Real-time Dynamic Monitoring Research Articles

Wastewater surveillance of severe acute respiratory syndrome coronavirus-2 in open drains of two Indian megacities captures evolutionary lineage transitions: a zonation approach.

Wastewater-based environmental surveillance (WBES) has been proven as proxy tool for monitoring nucleic acids of pathogens shed by infected population before clinical outcomes. The poor sewershed network of low to middle-income countries (LMICs) leads to most of the wastewater flow through open drains. We studied the effectiveness of WBES using open drain samples to monitor the emergence of the SARS-CoV-2 variants in 2 megacities of India having dense population through zonation approach. Samples from 28 locations spanned into 5 zones of Pune region, Maharashtra, India, were collected on a weekly basis during October 2021 to July 2022. Out of 1115 total processed samples, 303 (~ 27%) tested positive for SARS-CoV-2. The periodical rise and fall in the percentage positivity of the samples was found to be in sync with the abundance of SARS-CoV-2 RNA and the reported COVID-19 active cases for Pune city. Sequencing of the RNA obtained from wastewater samples confirmed the presence of SARS-CoV-2. Of 337 sequences, lineage identification for 242 samples revealed 265 distinct SARS-CoV-2 variants including 10 highly transmissible ones. Importantly, transition from Delta to Omicron variant could be detected in wastewater samples 2weeks prior to any clinically reported Omicron cases in India. Thus, this study demonstrates the usefulness of open drain samples for real-time monitoring of a viral pathogen's evolutionary dynamics and could be implemented in LMICs.

Visualizing cancer resistance via nano-quenching and recovery detector of CD44

Drug resistance to chemotherapy in cancers remains significant clinical challenges. CD44 modulates cellular adhesion, migration and growth, which plays a pivotal role in driving cancer resistance and even recurrence. Despite ongoing efforts, accurate, safe, and real-time dynamic monitoring techniques for CD44 expression remain inadequate in guiding the management of drug-resistant cancer treatment. In this study, we developed a nano-quenching and recovery detector of CD44 (Cy3-AptCD44@BPNSs) for visualizing cancer drug resistance. The fluorescence recovery of the detector is directly related to the CD44 expression level on cancer cells, which can be used to indicate the degree of drug resistance. It’s confirmed that downregulating CD44 expression on cancer cells results in a corresponding decrease in the fluorescence intensity of the detector, which enables precise and dynamic monitoring of CD44. In addition, the Cy3-AptCD44@BPNSs also exhibited specificity in detecting CD44. This visualizing strategy may open up a wide range of possibilities for rapid recognition to cancer drug resistance, which is more efficient and flexible.

Longitudinal on-treatment circulating tumor DNA as a biomarker for real-time dynamic risk monitoring in cancer patients: The EP-SEASON study

Recurrence risks of cancer patient can change during treatment as a result of treatment-related tumor evolution. However, biomarkers that can monitor these changes are lacking. Here, we investigated whether tracking circulating tumor DNA (ctDNA) dynamics through liquid biopsy can inform real-time recurrence risk. Nasopharyngeal carcinoma (NPC) provides an ideal model where cell-free Epstein-Barr virus (EBV) DNA (cfEBV DNA), a ctDNA, can be sensitively detected. We conducted the EP-SEASON study (NCT03855020) and prospectively recruited 1,000 NPC patients undergoing per-protocol cfEBV DNA assessments at 11 time points and receiving sequential chemo-radiotherapy. Longitudinal cfEBV DNA displayed distinct patterns during neoadjuvant chemotherapy and radiotherapy. Despite the prognostic significance of cfEBV DNA at each time point, real-time recurrence risks changed in sync with cfEBV DNA dynamics. Furthermore, we identified phenotypes of whole-course ctDNA changing dynamics associated with different survival outcomes. In conclusion, tracking longitudinal on-treatment ctDNA can forecast real-time recurrence risk, facilitating risk-adapted, individualized patient management.

