搜索结果：Biosensors

Genetically encoded fluorescent biosensors frequently use Förster resonance energy transfer (FRET) between donor and acceptor fluorescent proteins (FPs) as readouts for monitoring molecular activities in live cells. Here, we present a protocol for determining FRET efficiency through the simultaneous imaging of multiple FRET biosensors alongside donor and acceptor FPs using spectrally orthogonal fluorescent cell barcodes. We describe steps for culturing and transfecting cells, acquiring and analyzing images, and calculating FRET efficiency. This approach facilitates simultaneous analysis of multiple FRET biosensors. For complete details on the use and execution of this protocol, please refer to Wu et al.1.

Food products are highly vulnerable to fungal contamination throughout storage, transportation, and processing, leading to the accumulation of mycotoxins that pose significant risks to food safety and public health. Therefore, there is an urgent need to develop sensitive, rapid, and reliable detection tools. Visual detection enables real-time monitoring of mycotoxin contamination using miniaturized equipment, offering advantages such as simple operation, user-friendliness, fast detection speed, and high sensitivity. As a result, it has gained increasing favor among researchers and practitioners across various fields. This review summarizes recent advances in visual detection methods for mycotoxins, including colorimetric, fluorescent, electrochemiluminescent, and photoelectrochromic visualization approaches. For each category, the design principles, representative applications, key advantages, and inherent limitations are systematically analyzed. Finally, the key scientific and technological challenges currently facing this field are critically examined, and the emerging opportunities arising from the integration of visual biosensing with big data analytics and machine learning are highlighted. This review is intended to serve as a valuable reference for the development of novel visual biosensors for mycotoxin detection and for the broader application of next-generation visual biosensors in on-site mycotoxin monitoring.

Lung cancer is a highly prevalent and lethal malignant tumor worldwide, accounting for approximately 25% of all cancer deaths. Early symptoms are often subtle, leading to late-stage diagnosis in the majority of patients and a missed window for optimal treatment. Therefore, more sensitive diagnostic approaches are urgently required to improve survival rates and reduce the disease burden. Compared with traditional imaging and tissue biopsy, novel biosensors have become important tools for lung cancer diagnosis due to their high sensitivity, non-invasiveness and rapid detection abilities. Aptamers, a class of single-stranded DNA/RNA molecules capable of specific target recognition, are ideal for the development of efficient lung cancer biosensors owing to their low synthesis cost, high stability, minimal immunogenicity, and ease of modification. This review focuses on the application of aptamers in lung cancer detection, summarizes current developments in aptamer-based sensors (aptasensors), and critically compares the analytical performance, clinical limitations and translational obstacles of five mainstream aptasensor platforms, then discusses their challenges and future perspectives, aiming to promote more accurate and efficient early-diagnostic techniques for lung cancer.

Nano-biosensors represent innovative analytical devices that couple nanotechnology with biomolecular recognition elements to detect specific targets with high sensitivity and selectivity. By incorporating nanomaterials such as gold, carbon, or metal oxides, these devices exhibit enhanced conductivity, larger surface areas, and improved electron transfer, thereby enabling rapid and accurate detection even at ultralow concentrations. Electrochemical nano-biosensors are particularly advantageous for medical diagnostics, health monitoring, and environmental applications because they convert bioreceptor-analyte interactions into measurable real-time electrical signals. Due to their ability to monitor key biomarkers, including neurotransmitters, these sensors hold immense promise for early disease diagnosis, therapeutic monitoring, and neurological research. This review highlights current trends in the development of nanomaterial-enhanced electrochemical sensors for neurotransmitter detection, focuses on their performance and clinical translation potential, and outlines future directions to address challenges in selectivity, stability, and large-scale manufacturing.

