Epidermal secretion-purified biosensing patch with hydrogel sebum filtering membrane and unidirectional flow microfluidic channels.

The development of biosensing electronics for real-time sweat analysis has attracted increasing research interest due to their promising applications for non-invasive health monitoring. However, one of the critical challenges lies in the sebum interference that largely limits the sensing reliability in practical scenarios. Herein, we report a flexible epidermal secretion-purified biosensing patch with a hydrogel filtering membrane that can effectively eliminate the impact of sebum and sebum-soluble substances. The as-prepared sebum filtering membranes feature a dual-layer sebum-resistant structure based on the poly(hydroxyethyl methacrylate) hydrogel functionalized with nano-brush structured poly(sulfobetaine) to eliminate interferences and provide self-cleaning capability. Furthermore, the unidirectional flow microfluidic channels design based on the Tesla valve was incorporated into the biosensing patch to prevent external sebum contamination and allow effective sweat refreshing for reliable sensing. By seamlessly combining these components, the epidermal secretion-purified biosensing patch enables continuous monitoring of sweat uric acid, pH, and sodium ions with significantly improved accuracy of up to 12 %. The proposed strategy for enhanced sweat sensing reliability without sebum interference shows desirable compatibility for different types of biosensors and would inspire the advances of flexible and wearable devices for non-invasive healthcare.

Electrochemical biosensors for early detection of breast cancer.

Breast cancer continues to be a significant contributor to global cancer deaths, particularly among women. This highlights the critical role of early detection and treatment in boosting survival rates. While conventional diagnostic methods like mammograms, biopsies, ultrasounds, and MRIs are valuable tools, limitations exist in terms of cost, invasiveness, and the requirement for specialized equipment and trained personnel. Recent shifts towards biosensor technologies offer a promising alternative for monitoring biological processes and providing accurate health diagnostics in a cost-effective, non-invasive manner. These biosensors are particularly advantageous for early detection of primary tumors, metastases, and recurrent diseases, contributing to more effective breast cancer management. The integration of biosensor technology into medical devices has led to the development of low-cost, adaptable, and efficient diagnostic tools. In this framework, electrochemical screening platforms have garnered significant attention due to their selectivity, affordability, and ease of result interpretation. The current review discusses various breast cancer biomarkers and the potential of electrochemical biosensors to revolutionize early cancer detection, making provision for new diagnostic platforms and personalized healthcare solutions.

Electrochemical Sensors for Antibiotic Detection: A Focused Review with a Brief Overview of Commercial Technologies.

Antimicrobial resistance (AMR) poses a significant threat to global health, powered by pathogens that become increasingly proficient at withstanding antibiotic treatments. This review introduces the factors contributing to antimicrobial resistance (AMR), highlighting the presence of antibiotics in different environmental and biological matrices as a significant contributor to the resistance. It emphasizes the urgent need for robust and effective detection methods to identify these substances and mitigate their impact on AMR. Traditional techniques, such as liquid chromatography-mass spectrometry (LC-MS) and immunoassays, are discussed alongside their limitations. The review underscores the emerging role of biosensors as promising alternatives for antibiotic detection, with a particular focus on electrochemical biosensors. Therefore, the manuscript extensively explores the principles and various types of electrochemical biosensors, elucidating their advantages, including high sensitivity, rapid response, and potential for point-of-care applications. Moreover, the manuscript investigates recent advances in materials used to fabricate electrochemical platforms for antibiotic detection, such as aptamers and molecularly imprinted polymers, highlighting their role in enhancing sensor performance and selectivity. This review culminates with an evaluation and summary of commercially available and spin-off sensors for antibiotic detection, emphasizing their versatility and portability. By explaining the landscape, role, and future outlook of electrochemical biosensors in antibiotic detection, this review provides insights into the ongoing efforts to combat the escalating threat of AMR effectively.

Portable label-free electrochemical aptasensor for sensitive detection of paraquat herbicide mediated by oxygen reduction reaction.

