Platform For Continuous Monitoring Research Articles

Digital Platform for Continuous Monitoring of Patients Using a Smartwatch: Longitudinal Prospective Cohort Study.

Since the COVID-19 pandemic, there has been a boost in the digital transformation of the human society, where wearable devices such as a smartwatch can already measure vital signs in a continuous and naturalistic way; however, the security and privacy of personal data is a challenge to expanding the use of these data by health professionals in clinical follow-up for decision-making. Similar to the European General Data Protection Regulation, in Brazil, the Lei Geral de Proteção de Dados established rules and guidelines for the processing of personal data, including those used for patient care, such as those captured by smartwatches. Thus, in any telemonitoring scenario, there is a need to comply with rules and regulations, making this issue a challenge to overcome. This study aimed to build a digital solution model for capturing data from wearable devices and making them available in a safe and agile manner for clinical and research use, following current laws. A functional model was built following the Brazilian Lei Geral de Proteção de Dados (2018), where data captured by smartwatches can be transmitted anonymously over the Internet of Things and be identified later within the hospital. A total of 80 volunteers were selected for a 24-week follow-up clinical trial divided into 2 groups, one group with a previous diagnosis of COVID-19 and a control group without a previous diagnosis of COVID-19, to measure the synchronization rate of the platform with the devices and the accuracy and precision of the smartwatch in out-of-hospital conditions to simulate remote monitoring at home. In a 35-week clinical trial, >11.2 million records were collected with no system downtime; 66% of continuous beats per minute were synchronized within 24 hours (79% within 2 days and 91% within a week). In the limit of agreement analysis, the mean differences in oxygen saturation, diastolic blood pressure, systolic blood pressure, and heart rate were -1.280% (SD 5.679%), -1.399 (SD 19.112) mm Hg, -1.536 (SD 24.244) mm Hg, and 0.566 (SD 3.114) beats per minute, respectively. Furthermore, there was no difference in the 2 study groups in terms of data analysis (neither using the smartwatch nor the gold-standard devices), but it is worth mentioning that all volunteers in the COVID-19 group were already cured of the infection and were highly functional in their daily work life. On the basis of the results obtained, considering the validation conditions of accuracy and precision and simulating an extrahospital use environment, the functional model built in this study is capable of capturing data from the smartwatch and anonymously providing it to health care services, where they can be treated according to the legislation and be used to support clinical decisions during remote monitoring.

Biohybrid 3D Printing of a Tissue-Sensor Platform for Wireless, Real-Time, and Continuous Monitoring of Drug-Induced Cardiotoxicity.

Drug-induced cardiotoxicity is regarded as a major hurdle in the early stages of drug development. Although there are various methods for preclinical cardiotoxicity tests, they cannot completely predict the cardiotoxic potential of a compound due to the lack of physiological relevance. Recently, 3D engineered heart tissue (EHT) has been used to investigate cardiac muscle functions as well as pharmacological effects by exhibiting physiological auxotonic contractions. However, there is still no adequate platform for continuous monitoring to test acute and chronic pharmacological effects in vitro. Here, a biohybrid 3D printing method for fabricating a tissue-sensor platform, composed of a bipillar-grafted strain gauge sensor and EHT, is first introduced. Two pillars are three-dimensionally printed as grafts onto a strain gauge-embedded substrate to promote the EHT contractility and guide the self-assembly of the EHTs along with the strain gauge. In addition, the integration of a wireless multi-channel electronic system allows for continuous monitoring of the EHT contractile force by the tissue-sensor platform and, ultimately, for the observation of the acute and chronic drug effects of cardiotoxicants. In summary, biohybrid 3D printing technology is expected to be a potential fabrication method to provide a next-generation tissue-sensor platform for an effective drug development process.