Surface-layer (S-layer) proteins, forming the outermost envelope of many bacteria and archaea, exhibit extraordinary structural precision and self-assemble into two-dimensional crystalline lattices with square, hexagonal, or oblique symmetry. These monomolecular arrays, typically 5 to 25 nm in periodicity (varying by species), offer defined porosity and serve as robust biological nanoplatforms. Their innate capacity for self-assembly and molecular ordering has attracted significant attention in nanobiotechnology, vaccine development, biosensing, drug delivery, and ultrafiltration. S-layers are especially valued for their ability to mimic viral capsids, enhance antigen presentation, stabilize lipid bilayers, and provide highly organized scaffolds for enzyme immobilization and nanopatterning. Recent experimental achievements include the use of S-layer fusion proteins for mucosal vaccine delivery and the development of recombinant S-layer-based electrochemical biosensors. However, transitioning these advances to commercial-scale applications remains challenging. Limitations include the scalability of high-purity protein production, cost-effective recombinant expression, stability under harsh industrial conditions, and unresolved regulatory pathways for biologically derived nanomaterials. Additionally, synthetic alternatives present practical and economic competition. Nonetheless, interdisciplinary efforts in synthetic biology, materials science, and computational modeling are addressing these bottlenecks. Innovations such as cross-linkable domains, fusion with polymers or lipids, and predictive structure-function modeling are improving the robustness and adaptability of S-layer systems. As current research advances from theoretical potential to functional prototypes, S-layer proteins offer transformative prospects across medical, industrial, and environmental domains. This review uniquely integrates mechanistic S-layer biology with engineering-for-manufacture, protein-design workflows, and commercialization roadmaps - offering actionable protocols and benchmarks not covered in prior syntheses.

Adaptive bioelectronics that autonomously adjust to environmental changes represent an emerging paradigm, enabling reliable operation across diverse conditions. Hypoxic microenvironments are prevalent across numerous pathological conditions including chronic wounds, tumors, and ischemic tissues, creating a fundamental challenge: oxygen-dependent enzymatic biosensors fail precisely when monitoring is most critical, while oxygen deficiency simultaneously impairs tissue regeneration. We present a soft wireless Hypoxia-Adaptive Sensing and Therapeutic (HAST) system that maintains reliable biosensing functionality in oxygen-deficient environments through integrated oxygen management. Using engineered poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS)/polydopamine (PDA)/enzyme biocomposites, HAST integrates multiplexed biosensing (glucose, uric acid, lactate) with dual-oxygen provision: wound exudate-triggered dissolved oxygen generation restores biosensor functionality while electrical stimulation promotes vascular regeneration for sustained tissue oxygenation. This hypoxia-adaptive design achieves about 10-fold biosensor sensitivity enhancement under oxygen-deficient conditions while promoting tissue repair. In preclinical diabetic wound models, HAST enabled accurate continuous monitoring with ∼30% accelerated wound closure, demonstrating environment-adaptive bioelectronics for precision medicine in oxygen-deficient pathological conditions.

Quorum sensing (QS) orchestrates virulence, biofilm maturation, and antimicrobial tolerance across clinically dominant pathogens, driving chronic infections and therapeutic failure. Although quorum-sensing inhibitors (QSIs) were developed to attenuate pathogenic coordination without bactericidal pressure, their clinical translation has been constrained by biochemical instability, narrow receptor specificity, limited pharmacokinetic robustness, and emerging adaptive resistance. Molecularly imprinted polymers (MIPs) provide a mechanistically distinct strategy based on structurally defined recognition cavities capable of physically sequestering or catalytically degrading autoinducers with measurable thermodynamic parameters, including the imprinting factor (IF), dissociation constant (K d), and binding capacity. This review critically synthesizes advances in molecularly imprinted polymer design for QS detection and modulation, emphasizing the role of monomer-template complementarity, cross-link density, porogen environment, polymerization strategy, and template removal in governing recognition fidelity and biological performance. Computational modeling has improved monomer selection and prepolymerization complex prediction, yet translational reliability requires integration of solvent dynamics, cross-linker effects, and matrix competition under physiologically relevant conditions. Compared with conventional biosensors and small-molecule QSIs, MIPs demonstrate nanomolar detection limits, resilience in complex media, and up to 80% biofilm inhibition through signal sequestration. Early in vivo studies further support their potential to attenuate the QS-dependent virulence. Despite these advances, barriers remain, including monomer cytotoxicity, nonspecific adsorption in biological fluids, incomplete biodegradation profiling, and the need for standardized in vivo validation frameworks. With rational engineering and regulatory alignment, MIPs represent a programmable materials platform for communication-based infection control, expanding the antivirulence paradigm beyond receptor antagonism toward structurally resilient quorum interception.