Paraquat (PQ) is a highly toxic herbicide that has been prohibited in almost 70 countries, but remains in use worldwide. Thus, routine on-site PQ monitoring is a key mechanism to ensure safety and efficiently enforce regulations. Herein, a label-free portable electrochemical aptasensor for the detection of PQ was developed by utilizing aptamer designed to specifically recognize PQ. The aptasensor employs square-wave voltammetry (SWV) to quantify PQ binding on the aptamer-functionalized electrode surface by tracking the downstream oxygen reduction reaction. It provided a detection range spanning from 0.01 to 100.0 µg mL-1 PQ with a limit of detection (LOD) of 8.9 ng mL-1. Validation against spiked tap water, pomegranate juice, and orange juice revealed recovery rate performances of 75 %-130 %. The aptasensor demonstrates promising feasibility for PQ detection in real-world applications, offering remarkable portability and operational simplicity. Notably, it can operate without supplementary redox agents, requiring only sample incubation and subsequent washing steps.

Machine Learning and Wearable Technology: Monitoring Changes in Biomedical Signal Patterns during Pre-Migraine Nights.

Migraine is one of the most common neurological disorders, characterized by moderate-to-severe headache episodes. Autonomic nervous system (ANS) alterations can occur at phases of migraine attack. This study investigates patterns of ANS changes during the pre-ictal night of migraine, utilizing wearable biosensor technology in ten individuals. Various physiological, activity-based, and signal processing metrics were examined to train predictive models and understand the relationship between specific features and migraine occurrences. Data were filtered based on specified criteria for nocturnal sleep, and analysis frames ranging from 5 to 120 min were used to improve the diversity of the training sample and investigate the impact of analysis frame duration on feature significance and migraine prediction. Several models, including XGBoost (Extreme Gradient Boosting), HistGradientBoosting (Histogram-Based Gradient Boosting), Random Forest, SVM, and KNN, were trained on unbalanced data and using cost-sensitive learning with a 5:1 ratio. To evaluate the changes in features during pre-migraine nights and nights before migraine-free days, an analysis of variance (ANOVA) was performed. The results showed that the features of electrodermal activity, skin temperature, and accelerometer exhibited the highest F-statistic values and the most significant p-values in the 5 and 10 min frames, which makes them particularly useful for the early detection of migraines. The generalized prediction model using XGBoost and a 5 min analysis frame achieved 0.806 for accuracy, 0.638 for precision, 0.595 for recall, and 0.607 for F1-score. Despite identifying distinguishing features between pre-migraine and migraine-free nights, the performance of the current model suggests the need for further improvements for clinical application.

Critical Suitability Evaluation of Caco-2 Cells for Gut-on-a-Chip.

Currently, culturing Caco-2 cells in a Gut-on-a-chip (GOC) is well-accepted for developing intestinal disease models and drug screening. However, Caco-2 cells were found to overexpress surface proteins (e.g., P-gp) compared with the normal intestinal epithelial cells in vivo. To critically evaluate the challenge and suitability of Caco-2 cells, a GOC integrated with a carcinoembryonic antigen (CEA) biosensor was developed. This three-electrode system electrochemical sensor detects CEA by antigen-antibody specific binding, and it exhibits high selectivity, excellent stability, and good reproducibility. Under dynamic culturing in the GOC, Caco-2 cells exhibited an intestinal villus-like structure and maintained tissue barrier integrity. Meanwhile, CEA was discovered to be secreted from 0 to 0.22 ng/mL during the 10-day culturing of Caco-2 cells. Especially, CEA secretion increased significantly with the differentiation of Caco-2 cells after 6 days of culturing. The sustained high-level CEA secretion may induce cells to avoid apoptotic stimuli, which faithfully reflects the efficacy of a new drug and the mechanism of intestinal disease. Different kinds of cell types (e.g., intestinal primary cells, stem cell-induced differentiation) in the GOC should be attempted for drug screening in the future.

Sensitive Electrochemical and Thermal Detection of Human Noroviruses Using Molecularly Imprinted Polymer Nanoparticles Generated against a Viral Target.