Contact Lens-Based Microchannel Rings for Detecting Ocular Hypertension

Glaucoma is a major cause of irreversible blindness worldwide. The most acknowledged biomarker to diagnose and monitor glaucoma progression is intraocular pressure (IOP). Gold standard techniques for IOP monitoring are invasive, uncomfortable, and require visiting a clinic. In addition, most methods only provide a single snapshot on widely varying parameters. On the other hand, contact lenses have attracted particular interest to be used as continuous monitoring platforms to incorporate sensors, drugs, and more. Here, commercial contact lenses were laser-processed to be capable of detecting IOP variations in the physiological range. Three ring-couples with interspaces of 1.0, 1.5, and 2.0 mm were engraved on three soft contact lenses separately by using a carbon dioxide laser. The IOP/pressure variations induced repeatable changes in the ring-couple interspace which acted as a smartphone-readable pressure sensor. The processed contact lenses may be a potential candidate toward IOP monitoring at point-of-care settings.

IoT enabled microfluidic colorimetric detection platform for continuous monitoring of nitrite and phosphate in soil

With the amalgamation of microfluidics and cyber-physical systems, a paradigm shift can be witnessed in the way the devices are conceptualized and developed for many applications, including soil and water monitoring for agricultural application and overall environmental monitoring. Such technological enhancements are leveraged to facilitate on-site detection and quantification by developing miniaturized devices offering multiplexed detection and data transmission across the globe using internet of things (IoT). Herein, a colorimetry-based miniaturized device was developed by incorporating optoelectronic components and employing a poly(dimethylsiloxane) (PDMS) microfluidic device for precise determination of two of the soil macronutrients i.e. nitrogen and phosphorus. Miniaturization and online data monitoring using the IoT and Bluetooth-based modules, along with Arduino microcontroller, lead to generate data, and its monitoring and storage even in the remote locations. Nitrite and phosphorus were detected in a linear range of 1 µM–30 µM and 10 µM–100 µM with limit of detection (LOD) of 0.33 µM (0.021 ppm) and 0.75 µM (0.095 ppm) respectively which is above the prescribed limits. Furthermore, an android app was developed for continuous monitoring using Bluetooth module for short range data transmission. Overall this work demonstrates the microfluidic colorimetric sensing and IoT enabled data monitoring of soil macro nutrients through a cost-effective platform which opens up avenues for the development of miniaturized point-of-care devices.

Wearable electrochemical microneedle sensing platform for real-time continuous interstitial fluid monitoring of apomorphine: Toward Parkinson management

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, impacting millions of people across the globe. For its management, pro-neurotransmitters or agonists are commonly being prescribed, which help to mitigate the symptoms. However, the progressiveness of PD and narrowing down of the drug therapeutic window eventually led to its ineffective management. Therefore, the requirement of continuous monitoring of administered drugs is of utmost need. In view of this, here, we demonstrate a microneedle-based wearable electrochemical sensor platform for the continuous monitoring of apomorphine (APO), a widely used therapeutic drug for Parkinson’s management. The APO sensor relies on a metallized carbon-paste packed hollow microneedle, operated using the square wave voltammetry (SWV) and chronoamperometry (CA) based transduction modes. Under the optimal conditions, the microneedle sensor offers sensitive detection of micromolar APO concentrations in artificial interstitial fluid (ISF) through the monitoring of the two oxidation peaks of the APO catechol and tertiary amine moieties (at 0.1 V and 0.7 V, respectively). The microneedle sensor exhibited a detection limit of 0.6 and 0.75 μM with the transduction techniques SWV and CA, respectively, and good operational stability as well as anti-biofouling protection in artificial-ISF medium. The specificity has been tested for the developed sensor in the presence of potential interfering molecules, where the developed sensor showed the selectivity towards APO. The attractive analytical performance demonstrated in the skin mimic environment makes the new wearable APO microneedle sensor a powerful candidate for continuous APO detection in PD management.

