Jonathan W. Hennek

Universal mobile electrochemical detector designed for use in resource-limited applications

Significance The ability to perform electrochemical testing in the field, and in resource-limited environments, and to transmit data automatically to “the cloud” can enable a broad spectrum of analyses useful for personal and public health, clinical analysis, food safety, and environmental monitoring. Although the developed world has many options for analysis and web connection, the developing world does not have broad access to either the expensive equipment necessary to perform these tests or the advanced technologies required for network connectivity. To overcome these limitations, we have developed a simple, affordable, handheld device that can perform all the most common electrochemical analyses, and transmit the results of testing to the cloud from any phone, over any network, anywhere in the world. This paper describes an inexpensive, handheld device that couples the most common forms of electrochemical analysis directly to “the cloud” using any mobile phone, for use in resource-limited settings. The device is designed to operate with a wide range of electrode formats, performs on-board mixing of samples by vibration, and transmits data over voice using audio—an approach that guarantees broad compatibility with any available mobile phone (from low-end phones to smartphones) or cellular network (second, third, and fourth generation). The electrochemical methods that we demonstrate enable quantitative, broadly applicable, and inexpensive sensing with flexibility based on a wide variety of important electroanalytical techniques (chronoamperometry, cyclic voltammetry, differential pulse voltammetry, square wave voltammetry, and potentiometry), each with different uses. Four applications demonstrate the analytical performance of the device: these involve the detection of (i) glucose in the blood for personal health, (ii) trace heavy metals (lead, cadmium, and zinc) in water for in-field environmental monitoring, (iii) sodium in urine for clinical analysis, and (iv) a malarial antigen (Plasmodium falciparum histidine-rich protein 2) for clinical research. The combination of these electrochemical capabilities in an affordable, handheld format that is compatible with any mobile phone or network worldwide guarantees that sophisticated diagnostic testing can be performed by users with a broad spectrum of needs, resources, and levels of technical expertise.

From the Bench to the Field in Low‐Cost Diagnostics: Two Case Studies

Despite the growth of research in universities on point-of-care (POC) diagnostics for global health, most devices never leave the laboratory. The processes that move diagnostic technology from the laboratory to the field--the processes intended to evaluate operation and performance under realistic conditions--are more complicated than they might seem. Two case studies illustrate this process: the development of a paper-based device to measure liver function, and the development of a device to identify sickle cell disease based on aqueous multiphase systems (AMPS) and differences in the densities of normal and sickled cells. Details of developing these devices provide strategies for forming partnerships, prototyping devices, designing studies, and evaluating POC diagnostics. Technical and procedural lessons drawn from these experiences may be useful to those designing diagnostic tests for developing countries, and more generally, technologies for use in resource-limited environments.

Density-based separation in multiphase systems provides a simple method to identify sickle cell disease

Significance Red blood cells with a high density (ρ > 1.120 g/cm3) are characteristic of sickle cell disease. This paper demonstrates a density-based separation of red blood cells in a system of aqueous multiphase polymers that enables a visual test that identifies sickle cell disease, starting from samples of whole blood, in less than 12 min. This low-cost, simple test could provide a means to enable diagnosis of sickle cell disease in low-resource settings and enable life-saving interventions for children with the disease. The method itself provides a demonstration of the use of a biophysical indicator (here, density) rather than a biochemical marker (e.g., proteins separated by gel electrophoresis) as a means to do point-of-care hematology. Although effective low-cost interventions exist, child mortality attributable to sickle cell disease (SCD) remains high in low-resource areas due, in large part, to the lack of accessible diagnostic methods. The presence of dense (ρ > 1.120 g/cm3) cells is characteristic of SCD. The fluid, self-assembling step-gradients in density created by aqueous multiphase systems (AMPSs) identifies SCD by detecting dense cells. AMPSs separate different forms of red blood cells by density in a microhematocrit centrifuge and provide a visual means to distinguish individuals with SCD from those with normal hemoglobin or with nondisease, sickle-cell trait in under 12 min. Visual evaluation of a simple two-phase system identified the two main subclasses of SCD [homozygous (Hb SS) and heterozygous (Hb SC)] with a sensitivity of 90% (73–98%) and a specificity of 97% (86–100%). A three-phase system identified these two types of SCD with a sensitivity of 91% (78–98%) and a specificity of 88% (74–98%). This system could also distinguish between Hb SS and Hb SC. To the authors’ knowledge, this test demonstrates the first separation of cells by density with AMPSs, and the usefulness of AMPSs in point-of-care diagnostic hematology.