Norovirus (NoV) is the predominant cause of foodborne illness globally; current detection methods are typically expensive, have inadequate sensitivities, and utilize biological receptors with poor stability. Therefore, accurate, cost-effective, and highly stable detection methods are needed to screen for NoV in foods. We developed molecularly imprinted polymer nanoparticles (nanoMIPs) to detect NoV using a small target epitope (12 amino acids) with a solid-phase synthesis approach. The performance of three batches of nanoMIPs with varying monomer compositions (nanoMIP-1, -2, and -3) were compared both experimentally and computationally. Surface plasmon resonance examined nanoMIP binding affinity to norovirus virus-like particles (NoV-LPs), whereby nanoMIP-1 had the lowest KD value of 0.512 µM. This is significant, as traditional targets for generation of norovirus ligands previously reported were generated against drastically larger norovirus capsid segments that have limitations in ease of production. Further, an electrochemical sensor was developed by covalently attaching the nanoMIPs to glassy carbon electrodes. In agreement with our predictions from density functional theory simulations, electrochemical impedance spectroscopy showed a sensitive response toward NoV-LPs for nanoMIP batches tested; however, nanoMIP-1 was optimal, with an excellent detection limit of 3.4 pg/mL (1.9 × 105 particles/mL). Due to its exceptional performance, nanoMIP-1 was immobilized to screen-printed electrodes and utilized within a thermal sensor, where it exhibited a low detection limit of 6.5 pg/mL (3.7 × 105 particles/mL). Crucially, we demonstrated that nanoMIP-1 could detect NoV in real food samples (romaine lettuce) by using electrochemical and thermal sensors. Consequently, the study highlights the exceptional potential of nanoMIPs to replace traditional biological materials (e.g., antibodies) as sensitive, versatile, and highly stable receptors within NoV sensors.

Imaging the spatial distribution of structurally diverse plant hormones: A comprehensive review.

Plant hormones are essential and structurally diverse molecules that regulate various aspects of plant growth, development, and stress responses. However, the precise analysis of plant hormones in complex biological samples poses a challenge due to their low concentrations, dynamic levels, and intricate spatial distribution. Moreover, the complexity and interconnectedness of hormone signaling networks make it difficult to simultaneously trace multiple hormone distributions. In this review, we provide an overview of the currently recognized small-molecule plant hormones, signal peptide hormones, and plant growth regulators, along with the analytical methods employed for their analysis. We delve into the latest advancements in mass spectrometry imaging and in situ fluorescence techniques, which enable the examination of the spatial distribution of plant hormones. The advantages and disadvantages of these imaging techniques are further discussed. Finally, we propose potential avenues for future research in this field to further enhance our understanding of plant hormone biology.

Emerging sensing, imaging, and computational technologies to scale nano-to macroscale rhizosphere dynamics - Review and research perspectives.

The soil region influenced by plant roots, i.e., the rhizosphere, is one of the most complex biological habitats on Earth and significantly impacts global carbon flow and transformation. Understanding the structure and function of the rhizosphere is critically important for maintaining sustainable plant ecosystem services, designing engineered ecosystems for long-term soil carbon storage, and mitigating the effects of climate change. However, studying the biological and ecological processes and interactions in the rhizosphere requires advanced integrated technologies capable of decoding such a complex system at different scales. Here, we review how emerging approaches in sensing, imaging, and computational modeling can advance our understanding of the complex rhizosphere system. Particularly, we provide our perspectives and discuss future directions in developing in situ rhizosphere sensing technologies that could potentially correlate local-scale interactions to ecosystem scale impacts. We first review integrated multimodal imaging techniques for tracking inorganic elements and organic carbon flow at nano- to microscale in the rhizosphere, followed by a discussion on the use of synthetic soil and plant habitats that bridge laboratory-to-field studies on the rhizosphere processes. We then describe applications of genetically encoded biosensors in monitoring nutrient and chemical exchanges in the rhizosphere, and the novel nanotechnology-mediated delivery approaches for introducing biosensors into the root tissues. Next, we review the recent progress and express our vision on field-deployable sensing technologies such as planar optodes for quantifying the distribution of chemical and analyte gradients in the rhizosphere under field conditions. Moreover, we provide perspectives on the challenges of linking complex rhizosphere interactions to ecosystem sensing for detecting biological traits across scales, which arguably requires using the best-available model predictions including the model-experiment and image-based modeling approaches. Experimental platforms relevant to field conditions like SMART (Sensors at Mesoscales with Advanced Remote Telemetry) soils testbed, coupled with ecosystem sensing and predictive models, can be effective tools to explore coupled ecosystem behavior and responses to environmental perturbations. Finally, we envision that with the advent of novel high-resolution imaging capabilities at nano- to macroscale, and remote biosensing technologies, combined with advanced computational models, future studies will lead to detection and upscaling of rhizosphere processes toward ecosystem and global predictions.

Signal amplification strategy based on target-controlled release of mediator for ultrasensitive self-powered biosensing of acetamiprid.