Validation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas

Abstract The problem involving the monitoring of surface ground movements in post-mining areas is particularly important during the period of mine closures. During or after flooding of a mine, mechanical properties of the rock mass may be impaired, and this may trigger subsidence, surface landslides, uplift, sinkholes or seismic activity. It is, therefore, important to examine and select updating methods and plans for long-term monitoring of post-mining areas to mitigate seismic hazards or surface deformation during and after mine closure. The research assumed the implementation of continuous monitoring of surface movements using the Global Navigation Satellite System (GNSS) in the area of a closed hard coal mine ‘Kazimierz-Juliusz’, located in Poland. In order to ensure displacement measurement results with the accuracy of several millimetres, the accuracy of multi-GNSS observations carried out in real time as a combination of four global navigation systems, Global Positioning System (GPS), Globalnaja Navigacionnaja Sputnikova Sistema (GLONASS), Galileo and BeiDou, was determined. The article presents the results of empirical research conducted at four reference points. The test observations were made in variants comprising measurements based on: GPS, GPS and GLONASS systems, GPS, GLONASS and Galileo systems, GPS, GLONASS, Galileo and BeiDou systems. For each adopted solution, daily measurement sessions were performed using the RTK technique. The test results were subjected to accuracy analyses. Based on the obtained results, it was found that GNSS measurements should be carried out with the use of three navigation systems (GPS, GLONASS, Galileo), as an optimal solution for the needs of continuous geodetic monitoring in the area of the study.

Smartphone-Based Passive Sensing for Behavioral and Physical Monitoring in Free-Life Conditions: Technical Usability Study

Background Smartphone use is widely spreading in society. Their embedded functions and sensors may play an important role in therapy monitoring and planning. However, the use of smartphones for intrapersonal behavioral and physical monitoring is not yet fully supported by adequate studies addressing technical reliability and acceptance. Objective The objective of this paper is to identify and discuss technical issues that may impact on the wide use of smartphones as clinical monitoring tools. The focus is on the quality of the data and transparency of the acquisition process. Methods QuantifyMyPerson is a platform for continuous monitoring of smartphone use and embedded sensors data. The platform consists of an app for data acquisition, a backend cloud server for data storage and processing, and a web-based dashboard for data management and visualization. The data processing aims to extract meaningful features for the description of daily life such as phone status, calls, app use, GPS, and accelerometer data. A total of health subjects installed the app on their smartphones, running it for 7 months. The acquired data were analyzed to assess impact on smartphone performance (ie, battery consumption and anomalies in functioning) and data integrity. Relevance of the selected features in describing changes in daily life was assessed through the computation of a k-nearest neighbors global anomaly score to detect days that differ from others. Results The effectiveness of smartphone-based monitoring depends on the acceptability and interoperability of the system as user retention and data integrity are key aspects. Acceptability was confirmed by the full transparency of the app and the absence of any conflicts with daily smartphone use. The only perceived issue was the battery consumption even though the trend of battery drain with and without the app running was comparable. Regarding interoperability, the app was successfully installed and run on several Android brands. The study shows that some smartphone manufacturers implement power-saving policies not allowing continuous sensor data acquisition and impacting integrity. Data integrity was 96% on smartphones whose power-saving policies do not impact the embedded sensor management and 84% overall. Conclusions The main technological barriers to continuous behavioral and physical monitoring (ie, battery consumption and power-saving policies of manufacturers) may be overcome. Battery consumption increase is mainly due to GPS triangulation and may be limited, while data missing because of power-saving policies are related only to periods of nonuse of the phone since the embedded sensors are reactivated by any smartphone event. Overall, smartphone-based passive sensing is fully feasible and scalable despite the Android market fragmentation.

