Battery-Less NFC Potentiostat for Electrochemical Point-of-Care Sensors Based on COTS Components.

This work studies the feasibility of using a battery-less Near-Field Communication (NFC) potentiostat for the next generation of electrochemical point-of-care sensors. A design based on an NFC microchip, a microcontroller, and a custom potentiostat based on an operational amplifier is presented. A proof-of-concept prototype has been designed and used to quantify glucose concentration using commercial glucose test strips from chronoamperometry measurements. The device is harvested and the sensor is read using a mobile phone. The prototype uses an antenna loop covered with ferrite sheets to ensure stable operation of the electronics when the mobile phone is used as reader. The use of ferrite reduces the detuning caused by the proximity of the metal parts of the mobile phone. A comparison with a commercial glucometer device is provided. Results obtained using a commercial glucometer and those provided by the proposed potentiostat show an excellent agreement.

Application of Gaussian process regression and asymmetric least squares baseline algorithm on the determination of electrochemical sensor characteristics: A case study on SARS-CoV-2 glucometer

In this study, it was aimed to determine limit of detection, limit of quantification, and signal to noise ratio by the use of SARS-CoV-2 glucometer response data in "Singh, N·K., Ray, P., Carlin, A.F., Morgan, S·C., Magallanes, C., Laurent, L.C., Aronoff-Spencer, E.S., Hall, D.A., 2021b. Dataset on optimization and development of a point-of-care glucometer-based SARS-CoV-2 detection assay using aptamers. Data Brief 38, 107,278.” and by Bayesian optimization and asymmetric least squares baseline algorithm which was used for prediction of response curve and baseline. It was seen that the predicted limit of detection and limit of quantification reached a certain level after a certain number of training observations and ranged between 0.9-16 pM and 2.8–44 pM respectively.

Electrochemical Sensors for New Challenges

This article focuses upon new challenges faced by today’s society which electrochemical sensors maybe able to address. Focusing primarily upon two of the major challenges faced at the time of writing;the opioid crisis caused by fentanyl and the deadly Covid-19 pandemic, the employment of electrochemical sensors is assessed to determine the contribution they could make toward tackling these problems. Although only a small scope of the electrochemical research present is covered within this article the principles discussed are directly translated to other fields where electrochemical sensors could be applied. This article to aims to highlight the uses of electrochemical sensors and discusses in detail both their advantages but also where further improvements are required to improve their applications across a range of fields.

Seeking Opportunity in Crisis: Redesigning Care for High-risk Diabetics During the Pandemic.

Management of uncontrolled diabetic (DM) patients has always been a challenge across healthcare settings, but recently we noticed a surge in the number of uncontrolled DM patient in our clinic patients' population during the COVID19 pandemic. This in part a combination of disruptions to care, delayed or inaccessible care, and poor diet and physical activity. To address this issue, we formed a multidisciplinary Diabetes Initiative Team consisting of attending physicians, residents, clinical pharmacist, nurse manager, care manager, and coordinator, along with supportive staffs in our Internal Medicine Residency clinic. Our aim was to reengage diabetic patients in the outpatient setting and to overcome barriers limiting diabetic care.

Dataset on optimization and development of a point-of-care glucometer-based SARS-CoV-2 detection assay using aptamers.

We present supplementary data for the published article, "Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer" [1]. The assay described is designed to be performed at home or in a clinic without expensive instrumentation or professional training. SARS-CoV-2 is detected by an aptamer-based assay that targets the Nucleocapsid (N) or Spike (S) antigens. Binding of the N or S protein to their respective aptamer results in the competitive release of a complementary antisense-invertase enzyme complex. The released enzyme then catalyzes the conversion of sucrose to glucose that is measured by an off-the-shelf glucometer. The data presented here describe the optimization of the assay parameters and their contribution to developing this aptamer-based assay to detect SARS-CoV-2. The assay performance was checked in a standard buffer, contrived samples, and patient samples validated with well-established scientific methods. The resulting dataset can be used to further develop glucometer-based assays for diagnosing other communicable and non-communicable diseases.

Hitting the diagnostic sweet spot: Point-of-care SARS-CoV-2 salivary antigen testing with an off-the-shelf glucometer.

Significant barriers to the diagnosis of latent and acute SARS-CoV-2 infection continue to hamper population-based screening efforts required to contain the COVID-19 pandemic in the absence of widely available antiviral therapeutics or vaccines. We report an aptamer-based SARS-CoV-2 salivary antigen assay employing only low-cost reagents ($3.20/test) and an off-the-shelf glucometer. The test was engineered around a glucometer as it is quantitative, easy to use, and the most prevalent piece of diagnostic equipment globally, making the test highly scalable with an infrastructure that is already in place. Furthermore, many glucometers connect to smartphones, providing an opportunity to integrate with contact tracing apps, medical providers, and electronic health records. In clinical testing, the developed assay detected SARS-CoV-2 infection in patient saliva across a range of viral loads - as benchmarked by RT-qPCR - within 1 h, with 100% sensitivity (positive percent agreement) and distinguished infected specimens from off-target antigens in uninfected controls with 100% specificity (negative percent agreement). We propose that this approach provides an inexpensive, rapid, and accurate diagnostic for distributed screening of SARS-CoV-2 infection at scale.