Smartphone-based clinical diagnostics: towards democratization of evidence-based health care

Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review

BACKGROUND

Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field.

OBJECTIVE

This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations.

METHODS

A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis.

RESULTS

The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts.

CONCLUSIONS

Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.

Smartphone-Based Artificial Intelligence for the Detection and Diagnosis of Pediatric Diseases: A Comprehensive Review

In recent years, the use of smartphones and other wireless technology in medical care has developed rapidly. However, in some cases, especially for pediatric medical problems, the reliability of information accessed by mobile health technology remains debatable. The main aim of this paper is to evaluate the relevance of smartphone applications in the detection and diagnosis of pediatric medical conditions for which the greatest number of applications have been developed. This is the case of smartphone applications developed for the diagnosis of acute otitis media, otitis media with effusion, hearing impairment, obesity, amblyopia, and vision screening. In some cases, the information given by these applications has significantly improved the diagnostic ability of physicians. However, distinguishing between applications that can be effective and those that may lead to mistakes can be very difficult. This highlights the importance of a careful application selection before including smartphone-based artificial intelligence in everyday clinical practice.

Online dissemination of Cochrane reviews on digital health technologies: a cross-sectional study

BACKGROUND

This cross-sectional study investigated the online dissemination of Cochrane reviews on digital health technologies.

METHODS

We searched the Cochrane Database of Systematic Reviews from inception up to May 2023. Cochrane reviews with any population (P), intervention or concept supported by any digital technology (I), any or no comparison (C), and any health outcome (O) were included. Data on review characteristics (bibliographic information, PICO, and evidence quality) and dissemination strategies were extracted and processed. Dissemination was assessed using review information on the Cochrane website and Altmetric data that trace the mentions of academic publications in nonacademic online channels. Data were analysed using descriptive statistics and binary logistic regression analysis.

RESULTS

Out of 170 records identified in the search, 100 Cochrane reviews, published between 2005 and 2023, were included. The reviews focused on consumers (e.g. patients, n = 86), people of any age (n = 44), and clinical populations (n = 68). All reviews addressed interventions or concepts supported by digital technologies with any devices (n = 73), mobile devices (n = 17), or computers (n = 10). The outcomes focused on disease treatment (n = 56), health promotion and disease prevention (n = 27), or management of care delivery (n = 17). All reviews included 1-132 studies, and half included 1-10 studies. Meta-analysis was performed in 69 reviews, and certainty of evidence was rated as high or moderate for at least one outcome in 46 reviews. In agreement with the Cochrane guidelines, all reviews had a plain language summary (PLS) that was available in 3-14 languages. The reviews were disseminated (i.e. mentioned online) predominantly via X/Twitter (n = 99) and Facebook (n = 69). Overall, 51 reviews were mentioned in up to 25% and 49 reviews in 5% of all research outputs traced by Altmetric data. Dissemination (i.e. higher Altmetric scores) was associated with bibliographic review characteristics (i.e. earlier publication year and PLS available in more languages), but not with evidence quality (i.e. certainty of evidence rating, number of studies, or meta-analysis performed in review).

CONCLUSIONS

Online attention towards Cochrane reviews on digital health technologies is high. Dissemination is higher for older reviews and reviews with more PLS translations. Measures are required to improve dissemination of Cochrane reviews based on evidence quality.

SYSTEMATIC REVIEW REGISTRATION

The study was prospectively registered at the Open Science Framework ( https://osf.io/mpw8u/ ).

A commentary on the development and use of smartphone imaging devices

Current-age smartphones are known for their wide array of functionality and are now being utilized in the field of healthcare and medicine due to their proven capabilities as smartphone imaging devices (SIDs). Recent technical advancements enabled the integration of special add-on lenses with smartphones to transform them into SIDs. With the rising demand for efficient point-of-care (PoC) devices for better diagnostic applications, SIDs will be a one-stop solution. Additionally, portability, user-friendliness and low-cost make it accessible for all even at remote locations. Furthermore, improvements in resolution, magnification and field-of-view (FOV) have attracted the scientific community to use SIDs in various biomedical applications such as disease diagnosis, food quality control and pathogen detection. SIDs can be arranged in various combinational setups by using different illumination sources and optics to achieve suitable contrast and visibility of the specimen under study. This Commentary illustrates the various illumination sources used in SID and also spotlights their design and applications.

Smartphone-based device for point-of-care diagnostics of pulmonary inflammation using convolutional neural networks (CNNs)

In pulmonary inflammation diseases, like COVID-19, lung involvement and inflammation determine the treatment regime. Respiratory inflammation is typically arisen due to the cytokine storm and the leakage of the vessels for immune cells recruitment. Currently, such a situation is detected by the clinical judgment of a specialist or precisely by a chest CT scan. However, the lack of accessibility to the CT machines in many poor medical centers as well as its expensive service, demands more accessible methods for fast and cheap detection of lung inflammation. Here, we have introduced a novel method for tracing the inflammation and lung involvement in patients with pulmonary inflammation, such as COVID-19, by a simple electrolyte detection in their sputum samples. The presence of the electrolyte in the sputum sample results in the fern-like structures after air-drying. These fern patterns are different in the CT positive and negative cases that are detected by an AI application on a smartphone and using a low-cost and portable mini-microscope. Evaluating 160 patient-derived sputum sample images, this method demonstrated an interesting accuracy of 95%, as confirmed by CT-scan results. This finding suggests that the method has the potential to serve as a promising and reliable approach for recognizing lung inflammatory diseases, such as COVID-19.