Optical Spectral Tools for Diagnosing Water Media Quality: A Case Study on the Angara/Yenisey River System in the Siberian Region

This paper presents the results of spectral optical measurements of hydrochemical characteristics in the Angara/Yenisei river system (AYRS) extending from Lake Baikal to the estuary of the Yenisei River. For the first time, such large-scale observations were made as part of a joint American-Russian expedition in July and August of 1995, when concentrations of radionuclides, heavy metals, and oil hydrocarbons were assessed. The results of this study were obtained as part of the Russian hydrochemical expedition in July and August, 2019. For in situ measurements and sampling at 14 sampling sites, three optical spectral instruments and appropriate software were used, including big data processing algorithms and an AYRS simulation model. The results show that the water quality in AYRS has improved slightly due to the reasonably reduced anthropogenic industrial impact. Chemical concentrations in water have been found to vary along the Angara River depending on the location of the dams. The results of in situ measurements and modeling evaluations are given. To overcome the uncertainties in the data caused by the large monitoring area, it is recommended to use the combined AYRS simulation model and the universal 8-channel spectrophotometer installed on a fixed platform for continuous monitoring.

Development of a multiparametric (bio)sensing platform for continuous monitoring of stress metabolites

There is a growing need for real-time monitoring of metabolic products that could reflect cell damages over extended periods. In this paper, we report the design and development of an original multiparametric (bio)sensing platform that is tailored for the real-time monitoring of cell metabolites derived from cell cultures. Most attractive features of our developed electrochemical (bio)sensing platform are its easy manufacturing process, that enables seamless scale-up, modular and versatile approach, and low cost. In addition, the developed platform allows a multiparametric analysis instead of single-analyte analysis. Here we provide an overview of the sensors-based analysis of four main factors that can indicate a possible cell deterioration problem during cell-culture: pH, hydrogen peroxide, nitric oxide/nitrite and lactate. Herein, we are proposing a sensors platform based on thick-film coupled to microfluidic technology that can be integrated into any microfluidic system using Luer-lock connectors. This platform allows obtaining an accurate analysis of the secreting stress metabolites during cell/tissues culture.

Digital Biomarkers Enable Automated, Longitudinal Monitoring in a Mouse Model of Aging.

To understand the growing needs of an aging human population, there is demand for scalable and reproducible approaches to study animal models of aging and to test novel therapeutic interventions. We investigated the sensitivity and utility of a continuous monitoring platform and its digital biomarkers (motion, breathing rate, and wheel running) to evaluate behavioral and physiological differences between "young" (12 weeks) and "old" (23 months) male C57BL/6J mice with or without running wheels in the home cage. Compared to young mice, old mice showed marked reductions in motion and breathing rate, as well as altered circadian rhythms. Mice without running wheels possessed lower breathing rates compared to their counterparts with running wheels. Digital biomarkers showed age-dependent changes in response to routine procedures (cage changes and blood sampling) and alterations in subjects that unexpectedly reached endpoint. Continuous collection of digital biomarkers in the home cage can enhance current approaches by providing unbiased longitudinal monitoring for large-scale aging studies.

Принципы построения универсальной платформы непрерывного мониторинга технического состояния инфраструктурных объектов

The article discusses the development of monitoring technologies for industrial and transport infrastructure facilities. The importance of monitoring systems for improving the engineering facility maintenance technologies, as well as the ability to determine pre-failure conditions, predict further changes, and determine the residual operating life, is noted. The authors analyze approaches to the implementation of monitoring systems from the point of view of an optimum confi guration. A list of criteria for evaluating the efficacy of the considered design approaches is provided. Recommendations are given for rational designing of monitoring systems and the optimal sequence of actions is determined for creating a universal platform for continuous monitoring of the condition of engineering facilities. The concept of a universal platform for continuous monitoring for infrastructure facilities in the construction, transport and industry is proposed

Commentary on Some Recent Theses Relevant to Combating Aging: December 2020

Theses reviewed in this issue include "Advances on Chip-In-Cell Wireless Platform for Continuous Monitoring of Physiological Parameters in Single Cells," "Design and Delivery of Synthetic mRNA by a Peptide Nanoparticle," "Inflammation Alters Endothelial Progenitor Cell-derived Exosome Contents and Therapeutic Effect on Myocardial Repair," "Partial Reprogramming: A Shortcut to Rejuvenation," "Renal Angioplasty and Therapeutic Angiogenesis for Renovascular Disease: A Novel Treatment Strategy," and "Targeted EDTA Chelation Therapy with Albumin Nanoparticles to Reverse Arterial Calcification and Restore Vascular Health in Chronic Kidney Disease."