A super-elastic wearable strain sensor based on PU/CNTs yarns for human-motion detection

Yarn-based strain sensors increasingly garner attention for their potential applications in intelligent wearable electronic devices. Developing highly elastic conductive composite yarns and integrating them into fabrics poses a significant challenge in manufacturing flexible electronic devices. In this study, a polyurethane (PU)/carbon nanotubes (CNTs) composite nanofiber yarn was successfully and continuously prepared using a simple conjugate spinning technique. The resulting yarn exhibited excellent mechanical properties, with a high tensile strength of up to 56.7 MPa and an elongation at break of 504 %. A yarn with a dual conductive network was created using CNTs ink dip-coating. It demonstrated excellent conductivity (8.77 S/cm), exceptional linear variation, and reusability. The sensor remained stable after 1000 cycles of testing, exhibiting a relative electrical resistance change of up to 594 % under a strain of 350 %. Additionally, taking advantage of the inherent knittability of one-dimensional yarn structures, a susceptible wearable textile-type strain sensor was successfully developed using textile knitting technology. This sensor can be directly attached to the surface of the human body for real-time monitoring of human body dynamics. This sensor showcases significant promise for use in flexible, intelligent, wearable electronic devices.

An Experimental Study of the Morphological Evolution of Rills on Slopes under Rainfall Action

Accurately monitoring the morphology and spatiotemporal evolution characteristics of the entire process of slope erosion rill development is essential to circumvent the limitations inherent in traditional methods that rely on average flow velocity for hydrodynamic parameter calculations. This study employs an environmental chamber and a self-developed slope erosion test device to perform erosion tests on slopes with varying gradients and rainfall intensities. By integrating the structure-from-motion (SfM) method, fixed grid coordinate method, and continuous camera combined with the dye tracer technique, the morphological indexes and hydrodynamic parameters of the entire rill development process are precisely computed. The main conclusions are as follows: The entire process of slope rill development can be divided into three distinct stages. The initial stage is characterized by the appearance of tiny rills with mild erosion. The middle stage involves severe transverse spreading erosion and longitudinal undercutting, resulting in diverse rill morphologies. The final stage is marked by the stabilization of morphological characteristics. The peak slope soil loss is observed during the middle stage of rill development. The most effective parameters for characterizing slope soil loss from the beginning to the end are the Reynolds number and flow shear stress, the Froude number and flow shear stress, and the Froude number during different periods. Throughout the development of rills, the flow velocity initially decreases and then gradually increases until it stabilizes. The morphological indexes, including rill density, dissected degree, inclination, and complexity, generally show an increasing trend. However, in the middle stage, the rate of increase slows down, followed by a sharp rise at certain points. The optimal hydraulic parameters for evaluating rill density across different slope gradients, which were found to be the Darcy–Weisbach drag coefficient and real-time flow velocity, for assessing rill dissected degree, complexity, and inclination, were the Reynolds number and flow power. Under varying rainfall intensities, the most effective hydraulic and kinetic parameters for evaluating rill density, dissected degree, and inclination were flow shear stress and Reynolds number; for assessing rill complexity, the Reynolds number and flow power were used. The findings of this research enhance the accuracy of hydrodynamic parameter calculations in rill erosion tests, enable precise prediction of rill development trends on slopes, and offer innovative approaches for real-time dynamic monitoring of rill morphology and characteristics. These advancements are of significant importance for soil and water conservation and sustainability.

Real-time dynamic damage monitoring of ultra-thin-ply composite bonded/bolted joint interference-fit installation based on evolutionary affinity propagation

This research introduced ultra-thin prepregs for designing equal-thickness laminates and conducted experimental tests on interference-fit. The uncertainty of damage, attributed to the bearing and friction exerted by the shank against the hole wall during installation, posed a significant challenge. Moreover, the absence of real-time damage monitoring methods in existing literature. In this paper, we proposed the utilization of acoustic emission (AE) technology in conjunction with the evolutionary affinity propagation (EAP) algorithm to facilitate dynamic, real-time monitoring and classification of damage. The findings indicated that employing ultra-thin in composite interference-fit installations substantially reduced damage to the hole walls. Furthermore, the EAP algorithm surpassed traditional methods in its ability to accurately and efficiently monitor and analyze damage dynamically throughout the interference-fit installation.

Exosomal microRNAs: impact on cancer detection, treatment, and monitoring.