To explore the research trends of microfluidic technology for cancer diagnosis from 2015 to 2024 using bibliometric and visualization methods (not a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-compliant systematic review), and provide references for subsequent scientific research. Relevant literatures were retrieved from the Web of Science Core Collection, and analyzed using tools such as Origin 2018, R software, VOSviewer, and CiteSpace. The cooperation network, co - citation network, and keyword co - occurrence network was constructed. A total of 897 literatures were included. The number of literatures first increased, then decreased, and then increased again, reaching a peak in 2023. China had the highest literature output (358 articles), but the international co - authorship rate was low (19%). Biosensors & Bioelectronics had high publication and citation numbers. The research hotspots were the isolation and detection of circulating tumor cells (with a focus on breast cancer, colorectal cancer, and lung cancer, accounting for 36%) and microfluidic analysis of exosomes (accounting for 24%). Keyword clustering involved microfluidic device materials, tumor cell detection, exosome applications, and cancer mechanism research. The research direction shifted from broad-based technology to precise applications for specific cancers and samples. This study clarified the research status and hotspots in this field. Microfluidic technology contributes to the early and accurate diagnosis of cancer. In the future, international cooperation should be strengthened to explore more potential of microfluidic technology in cancer diagnosis and improve the level of early diagnosis.

Plant growth, stress adaptation, and productivity depend on the continuous exchange of information between hormone signaling and metabolic networks. Although major phytohormones have been widely studied through their biosynthesis, receptors, and downstream transcriptional modules, these pathways are still often presented as linear systems. This view does not fully explain how plants integrate carbon status, nutrient availability, redox balance, cellular energy, and developmental signals under changing environments. In this review, we present plant hormone signaling and metabolism as a reciprocal regulatory network in which hormones reshape metabolic flux, while metabolites feedback to control hormone biosynthesis, transport, perception, degradation, and signal output. We synthesized evidence across salicylic acid, gibberellins, auxin, abscisic acid, strigolactones, ethylene, jasmonates, cytokinins, brassinosteroids, and melatonin, showing that sugars, amino acids, organic acids, lipid derivatives, sulfur metabolites, and redox signals act as shared regulatory nodes. This integrated perspective reveals that core metabolic signals such as sucrose, trehalose-6-phosphate, 2-oxoglutarate, citrate, malate, reactive oxygen species, glutathione, ascorbate, cysteine, and tryptophan coordinate multiple hormone pathways across tissues, developmental stages, and stress contexts. We further highlight emerging tools, including hormone atlases, live biosensors, spatial omics, single-cell omics, isotope tracing, genome editing, and computational network modeling, as essential approaches for moving from descriptive pathway maps to predictive systems biology. By defining hormone metabolism crosstalk as a central principle in plant biochemistry and physiology, this review provides a conceptual framework for identifying engineering targets that can improve crop resilience, nutrient use efficiency, and growth stress balance under future agricultural conditions.