Highly Sensitive Bacteria-Responsive Membranes Consisting of Core-Shell Polyurethane Polyvinylpyrrolidone Electrospun Nanofibers for In Situ Detection of Bacterial Infections.

Bacteria responsive color-changing wound dressings offer a valuable platform for continuous monitoring of the wound bed facilitating early detection of bacterial infections. In this study, we present a highly sensitive electrospun nanofibrous polyurethane wound dressing incorporating a hemicyanine-based chromogenic probe with a labile ester linkage that can be enzymatically cleaved by bacterial lipase released from clinically relevant strains, such as Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA). A rapid chromogenic response was achieved by localizing the dye at the surface of core-shell fibers, resulting in a 5x faster response relative to conventional nanofibers. By incorporating polyvinylpyrrolidone (PVP) dopant in the shell, the sensitivity was boosted to enable detection of bacteria at clinically relevant concentrations after 2 h exposure: 2.5 × 105 CFU/cm2 P. aeruginosa and 1.0 × 106 CFU/cm2 MRSA. Introduction of PVP in the shell also boosted the degree of hydrolysis of the chromogenic probe by a factor of 1.2× after a 3 h exposure to a low concentration of P. aeruginosa (105 CFU/cm2). PVP was also found to improve the discernibility of the color change at high bacterial concentrations. The co-operativity between the chromogenic probe, fiber structure, and polymer composition is well-suited for timely in situ detection of wound infection.

Abstract A21: Digital vivarium cloud platform facilitates nonclinical endpoint assessment in an ovarian carcinoma xenograft model with ascites

Abstract Background: Successful translation of nonclinical data is reliant upon the validity of measures for assessing disease morbidity and endpoint in mouse oncology models. Conventional means of endpoint evaluation (i.e., tumor weight, volume of ascites, or clinical signs) can be subjective and unreliable. Here we demonstrate continuous automated measurement of motion reliably predicts endpoint; is correlative with efficacy in an ovarian cancer xenograft model with ascites; and can be used to improve adherence to the three Rs, the guiding principles utilized to ensure animal welfare when conducting nonclinical research. Methods: Six groups of athymic mice were intraperitoneally inoculated with increasing numbers of ES-2 ovarian cancer cells or control (PBS) and housed in a homecage on a continuous monitoring platform. Leveraging the platform’s videographic and electronic records, we retrospectively analyzed night-time motion data. Based on these analyses, we established a Motion Threshold for noticeable decline in the motion metric. Relative to the Motion Threshold, the following parameters were defined: motion loss post induction (MLPI) and motion loss from endpoint (MLFE). These were in turn analyzed for their ability to predict endpoint in comparison to conventional parameters. Upon validation, the Motion Threshold was applied to a subsequent study to analyze its ability to predict efficacy. Results: In the first study, MLPI showed significant correlation with endpoint when graphed on a linear regression plot (R2 = 0.87; p < 0.0001), while conventional metrics showed low correlations with endpoint: number of tumor nodules (R2 = 0.1334; p = 0.1133), volume of ascites (R2 = 0.2524; p = 0.0240), tumor weight (R2 = 0.1162; p = 0.1413). Additionally, we found the MLFE predicted endpoint earlier than the first onset of clinical signs (p < 0.0001). A subsequent study was performed utilizing the Motion Threshold to analyze the efficacy of cisplatin in combination with OS2966 versus vehicle or both therapies alone. OS2966 + cisplatin significantly extended normal activity of mice (according to the Motion Threshold) compared to vehicle (p = 0.003). The Motion Threshold was also shown to correlate with standard survival curve (R2 = 0.86; p < 0.0001) and was superior to conventional parameters for determining intergroup differences. Conclusion: The results demonstrate the high sensitivity, reproducibility, and objectivity of continuous collection of the motion metric. These results are relevant as they enhance study interpretation and reduce time to humane endpoint. The use of digital metrics also increases statistical power, which can be used to potentially reduce the number of animals required for cancer research, hence facilitating faithfulness to the three Rs. Citation Format: Chibueze D. Nwagwu, Erwin Defensor, Anne-Marie Carbonell, Shawn Carbonell. Digital vivarium cloud platform facilitates nonclinical endpoint assessment in an ovarian carcinoma xenograft model with ascites [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A21.