Self-powered biosensors with high sensitivity have garnered significant interest for their potential applications in the realm of portable sensing. Herein, a self-powered biosensor with a novel signal amplification strategy was developed by integrating target-controlled release of mediator with an enzyme biofuel cell for the ultrasensitive detection of acetamiprid (ACE). Zeolitic imidazolate framework-67 was utilized as both a nanocontainer for capturing the electron mediator 2,2'-azidobis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and a precursor for the synthesis of cobalt nanoparticles/nitrogen, sulfur-codoped carbon nanotubes (Co NPs/NS-CNTs), which were employed as the electrode material for constructing both the glucose oxidase-based bioanode and the laccase-based biocathode. The target analyte ACE can specifically bind to its aptamer, leading to the release of ABTS, which cyclically participates in the catalytic reaction of the biocathode, thereby amplifying the electrochemical signal. By leveraging the benefits of ABTS cyclic catalysis and the effective electrocatalysis of bioelectrodes based on Co NPs/NS-CNTs, the self-powered biosensor has a broad detection range of 0.1-1000 fM and a low detection limit of 25 aM toward ACE. The proposed signal amplification approach presents a promising strategy for enhancing sensitivity and enabling portable analysis in applications of food safety, environmental monitoring, and medical diagnostics.

Ecofriendly approaches to efficiently enhance catalase performance.

The present work reports on two approaches to enhance catalase (CAT) activity and its stability by using two simple, green processes. In the first procedure, CAT was transiently exposed to an ionic liquid (IL) in the presence of redox molecules related to CAT structure which resulted in partial denaturation. The other method, which uses high hydraulic pressure (HHP) to partially denature CAT (in the presence of redox molecules), has the advantage of being completely reagentless. In both cases, partial denaturation was followed by dialysis, hence refolding and entrapment of redox molecules within the modified 3-D CAT structure (affording a "wired" enzyme). The two approaches to enzyme "wiring" are discussed comparatively from the point of view of the parameters used during the procedure, residual enzyme activity, nature of the modifier, interaction between CAT and the redox molecules, antioxidant activity, and stability over time of the modified protein. Samples of CAT modified in the presence of iron sulfate heptahydrate from each series, respectively, were used to make enzyme electrodes which were tested as amperometric biosensors for hydrogen peroxide detection. Both showed catalytic effect and linear behavior and have potential for applications in the food industry, pharmaceuticals and the textile industry.

Renewable regeneration optic fiber glucose sensor based on succinylaminobenzenoboronic acid modified excessively tilted fiber grating.

BACKGROUND: Optical fiber sensors have been used to detect glucose owing to advantages such as low cost, small size, and ease of operation etc. phenylboronic acid is one of the commonly used receptors for glucose detection, however phenylboronic acid based regenerative optical fiber sensors are commonly cumulative regeneration, renewable regeneration sensor has been missing from the literature. RESULTS: In this work, instead of using phenylboronic acid, we synthesized succinylaminobenzenoboronic acid molecule (BPOA) by introducing a short chain containing carboxyl group at the other end of phenylboronic acid then covalently bonded BPOA on the surface of excessively tilted fiber grating (Ex-TFG). This provides a very stable platform for renewable regeneration and the regenerative buffer was also optimized. The proposed renewable regeneration method exhibited higher linearity and sensitivity (R2 = 0.9992, 8 pm/mM) in relative to the conventional cumulative regeneration method (R2 = 0.9718, 4.9 pm/mM). The binding affinity between BPOA and glucose was found to be almost constant over 140 bind/release cycles with a variation of less than 0.3 % relative standard deviation. SIGNIFICANCE: The regenerative and label-free sensing capacity of the proposed device provides a theoretical foundation for label-free saccharide detection and the development of wearable glucose monitoring devices based on fiber optic sensors.

Bioelectrochemical biosensors for water quality assessment and wastewater monitoring.

Bioelectrochemical biosensors offer a promising approach for real-time monitoring of industrial bioprocesses. Many bioelectrochemical biosensors do not require additional labelling reagents for target molecules. This simplifies the monitoring process, reduces costs, and minimizes potential contamination risks. Advancements in materials science and microfabrication technologies are paving the way for smaller, more portable bioelectrochemical biosensors. This opens doors for integration into existing bioprocessing equipment and facilitates on-site, real-time monitoring capabilities. Biosensors can be designed to detect specific heavy metals such as lead, mercury, or chromium in wastewater. Early detection allows for the implementation of appropriate removal techniques before they reach the environment. Despite these challenges, bioelectrochemical biosensors offer a significant leap forward in wastewater monitoring. As research continues to improve their robustness, selectivity, and cost-effectiveness, they have the potential to become a cornerstone of efficient and sustainable wastewater treatment practices.

