density Functional Theory calculations, and the whole interfacial structure, property and thickness of RMIP film is regulated by adjusting the polymerization techniques. The dual-functional applications of RMIP for biomarker detection and disease therapy in vivo is explored. Such RMIP-based biosensors achieves highly sensitive biomarker detection, where the LODs reaches down to 1.31 × 10-6 and 1.26 × 10-6 ng mL-1 for electrochemical and chemical polymers, respectively, and the application for disease therapy in vivo has been verified where displays the obviously decreased blood pressure values of mice. No acute and long-term toxicity is found from the pathological slices, declaring the promising clinical application potential of such engineered RMIP nanostructure.

Solid-state nanochannel-based sensing systems have been established as vigorous tools for sensing plentiful biomarkers due to their label-free, highly sensitive, and high-throughput screening. However, research on solid-state nanochannels has predominantly centered on the functional groups modified on the inner wall, neglecting investigations into the outer surface. Actually, the outer surface, as a part of the nanochannels, also plays a key role in regulating ionic current. When the target nears the entrance of the nanochannel and prepares to pass through, it would also interact with functional groups located on the nanochannel\'s outer surface, leading to subsequent alterations in the ionic current. Recently, the probes on the outer surface have experimentally demonstrated their ability to independently regulate ionic current, unveiling advantages in in situ target detection, especially for targets larger than the diameter of the nanochannels that cannot pass through them. Here, we review the progress over the past decade in nanochannels featuring diverse outer-surface functionalization aimed at enhanced sensing performance, including charge modification, wettability adjustment, and probe immobilization. In addition, we present the promises and challenges posed by outer-surface functionalized nanochannels and discuss possible directions for their future deployments.

As one of the major public health problems, cancers seriously threaten the human health. Among them, lung cancer is considered to be one of the most life-threatening malignancies. Therefore, developing early diagnosis technology and timely treatment for lung cancer is urgent. Recent research has witnessed that measuring changes of biomarkers expressed in lung cancer has practical significance. Meanwhile, we note that bioimaging with organic fluorescent probes plays an important role for its high sensitivity, real-time analysis and simplicity of operation. In the past years, kinds of organic fluorescent probes targeting lung cancer related biomarker have been developed. Herein, we summarize the research progress of organic fluorescent probes for the detection of lung cancer related biomarkers in this review, along with their design principle, luminescence mechanism and bioimaging application. Additionally, we put forward some challenges and future prospects from our perspective.

Breast cancer (BC) is one of the most common malignant tumors in women worldwide, and its incidence is increasing every year. Early diagnosis and treatment are critical to improve the curability and prognosis of patients. However, existing detection methods often suffer from insufficient sensitivity and specificity, which limits their clinical application. Fortunately, the rapid development of nanotechnology offers new possibilities for diagnosing BC. For example, the unique physicochemical properties of gold nanomaterials (Au NMs), such as fascinating optical properties and quantum size effect, along with excellent biocompatibility and modifiability, enable them to manifest great potential in the field of biosensing, especially in the detection of BC biomarkers. Through fine surface modification and functionalization, Au NMs can accurately bind to specific antibodies, nucleic acids, and other biomolecules, thus achieving sensitive and precise detection of specific biomarkers. Here, we focus on the research progress of Au NMs as a key biosensing vector in BC biomarker detection. From four major perspectives of early diagnosis, prognostic evaluation, risk prediction, and bioimaging applications, we have thoroughly analyzed the broad application of Au NMs in BC biomarker detection and prospectively addressed its possible future trends. We hope this review will provide more comprehensive ideas for future researchers and promote the further development of this field.

Metal-organic frameworks (MOFs) porous material have obtained more and more attention during the past decade. Among various MOFs materials, luminescent MOFs with specific chemical characteristics and excellent optical properties have been regarded as promising candidates in the research of cancer biomarkers detection and bioimaging. Therefore, the latest advances and the principal biosensing and imaging strategies based on the luminescent MOFs were discussed in this review. The effective synthesis methods of luminescent MOFs were emphasized firstly. Subsequently, the luminescent principle of MOFs has been summarized. Furthermore, the luminescent MOF-based sensing mechanisms have been highlighted to provide insights into the design of biosensors. The designability of LMOFs was suitable for different needs of biorecognition, detection, and imaging. Typical examples of luminescent MOF in the various cancer biomarkers detection and bioimaging were emphatically introduced. Finally, the future outlooks and challenges of luminescent MOF-based biosensing systems were proposed for clinical cancer diagnosis.

Molecularly imprinted polymers (MIPs) are the equivalent of natural antibodies and have been widely used as synthetic receptors for the detection of disease biomarkers. Benefiting from their excellent chemical and physical stability, low-cost, relative ease of production, reusability, and high selectivity, MIP-based electrochemical sensors have attracted great interest in disease diagnosis and demonstrated superiority over other biosensing techniques. Here we compare various types of MIP-based electrochemical sensors with different working principles. We then evaluate the state-of-the-art achievements of the MIP-based electrochemical sensors for the detection of different biomarkers, including nucleic acids, proteins, saccharides, lipids, and other small molecules. The limitations, which prevent its successful translation into practical clinical settings, are outlined together with the potential solutions. At the end, we share our vision of the evolution of MIP-based electrochemical sensors with an outlook on the future of this promising biosensing technology.