Vapor intrusion risk evaluation using automated continuous chemical and physical parameter monitoring

AbstractVapor intrusion risk characterization efforts are challenging due to complexities associated with background indoor air constituents, preferential subsurface migration pathways, and representativeness limitations associated with traditional randomly timed time‐integrated sampling methods that do not sufficiently account for factors controlling concentration dynamics. The U.S. Environmental Protection Agency recommends basing risk related decisions on the reasonable maximum exposure (RME). However, with very few exceptions, practitioners have not been applying this criterion. The RME will most likely occur during upward advective flux conditions. As such, for RME determinations, it is important to sample when upward advective flux conditions are occurring. The most common vapor intrusion assessment efforts include randomly timed sample collection events, and therefore do not accurately yield RME estimates. More specifically, researchers have demonstrated that randomly timed sampling schemes can result in false negative determinations of potential risk corresponding to RMEs. For sites experiencing trichloroethylene (TCE) vapor intrusion, the potential for acute risks poses additional challenges, as there is a critical need for rapid response to exposure exceedances to minimize health risks and liabilities. To address these challenges, continuous monitoring platforms have been deployed to monitor indoor concentrations of key volatile constituents, atmospheric pressure, and pressure differential conditions that can result in upward toxic vapor transport and entry into overlying buildings. This article demonstrates how vapor intrusion RME‐based risks can be successfully and efficiently determined using continuous monitoring of concentration and parameters indicating upward advective chemical flux. Time series analyses from multiple selected 8‐ and 24‐hr time increments during upward advective TCE flux conditions were performed to simulate results expected from the most commonly employed sampling methods. These analyses indicate that, although most of the selected time increments overlap within the same 24‐hr window, results and conclusions vary. As such, these findings demonstrate that continuous monitoring of concentration and parameters such as differential pressure and determination of a time‐weighted concentration average over a selected duration when upward advective flux is occurring can allow for a realistic RME‐based risk estimate.

Context-Aware Human Activity Recognition (CAHAR) in-the-Wild Using Smartphone Accelerometer

Smartphones are a promising platform for continuous monitoring of human behavior. However, the ability to capture people’s behavioral patterns in-the-wild is a challenge, as the user’s behavior and physical activities can vary, given the variability of settings and environments. Modeling and understanding of human activity in-the-wild must not overlook a user’s behavioral context, which is just as crucial as recognizing the range of physical activities. The work in this paper presents a novel framework for context-aware human activity recognition by incorporating human behavioral contexts with physical activities. The proposed framework utilizes a series of machine learning classifiers to validate the efficiency of the proposed method.

IRIS: A Modular Platform for Continuous Monitoring and Caretaker Notification in the Intensive Care Unit.

New approaches are needed to interpret large amounts of physiologic data continuously recorded in the ICU. We developed and prospectively validated a versatile platform (IRIS) for real-time ICU physiologic monitoring, clinical decision making, and caretaker notification. IRIS was implemented in the neurointensive care unit to stream multimodal time series data, including EEG, intracranial pressure (ICP), and brain tissue oxygenation (PbtO2), from ICU monitors to an analysis server. IRIS was applied for 364 patients undergoing continuous EEG, 26 patients undergoing burst suppression monitoring, and four patients undergoing intracranial pressure and brain tissue oxygen monitoring. Custom algorithms were used to identify periods of elevated ICP, compute burst suppression ratios (BSRs), and detect faulty or disconnected EEG electrodes. Hospital staff were notified of clinically relevant events using our secure API to route alerts through a password-protected smartphone application. Sustained increases in ICP and concordant decreases in PbtO2 were reliably detected using user-defined thresholds and alert throttling. BSR trends computed by the platform correlated highly with manual neurologist markings (r20.633-0.781; p < 0.0001). The platform identified EEG electrodes with poor signal quality with 95% positive predictive value, and reduced latency of technician response by 93%. This study validates a flexible real-time platform for monitoring and interpreting ICU data and notifying caretakers of actionable results, with potential to reduce the manual burden of continuous monitoring services on care providers. This work represents an important step toward facilitating translational medical data analytics to improve patient care and reduce health care costs.