A DNA Aptamer for 2-Aminopurine: Binding-induced Fluorescence Quenching.

2-Aminopurine (2AP) is a fluorescent analog of adenine, and its unique properties make it valuable in various scientific and biotechnological applications. Its fluorescence property probes local dynamics in DNA and RNA because the surrounding bases quench its fluorescence. 2AP-labeled probes that can bind to specific DNA or RNA sequences, enabling the detection of genetic mutations, viral RNA, or other nucleic acid-based markers associated with diseases like cancer and infectious diseases. In this study, we isolated aptamers for 2AP using the library immobilization capture-SELEX technique. Two major aptamer families were isolated after 15 rounds of screening. The Kd values for the 2AP1 aptamer from family 1 are 209 nM in a fluorescence assay and 72 nM in an isothermal titration calorimetry test. The 32 nM 2AP limit of detection was tested. Additionally, we conducted some mutation analysis. Furthermore, we tested the selectivity of our aptamer using various molecules with similar structures and discovered that it can bind adenine and adenosine as well.

Deep Learning-Based Kinetic Analysis in Paper-Based Analytical Cartridges Integrated with Field-Effect Transistors.

This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity challenge observed in paper analytical devices, enabling electrical measurements with kinetic data. The paper-based cartridge eliminates the need for surface chemistry required in FET sensors, ensuring economical operation (cost < $0.15/test). The DL analysis mitigates chronic challenges of FET biosensors such as sample matrix interference, by leveraging kinetic data from target-specific bioreactions. In our proof-of-concept demonstration, our DL-based analyses showcased a coefficient of variation of <6.46% and a decent concentration measurement correlation with an r2 value of >0.976 for cholesterol testing when blindly compared to results obtained from a CLIA-certified clinical laboratory. These integrated technologies have the potential to advance FET-based biosensors, potentially transforming point-of-care diagnostics and at-home testing through enhanced accessibility, ease-of-use, and accuracy.

Sensing Interfaces Engineering for Organic Thin Film Transistors-Based Biosensors: Opportunities and Challenges.

Organic thin film transistors (OTFTs) enable rapid and label-free high-sensitivity detection of target analytes due to their low cost, large-area processing, biocompatibility, and inherent signal amplification. At the same time, the freedom of synthesis, tailorability, and functionalization of organic semiconductor materials and their ability to be combined with flexible substrates make them one of the ideal platforms for biosensing. However, OTFTs-based biosensors still face significant challenges, such as unexpected surface adsorption, disordered conformation, inhomogeneous graft density, and flexibility of probe molecules that biological sensing probes would face during immobilization. In this review, efficient immobilization strategies based on OTFTs biological sensing probes developed in the last 5 years are highlighted. First, the biosensors are classified according to their sensing interface. Second, a comprehensive discussion of the types of biological sensing probes is presented. Third, three commonly used methods for immobilizing biological sensing probes and their challenges are briefly described. Finally, the applications of OTFTs-based biosensors for liquid phase detection are summarized. This review provides a comprehensive and timely review of optimization in sensing interface engineering so that efficient immobilization of biological sensing probes with sensing interfaces will contribute to the development of high-performance OTFTs-based biosensors.

Soft Bioelectronics for Heart Monitoring.

Cardiovascular diseases (CVDs) are a predominant global health concern, accounting for over 17.9 million deaths in 2019, representing approximately 32% of all global fatalities. In North America and Europe, over a million adults undergo cardiac surgeries annually. Despite the benefits, such surgeries pose risks and require precise postsurgery monitoring. However, during the postdischarge period, where monitoring infrastructures are limited, continuous monitoring of vital signals is hindered. In this area, the introduction of implantable electronics is altering medical practices by enabling real-time and out-of-hospital monitoring of physiological signals and biological information postsurgery. The multimodal implantable bioelectronic platforms have the capability of continuous heart sensing and stimulation, in both postsurgery and out-of-hospital settings. Furthermore, with the emergence of machine learning algorithms into healthcare devices, next-generation implantables will benefit artificial intelligence (AI) and connectivity with skin-interfaced electronics to provide more precise and user-specific results. This Review outlines recent advancements in implantable bioelectronics and their utilization in cardiovascular health monitoring, highlighting their transformative deployment in sensing and stimulation to the heart toward reaching truly personalized healthcare platforms compatible with the Sustainable Development Goal 3.4 of the WHO 2030 observatory roadmap. This Review also discusses the challenges and future prospects of these devices.