Bacterial infections remain a significant threat to public health worldwide, driving an urgent need for rapid, accurate, and field-deployable diagnostic techniques. Point-of-care testing (POCT) has emerged as a transformative strategy, providing timely detection, operational simplicity, and portability. Recent studies have aimed at enhancing sensitivity, specificity, multiplexing capability, and automation through the integration of molecular diagnostics with microfluidics and lab-on-chip technologies, alongside the development of low-cost, portable devices equipped with smartphone-based readout and cloud connectivity for real-time surveillance in resource-limited settings. Nonetheless, evidence-based frameworks for selecting optimal detection targets-such as genomic sequences, conserved protein epitopes, or viable whole cells-and matching them to appropriate POCT modalities remain notably underrepresented in the literature. This review systematically summarizes recent advances in POCT strategies for bacterial detection, categorized according to three major types of detection targets, including cellular phenotypic characteristics, surface antigens, and nucleic acids. We discuss the principles, advantages, limitations, and representative applications of key POCT platforms, which include microscopy-based visualization, immunoassays, isothermal amplification, clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) systems, and microfluidic biosensors. Critical challenges, such as sample pretreatment, detection sensitivity, and operational simplicity, have been partially addressed through recent innovations. Finally, we outline the main future research directions focused on the development of integrated, automated, and intelligent POCT systems for clinical deployment. 细菌感染已成为全球性重大公共卫生威胁，亟需发展快速、准确、可现场化的诊断技术。即时检测（POCT）技术凭借其检测及时、操作简便和便携等优势，已成为应对细菌感染的变革性技术。POCT通过将分子诊断与微流控芯片技术相结合，提升了细菌检测的灵敏度、特异性、多重检测能力和自动化水平;同时，伴随着低成本、便携式检测装置不断涌现，以及智能手机读取信号与云端传输数据等技术的融合，POCT为在资源受限的场景下实时监测病原菌提供了可行性。然而，如何选择最优检测靶标（例如，基因组序列、保守蛋白表位或存活细胞）并构建与之匹配的POCT技术，相关综述尚不充分。本综述系统总结了用于细菌检测的POCT策略的最新进展，并依据三类主要检测目标（细胞表型特征、表面抗原和核酸）进行分类;评述了可视化显微镜成像技术、免疫检测方法、等温核酸扩增技术、成簇规律间隔短回文重复序列及其关联蛋白系统（CRISPR-Cas）系统以及微流控生物传感器等POCT平台的检测原理、优势、局限性及代表性生物医学应用，展示了POCT技术在样品前处理、检测灵敏度和操作简便性等关键环节上取得的阶段性突破;最后提出了当前POCT技术面向临床实际需求所面临的挑战，并展望了未来聚焦于构建集成化、自动化、智能化POCT系统的发展趋势。.

Hematological malignancies remain one of the leading causes of morbidity and mortality despite advances in targeted therapies, immunotherapy, and stem cell transplantation. Emerging evidence indicates that treatment efficacy and toxicity depend not only on the choice of therapy but also on its timing relative to the patient's internal circadian rhythm. The circadian clock orchestrates fundamental processes in hematopoiesis and immunity, such as stem-cell proliferation, leukocyte trafficking, DNA repair, and drug metabolism, while its disruption promotes malignant transformation, therapeutic resistance, and systemic toxicity. This narrative review synthesizes current understanding of circadian regulation in hematopoietic and immune systems, the mechanistic and preclinical foundations of chronotherapy in blood cancers, and the limited but growing body of clinical evidence linking treatment timing with outcome in leukemia, lymphoma, and transplantation. The review also examines practical challenges, including inter-individual variability, disease-induced circadian disruption, and hospital workflow constraints, while highlighting emerging technologies, such as transcriptomic clocks, wearable biosensors, and AI-driven scheduling algorithms, that are poised to enable personalized, time-aware therapy. By integrating temporal precision into existing therapeutic frameworks, chronotherapy may represent a promising investigational dimension of precision medicine in hematological oncology. However, its clinical value remains to be defined through prospective studies that incorporate validated circadian biomarkers, predefined timing windows, and clinically meaningful efficacy and toxicity endpoints.

Chemoattractant gradients guide cell migration in immunity, tissue repair, and development, yet their spatial and temporal distribution remains difficult to measure. In this review, we discuss how the field is moving beyond static source maps and indirect cellular proxies toward direct visualization of extracellular guidance cues. We outline the strengths and limitations of classical approaches for inferring chemoattractant gradients and highlight new strategies provided by genetically encoded chemoattractant indicators (GECHIs). Emerging PBP- and GPCR-based biosensors enable continuous visualization and localization of extracellular ligands in living tissues using fluorescence intensity- or lifetime-based readouts. Although the current toolbox is limited to a small number of chemoattractants, ongoing sensor development is likely to expand ligand coverage and enable multiplexed measurements with spectrally distinct sensors in the near future.