Exosomes, measuring between 30 and 150nm in diameter, are small vesicles enclosed by a lipid bilayer membrane. They are released by various cells in the body and carry a diverse payload of molecules, including proteins, lipids, mRNA, and different RNA species such as long non-coding RNA, circular RNA, and microRNA (miRNA). With lengths of approximately 19-22 nucleotides, miRNAs constitute the predominant cargo in exosomes and serve as crucial regulators of protein biosynthesis. In cancer detection, exosomal miRNAs show promise as non-invasive biomarkers due to their stability and presence in various bodily fluids, aiding in early detection and precise diagnosis with specific miRNA signatures linked to different cancer types. Moreover, exosomal miRNAs influence treatment outcomes by affecting cellular processes like cell growth, cell death, and drug resistance, thereby impacting response to therapy. Additionally, they serve as indicators of disease progression and treatment response, providing insights that can guide treatment decisions and improve patient care. Through longitudinal studies, changes in exosomal miRNA profiles have been observed to correlate with disease progression, metastasis, and response to therapy, highlighting their potential for real-time monitoring of tumor dynamics and treatment efficacy. Understanding the intricate roles of exosomal miRNAs in cancer biology offers opportunities for developing innovative diagnostic tools and therapeutic strategies tailored to individual patients, ultimately advancing precision medicine approaches and improving outcomes for cancer patients. This review aims to provide an understanding of the role of exosomal miRNAs in cancer detection, treatment, and monitoring, shedding light on their potential for revolutionising oncology practices and patient care.

Farnesyltransferase inhibition overcomes oncogene-addicted non-small cell lung cancer adaptive resistance to targeted therapies

Drug-tolerance has emerged as one of the major non-genetic adaptive processes driving resistance to targeted therapy (TT) in non-small cell lung cancer (NSCLC). However, the kinetics and sequence of molecular events governing this adaptive response remain poorly understood. Here, we combine real-time monitoring of the cell-cycle dynamics and single-cell RNA sequencing in a broad panel of oncogenic addiction such as EGFR-, ALK-, BRAF- and KRAS-mutant NSCLC, treated with their corresponding TT. We identify a common path of drug adaptation, which invariably involves alveolar type 1 (AT1) differentiation and Rho-associated protein kinase (ROCK)-mediated cytoskeletal remodeling. We also isolate and characterize a rare population of early escapers, which represent the earliest resistance-initiating cells that emerge in the first hours of treatment from the AT1-like population. A phenotypic drug screen identify farnesyltransferase inhibitors (FTI) such as tipifarnib as the most effective drugs in preventing relapse to TT in vitro and in vivo in several models of oncogenic addiction, which is confirmed by genetic depletion of the farnesyltransferase. These findings pave the way for the development of treatments combining TT and FTI to effectively prevent tumor relapse in oncogene-addicted NSCLC patients.

Effects of different nitric oxide synthases on pulmonary and systemic hemodynamics in hypoxic stress rat model.

Under hypoxia, exaggerated compensatory responses may lead to acute mountain sickness. The excessive vasodilatory effect of nitric oxide (NO) can lower the hypoxic pulmonary vasoconstriction (HPV) and peripheral blood pressure. While NO is catalyzed by various nitric oxide synthase (NOS) isoforms, the regulatory roles of these types in the hemodynamics of pulmonary and systemic circulation in living hypoxic animals remain unclear. Therefore, this study aims to investigate the regulatory effects of different NOS isoforms on pulmonary and systemic circulation in hypoxic rats by employing selective NOS inhibitors and continuously monitoring hemodynamic parameters of both pulmonary and systemic circulation. Forty healthy male Sprague-Dawley (SD) rats were randomly divided into four groups: Control group (NG-nitro-D-arginine methyl ester, D-NAME), L-NAME group (non-selective NOS inhibitor, NG-nitro-L-arginine methyl ester), AG group (inducible NOS inhibitor group, aminoguanidine), and 7-NI group (neurological NOS inhibitor, 7-nitroindazole). Hemodynamic parameters of rats were monitored for 10 min after inhibitor administration and 5 min after induction of hypoxia [15% O2, 2200 m a. sl., 582 mmHg (76.5 kPa), Xining, China] using the real-time dynamic monitoring model for pulmonary and systemic circulation hemodynamics invivo. Serum NO concentrations and blood gas analysis were measured. Under normoxia, mean arterial pressure and total peripheral vascular resistance were increased, and ascending aortic blood flow and serum NO concentration were decreased in the L-NAME and AG groups. During hypoxia, pulmonary arterial pressure and pulmonary vascular resistance were significantly increased in the L-NAME and AG groups. This compensatory mechanism activated by inducible NOS and endothelial NOS effectively counteracts the pulmonary hemodynamic changes induced by hypoxic stress. It plays a crucial role in alleviating hypoxia-induced pulmonary arterial hypertension.

Recent Progress of Multifunctional Molecular Probes for Triple-Negative Breast Cancer Theranostics.