In vivo monitoring of cerebral glucose with an updated on-line electroanalytical system.

Because cerebral species involve rapid events, increasing the temporal resolution to realize in vivo near-real-time measurements is desirable. Here, we aimed to improve the low resolution of our previous on-line electroanalytical system by decreasing the dead volume and reducing molecular dispersion. This updated system has advantages of elevated time resolution and accelerated analysis for on-line monitoring of glucose versus the previous system. Finally, this new system was successfully applied to continuous measurement of cerebral glucose in vivo during global ischemia/reperfusion events. This study is expected to offer a reliable on-line analytical platform for continuous monitoring of important species associated with fast physiological and pathological events in vivo. Graphical abstract.

A microfluidic platform for continuous monitoring of dopamine homeostasis in dopaminergic cells

Homeostasis of dopamine, a classical neurotransmitter, is a key indicator of neuronal health. Dysfunction in the regulation of dopamine is implicated in a long list of neurological disorders, including addiction, depression, and neurodegeneration. The existing methods used to evaluate dopamine homeostasis in vitro are inconvenient and do not allow for continuous non-destructive measurement. In response to this challenge, we introduce an integrated microfluidic system that combines dopaminergic cell culture and differentiation with electroanalytical measurements of extracellular dopamine in real-time at any point during an assay. We used the system to examine the behavior of differentiated SH-SY5Y cells upon exposure to four dopamine transporter ant/agonists (cocaine, ketamine, epigallocatechin gallate, and amphetamine) and study their pharmacokinetics. The IC50 values of cocaine, ketamine, and epigallocatechin gallate were determined to be (average ± standard deviation) 3.7 ± 1.1 µM, 51.4 ± 17.9 µM, and 2.6 ± 0.8 µM, respectively. Furthermore, we used the new system to study amphetamine-mediated dopamine release to probe the related phenomena of dopamine transporter-mediated reverse-transport and dopamine release from vesicles. We propose that this platform, which is the first platform to simultaneously evaluate uptake and release, could be useful to screen for drugs and other agents that target dopaminergic neurons and the function of the dopamine transporter. More broadly, this platform should be adaptable for any application that could benefit from high-temporal resolution electroanalysis combined with multi-day cell culture using small numbers of cells.

Self-sustaining water-motion sensor platform for continuous monitoring of frequency and amplitude dynamics

A self-sustaining sensor platform is a core component for Internet-of-Things and smart-grid systems. However, monitoring, processing, and displaying the minute changes of a targeted-environmental element in a real-time fashion without external power sources is challenging because of a practical difficulty of doing energy harvesting and analysis of dynamics at the same time. Here, we present a self-sustaining water-motion-sensing (SS-WMS) platform to monitor and display the time-varying dynamics of water-motion, i.e., frequency and amplitude, using only the energy harvested from the water-motion itself. A water-contact triboelectric nanogenerator (WC-TENG) produces electrical energy, correlated with the repetitive squeezing and releasing of a water droplet. The SS-WMS integrated circuit (IC) harvests the energy and simultaneously analyzes the dynamics of water-motion, which is converted into binary codes to be displayed through LEDs powered by the gathered energy. The proposed platform would contribute to advanced sensing functions of a self-sustaining system for various targeted-ambient elements.