Using Magnetic Levitation for Non-Destructive Quality Control of Plastic Parts

Magnetic levitation (MagLev) enables rapid and non-destructive quality control of plastic parts. The feasibility of MagLev as a method to: i) rapidly assess injection-molded plastic parts for defects during process optimization, ii) monitor the degradation of plastics after exposure to harsh environmental conditions, and iii) detect counterfeit polymers by density is demonstrated.

Evaluation of a Density-Based Rapid Diagnostic Test for Sickle Cell Disease in a Clinical Setting in Zambia

Although simple and low-cost interventions for sickle cell disease (SCD) exist in many developing countries, child mortality associated with SCD remains high, in part, because of the lack of access to diagnostic tests for SCD. A density-based test using aqueous multiphase systems (SCD-AMPS) is a candidate for a low-cost, point-of-care diagnostic for SCD. In this paper, the field evaluation of SCD-AMPS in a large (n = 505) case-control study in Zambia is described. Of the two variations of the SCD-AMPS used, the best system (SCD-AMPS-2) demonstrated a sensitivity of 86% (82–90%) and a specificity of 60% (53–67%). Subsequent analysis identified potential sources of false positives that include clotting, variation between batches of SCD-AMPS, and shipping conditions. Importantly, SCD-AMPS-2 was 84% (62–94%) sensitive in detecting SCD in children between 6 months and 1 year old. In addition to an evaluation of performance, an assessment of end-user operability was done with health workers in rural clinics in Zambia. These health workers rated the SCD-AMPS tests to be as simple to use as lateral flow tests for malaria and HIV.

Fractionating Polymer Microspheres as Highly Accurate Density Standards.

This paper describes a method of isolating small, highly accurate density-standard beads and characterizing their densities using accurate and experimentally traceable techniques. Density standards have a variety of applications, including the characterization of density gradients, which are used to separate objects in a variety of fields. Glass density-standard beads can be very accurate (±0.0001 g cm(-3)) but are too large (3-7 mm in diameter) for many applications. When smaller density standards are needed, commercial polymer microspheres are often used. These microspheres have standard deviations in density ranging from 0.006 to 0.021 g cm(-3); these distributions in density make these microspheres impractical for applications demanding small steps in density. In this paper, commercial microspheres are fractionated using aqueous multiphase systems (AMPS), aqueous mixture of polymers and salts that spontaneously separate into phases having molecularly sharp steps in density, to isolate microspheres having much narrower distributions in density (standard deviations from 0.0003 to 0.0008 g cm(-3)) than the original microspheres. By reducing the heterogeneity in densities, this method reduces the uncertainty in the density of any specific bead and, therefore, improves the accuracy within the limits of the calibration standards used to characterize the distributions in density.

Diagnosis of iron deficiency anemia using density-based fractionation of red blood cells

Iron deficiency anemia (IDA) is a nutritional disorder that impacts over one billion people worldwide; it may cause permanent cognitive impairment in children, fatigue in adults, and suboptimal outcomes in pregnancy. IDA can be diagnosed by detection of red blood cells (RBCs) that are characteristically small (microcytic) and deficient in hemoglobin (hypochromic), typically by examining the results of a complete blood count performed by a hematology analyzer. These instruments are expensive, not portable, and require trained personnel; they are, therefore, unavailable in many low-resource settings. This paper describes a low-cost and rapid method to diagnose IDA using aqueous multiphase systems (AMPS)-thermodynamically stable mixtures of biocompatible polymers and salt that spontaneously form discrete layers having sharp steps in density. AMPS are preloaded into a microhematocrit tube and used with a drop of blood from a fingerstick. After only two minutes in a low-cost centrifuge, the tests (n = 152) were read by eye with a sensitivity of 84% (72-93%) and a specificity of 78% (68-86%), corresponding to an area under the curve (AUC) of 0.89. The AMPS test outperforms diagnosis by hemoglobin alone (AUC = 0.73) and is comparable to methods used in clinics like reticulocyte hemoglobin concentration (AUC = 0.91). Standard machine learning tools were used to analyze images of the resulting tests captured by a standard desktop scanner to 1) slightly improve diagnosis of IDA-sensitivity of 90% (83-96%) and a specificity of 77% (64-87%), and 2) predict several important red blood cell parameters, such as mean corpuscular hemoglobin concentration. These results suggest that the use of AMPS combined with machine learning provides an approach to developing point-of-care hematology.