Breast cancer (BC) poses a significant threat to women's health, with triple-negative breast cancer (TNBC) representing one of the most challenging and aggressive subtypes due to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression. Traditional TNBC treatments often encounter issues such as low drug efficiency, limited tumor enrichment, and substantial side effects. Therefore, it is crucial to explore novel diagnostic and treatment systems for TNBC. Multifunctional molecular probes (MMPs), which integrate target recognition as well as diagnostic and therapeutic functions, introduce advanced molecular tools for TNBC theranostics. Using an MMP system, molecular drugs can be precisely delivered to the tumor site through a targeted ligand. Real-time dynamic monitoring of drug release achieved using imaging technology allows for the evaluation of drug enrichment at the tumor site. This approach enables accurate drug release, thereby improving the therapeutic effect. Therefore, this review summarizes the recent advancements in MMPs for TNBC theranostics, encompassing the design and synthesis of MMPs as well as their applications in the field of TNBC theranostics.

Development of halochromic labels based on binary systems of cationic guar gum and κ-carrageenan loaded with alizarin red S for monitoring milk and seafood freshness

Monitoring of food quality, in particular, high-protein food quality, is an important component in ensuring food safety and human health. In this research, a feasible and easy solution casting and solvent evaporation strategy was adapted to fabricate alizarin red S (ARS)-loaded halochromic cationic guar gum (CGG) and κ-carrageenan (CAR) blend packaging labels to improve its good physical strength, multifunctional acid–base responsive characteristics, and water barrier properties. The findings indicated that incorporating CAR at 40% polymer solid mass achieved higher tensile strength (21.0 ± 1.77 MPa), water resistance (29.92 ± 6.61% solubility), and thermal stability, which can be attributed to good compatibility between CGG and CAR. The results obtained from FT-IR, XRD, and SEM analyses demonstrate that the incorporation of ARS exhibits non-covalent bonding with the polymer blend matrix through electrostatic interactions and hydrogen bonding, thus reducing its crystallinity and restructuring the CGG-CAR matrix disorderly. The prepared indicating label films presented visual recognition of ammonia and trimethylamine (TMA-N) at 0.008 mM in 6 min (the total color difference (ΔE) for TMA-N is＞11.89), and can be reused at least six times. Moreover, the color of ARS at different pH values remains persistent for at least 180 days. The practical applications show that the films, as indicator labels, can realize real-time, accurate, and visual dynamic monitoring of seafood (shrimp) and milk by engendering three chromatic stages discernible by the naked eye (fresh, spoiling, and spoiled). The ΔE for monitoring sub-fresh milk and shrimp reached as high as 14.91 and 13.32, respectively.

Robust Intelligent Monitoring and Measurement System toward Downhole Dynamic Liquid Level.

Dynamic liquid level monitoring and measurement in oil wells is essential in ensuring the safe and efficient operation of oil extraction machinery and formulating rational extraction policies that enhance the productivity of oilfields. This paper presents an intelligent infrasound-based measurement method for oil wells' dynamic liquid levels; it is designed to address the challenges of conventional measurement methods, including high costs, low precision, low robustness and inadequate real-time performance. Firstly, a novel noise reduction algorithm is introduced to effectively mitigate both periodic and stochastic noise, thereby significantly improving the accuracy of dynamic liquid level detection. Additionally, leveraging the PyQT framework, a software platform for real-time dynamic liquid level monitoring is engineered, capable of generating liquid level profiles, computing the sound velocity and liquid depth and visualizing the monitoring data. To bolster the data storage and analytical capabilities, the system incorporates an around-the-clock unattended monitoring approach, utilizing Internet of Things (IoT) technology to facilitate the transmission of the collected dynamic liquid level data and computed results to the oilfield's central data repository via LoRa and 4G communication modules. Field trials on dynamic liquid level monitoring and measurement in oil wells demonstrate a measurement range of 600 m to 3000 m, with consistent and reliable results, fulfilling the requirements for oil well dynamic liquid level monitoring and measurement. This innovative system offers a new perspective and methodology for the computation and surveillance of dynamic liquid level depths.