Integrating, Validating, and Expanding Information Space in Single-Molecule Surface-Enhanced Raman Spectroscopy for Biomolecules.

Single-molecule surface-enhanced Raman spectroscopy (SM-SERS) is an ultrahigh-resolution spectroscopic method for directly obtaining the complex vibrational mode information on individual molecules. SM-SERS offers a wide range of submolecular information on the hidden heterogeneity in its functional groups and varying structures, dynamics of conformational changes, binding and reaction kinetics, and interactions with the neighboring molecule and environment. Despite the richness in information on individual molecules and potential of SM-SERS in various detection targets, including large and complex biomolecules, several issues and practical considerations remain to be addressed, such as the requirement of long integration time, challenges in forming reliable and controllable interfaces between nanostructures and biomolecules, difficulty in determining hotspot size and shape, and most importantly, insufficient signal reproducibility and stability. Moreover, utilizing and interpreting SERS spectra is challenging, mainly because of the complexity and dynamic nature of molecular fingerprint Raman spectra, and this leads to fragmentary analysis and incomplete understanding of the spectra. In this Perspective, we discuss the current challenges and future opportunities of SM-SERS in views of system approaches by integrating molecules of interest, Raman dyes, plasmonic nanostructures, and artificial intelligence, particularly for detecting and analyzing biomolecules to realize the validation and expansion of information space in SM-SERS.

Fiber photometry in neuroscience research: principles, applications, and future directions.

In recent years, fluorescent sensors are enjoying a surge of popularity in the field of neuroscience. Through the development of novel genetically encoded sensors as well as improved methods of detection and analysis, fluorescent sensing has risen as a new major technique in neuroscience alongside molecular, electrophysiological, and imaging methods, opening up new avenues for research. Combined with multiphoton microscopy and fiber photometry, these sensors offer unique advantages in terms of cellular specificity, access to multiple targets - from calcium dynamics to neurotransmitter release to intracellular processes - as well as high capability for in vivo interrogation of neurobiological mechanisms underpinning behavior. Here, we provide a brief overview of the method, present examples of its integration with other tools in recent studies ranging from cellular to systems neuroscience, and discuss some of its principles and limitations, with the aim of introducing new potential users to this rapidly developing and potent technique.

Electrochemical detection of poly(ADP-ribose) polymerase-1 with silver nanoparticles as signal labels by integrating the advantages of homogeneous reaction with surface-tethered detection.

Poly(ADP-ribose)polymerase-1 (PARP1) could be activated by binding to nucleic acids with specific sequences, thus catalyzing the poly-ADP-ribosylation (PARylation) of target proteins including PARP1 itself. Most of the previously reported electrochemical methods for the determination of PARP1 were relied on the electrostatic interactions, which required the pre-immobilization of DNA on an electrode for the capture of PARP1. Herein, we reported an "immobilization-free" electrochemical strategy for the assays of PARP1 on the basic of avidin-biotin interaction. Once PARP1 was activated by binding with the specific double-stranded DNA (dsDNA) in a homogeneous solution, the biotinylated nicotinamide adenine dinucleotide (biotin-NAD+) was transferred onto PARP1, resulting in the formation of biotinylated PAR polymers. The resulting biotinylated PAR polymers were then captured by a neutravidin (NA)-modified electrode through avidin-biotin interactions. The rich biotin moieties in the PAR polymers allowed for the capture of NA-modified silver nanoparticles (NA-AgNPs) through the avidin-biotin interactions. The surface-tethered AgNPs produced a well-defined electrochemical signal due to the characteristic solid-state Ag/AgCl process. The "immobilization-free", electrostatic interaction-independent electrochemical biosensor exhibited low background current, high sensitivity, and good stability. It has achieved the determination of PARP1 with a detection limit down to 0.7 mU. The biosensor was further applied to determine the inhibition efficiency of potential inhibitors with a satisfactory result. This method shows promising potential applications in PARP1-related clinical diagnosis and drug discovery.