Dynamic monitoring soft tissue healing via visualized Gd-crosslinked double network MRI microspheres

By integrating magnetic resonance-visible components with scaffold materials, hydrogel microspheres (HMs) become visible under magnetic resonance imaging(MRI), allowing for non-invasive, continuous, and dynamic monitoring of the distribution, degradation, and relationship of the HMs with local tissues. However, when these visualization components are physically blended into the HMs, it reduces their relaxation rate and specificity under MRI, weakening the efficacy of real-time dynamic monitoring. To achieve MRI-guided in vivo monitoring of HMs with tissue repair functionality, we utilized airflow control and photo-crosslinking methods to prepare alginate-gelatin-based dual-network hydrogel microspheres (G-AlgMA HMs) using gadolinium ions (Gd (III)), a paramagnetic MRI contrast agent, as the crosslinker. When the network of G-AlgMA HMs degrades, the cleavage of covalent bonds causes the release of Gd (III), continuously altering the arrangement and movement characteristics of surrounding water molecules. This change in local transverse and longitudinal relaxation times results in variations in MRI signal values, thus enabling MRI-guided in vivo monitoring of the HMs. Additionally, in vivo data show that the degradation and release of polypeptide (K2 (SL)6 K2 (KK)) from G-AlgMA HMs promote local vascular regeneration and soft tissue repair. Overall, G-AlgMA HMs enable non-invasive, dynamic in vivo monitoring of biomaterial degradation and tissue regeneration through MRI, which is significant for understanding material degradation mechanisms, evaluating biocompatibility, and optimizing material design.

Real-time monitoring of chromatic and phenolic dynamics of vinification employing UV-Vis spectroscopy, Python and chemometrics

Increasing consumer demand for high-quality wines required the introduction of more comprehensive monitoring indicators for quality management, necessitating winemakers to strive for rapid, real-time, and affordable monitoring tools during winemaking. This study investigated the feasibility of cost-efficient and easy-to-implement ultraviolet-visible (UV-Vis) spectroscopy combined with chemometric methods to predictively monitor the evolution of wine color and phenolics throughout commercial fermentation. Fermentations on a winery scale were carried out with a daily analysis of the UV-Vis spectra, color, and phenolics. Furthermore, characteristic wavelengths were established by a self-compiled Python program to reduce redundancy in spectra. The optimized partial least squares (PLS) model predicted well with a residual prediction deviation (RPD) greater than 2.54, and the robustness was further verified by a robust external Bland-Altman method. UV-Vis spectroscopy can achieve objective monitoring of the practical fermentation profile, which can better help winemakers make decisions to improve wine quality and consistency.

Updated Toolbox for Assessing Neuronal Network Reconstruction after Cell Therapy.

Cell therapy has proven to be a promising treatment for a range of neurological disorders, including Parkinson Disease, drug-resistant epilepsy, and stroke, by restoring function after brain damage. Nevertheless, evaluating the true effectiveness of these therapeutic interventions requires a deep understanding of the functional integration of grafted cells into existing neural networks. This review explores a powerful arsenal of molecular techniques revolutionizing our ability to unveil functional integration of grafted cells within the host brain. From precise manipulation of neuronal activity to pinpoint the functional contribution of transplanted cells by using opto- and chemo-genetics, to real-time monitoring of neuronal dynamics shedding light on functional connectivity within the reconstructed circuits by using genetically encoded (calcium) indicators in vivo. Finally, structural reconstruction and mapping communication pathways between grafted and host neurons can be achieved by monosynaptic tracing with viral vectors. The cutting-edge toolbox presented here holds immense promise for elucidating the impact of cell therapy on neural circuitry and guiding the development of more effective treatments for neurological disorders.

喷杆倾角控制系统的设计与实验

During field operations of the spray boom sprayer, the distance between the ends of the spray boom and the height of the crop canopy affects the uniformity of spraying, requiring operators to manually adjust the spray boom to be parallel to the crop canopy, which impacts operational efficiency. This study presents the design of a boom tilt control system, consisting of a main control node, distance measurement node, vehicle tilt detection node, and spray boom tilt control node. The bus communication protocol for the spray boom tilt control system is defined according to the ISO11783 standard, and a serial communication network is designed, along with the development of a real-time dynamic monitoring interface for the spray boom. The system automatically monitors the height of the boom and the tilt of the vehicle, makes decisions based on the detection information, controls the electric actuator, and adjusts the tilt of the boom. Leveraging the advantages of fast computing speed and user-friendly human-machine interface of the PC, as well as the high cost-effectiveness and small size of the microcontroller, and the multi-master-slave structure of the CAN bus, this system can complete data acquisition, processing, and other functions required for spray boom tilt control, achieving automatic adjustment of spray boom tilt. This enhances spray uniformity and operational efficiency of the sprayer, while reducing the workload of operators.

An AND-Gate Photoacoustic Probe for Cys and H2S Precise Photoacoustic Sensing in Localized Tumors.

Photoacoustic (PA) tomography has shown many promising aspects in noninvasive and precise imaging of deep-localized biomarkers. However, these traditional single-locked PA probes always face challenges in precise PA imaging with high specificity. Here, we report a novel AND-gate photoacoustic probe, BAE, to improve tumor imaging accuracy via the combination of two tumor-associated biomarkers, cysteine (Cys) and hydrogen sulfide (H2S). Only when Cys and H2S are concurrently introduced into the detection system does the absorption of BAE red-shift from the initial 680 to 810 nm, thereby showing a 5.29-fold enhancement in its PA signal at 810 nm. The good specificity of BAE is proven, since an obvious PA signal could be observed only in the solution containing both Cys and H2S and was not affected by other reactive sulfur species. After being taken up by tumors with the assistance of a nanomicelle, the AND-gate PA probe BAE was applied for dynamic real-time monitoring of Cys and H2S in vivo, achieving precise identification of tumors. This AND-gate PA probe provides a potential technical tool for precise sensing analysis of deep-seated diseases.

Fine-grained spatiotemporal estimation of tourism flows leveraging cross-video collaborative perception

Microscale research on tourism flows is crucial for controlling such flows, analyzing resource-carrying capacity, and promoting sustainable development in the tourism industry. Current fine-grained monitoring of tourism flows using location-based big data faces challenges, such as inadequate user representation, data acquisition difficulties and spatiotemporal uncertainty. This study presents a method for the spatiotemporal modeling and estimation of regional tourism flows based on the collaborative perception of discrete surveillance videos. The method employed bridges the gap between physical and video image scenes by establishing collaborative perception relationships among multiple devices, thereby enabling the precise modeling and estimation of the dynamic spatiotemporal processes of population movement in the region. Empirical studies in real scenic areas confirm the adaptability of this technology to diverse geographical scenes and ensure the accuracy of the spatiotemporal flow estimation. This study addresses the challenges of high sampling costs and low spatiotemporal accuracy in regional fine-grained crowd estimation and offers technical support for near real-time dynamic crowd modeling and monitoring. The experimental results have the potential to assist in applications, such as tourism flow management, dynamic regulation and the risk analysis of group activities in scenic areas.

Reverse engineering the last-minute on-line pricing practices: an application to hotels

We suggest a nonlinear time series methodology to model the (last-minute) price adjustments that hotels active in the online market make to adapt their early-booking rates in response to unpredictable fluctuations in demand. We use this approach to reverse-engineer the pricing strategies of six hotels in Milan, Italy, each with different features and services. The results reveal that the hotels’ ability to align last-minute adjustments with early-booking decisions and account for stochastic demand seasonality varies depending on factors such as size, star rating, and brand affiliation. As a primary empirical finding, we show that the autocorrelations of the first four moments of the last-minute price adjustment can be used to gain crucial insights into the hoteliers’ pricing strategies. Scaling up this approach has the potential to equip policymakers in smart destinations with a reliable and transparent tool for the real-time monitoring of demand dynamics.

Hydroxylase-like Biomimetic Nanozyme Synthesized via a Urea-Mediated MOF Pyrolytic Reconstruction Strategy for Non-"o-Phenol hydroxyl"-Dependent Dopamine Electrochemical Sensing.

Dopamine (DA), an essential neurotransmitter, is closely associated with various neurological disorders, whose real-time dynamic monitoring is significant for evaluating the physiological activities of neurons. Electrochemical sensing methods are commonly used to determine DA, but they mostly rely on the redox reaction of its o-phenolic hydroxyl group, which makes it difficult to distinguish it from substances with this group. Here, we design a biomimetic nanozyme inspired by the coordination structure of the copper-based active site of dopamine β-hydroxylase, which was successfully synthesized via a urea-mediated MOF pyrolysis reconstruction strategy. Experimental studies and theoretical calculations revealed that the nanozyme with Cu-N3 coordination could hydroxylate the carbon atom of the DA β-site at a suitable potential and that the active sites of this Cu-N3 structure have the lowest binding energy for the DA β-site. With this property, the new oxidation peak achieves the specific detection of DA rather than the traditional electrochemical signal of o-phenol hydroxyl redox, which would effectively differentiate it from neurotransmitters, such as norepinephrine and epinephrine. The sensor exhibited good monitoring capability in DA concentrations from 0.05 to 16.7 μM, and its limit of detection was 0.03 μM. Finally, the sensor enables the monitoring of DA released from living cells and can be used to quantitatively analyze the effect of polystyrene microplastics on the amount of DA released. The research provides a method for highly specific monitoring of DA and technical support for initial screening for neurocytotoxicity of pollutants.