Advancing Point-of-Care Diagnosis: Digitalizing Combinatorial Biomarker Signals for Lupus Nephritis

To improve the efficiency and patient coverage of the current healthcare system, user-friendly novel homecare devices are urgently needed. In this work, we developed a smartphone-based analyzing and reporting system (SBARS) for biomarker detection in lupus nephritis (LN). This system offers a cost-effective alternative to traditional, expensive large equipment in signal detection and quantification. This innovative approach involves using a portable and affordable microscopic reader to capture biomarker signals. Through smartphone-based image processing techniques, the intensity of each biomarker signal is analyzed. This system exhibited comparable performance to a commercial Genepix scanner in the detection of two potential novel biomarkers of LN, VISG4 and TNFRSF1b. Importantly, this smartphone-based analyzing and reporting system allows for discriminating LN patients with active renal disease from healthy controls with the area-under-the-curve (AUC) value = 0.9 for TNFRSF1b and 1.0 for VSIG4, respectively, indicating high predictive accuracy.

Single-Atom Site SERS Chip for Rapid, Ultrasensitive, and Reproducible Direct-Monitoring of RNA Binding

Ribonucleic acids (RNA) play active roles within cells or viruses by catalyzing biological reactions, controlling gene expression, and communicating responses to cellular signals. Rapid monitoring RNA variation has become extremely important for appropriate clinical decisions and frontier biological research. However, the most widely used method for RNA detection, nucleic acid amplification, is restricted by a mandatory temperature cycling period of ≈1 h required to reach target detection criteria. Herein, a direct detection approach via single-atom site integrated surface-enhanced Raman scattering (SERS) monitoring nucleic acid pairing reaction, can be completed within 3 min and reaches high sensitivity and extreme reproducibility for COVID-19 and two other influenza viruses' detection. The mechanism is that a single-atom site on SERS chip, enabled by positioning a single-atom oxide coordinated with a specific complementary RNA probe on chip nanostructure hotspots, can effectively bind target RNA analytes to enrich them at designed sites so that the binding reaction can be detected through Raman signal variation. This ultrafast, sensitive, and reproducible single-atom site SERS chip approach paves the route for an alternative technique of immediate RNA detection. Moreover, single-atom site SERS is a novel surface enrichment strategy for SERS active sites for other analytes at ultralow concentrations.

Fast detection of bacterial gut pathogens on miniaturized devices: an overview

INTRODUCTION

Gut microbes pose challenges like colon inflammation, deadly diarrhea, antimicrobial resistance dissemination, and chronic disease onset. Development of early, rapid and specific diagnosis tools is essential for improving infection control. Point-of-care testing (POCT) systems offer rapid, sensitive, low-cost and sample-to-answer methods for microbe detection from various clinical and environmental samples, bringing the advantages of portability, automation, and simple operation.

AREAS COVERED

Rapid detection of gut microbes can be done using a wide array of techniques including biosensors, immunological assays, electrochemical impedance spectroscopy, mass spectrometry and molecular biology. Inclusion of Internet of Things, machine learning, and smartphone-based point-of-care applications is an important aspect of POCT. In this review, the authors discuss various fast diagnostic platforms for gut pathogens and their main challenges.

EXPERT OPINION

Developing effective assays for microbe detection can be complex. Assay design must consider factors like target selection, real-time and multiplex detection, sample type, reagent stability and storage, primer/probe design, and optimizing reaction conditions for accuracy and sensitivity. Mitigating these challenges requires interdisciplinary collaboration among scientists, clinicians, engineers, and industry partners. Future efforts are essential to enhance sensitivity, specificity, and versatility of POCT systems for gut microbe detection and quantification, advancing infectious disease diagnostics and management.

A digital image colorimetry system based on smart devices for immediate and simultaneous determination of enzyme-linked immunosorbent assays

Standard enzyme-linked immunosorbent assays based on microplates are frequently utilized for various molecular sensing, disease screening, and nanomedicine applications. Comparing this multi-well plate batched analysis to non-batched or non-standard testing, the diagnosis expenses per patient are drastically reduced. However, the requirement for rather big and pricey readout instruments prevents their application in environments with limited resources, especially in the field. In this work, a handheld cellphone-based colorimetric microplate reader for quick, credible, and novel analysis of digital images of human cancer cell lines at a reasonable price was developed. Using our in-house-developed app, images of the plates are captured and sent to our servers, where they are processed using a machine learning algorithm to produce diagnostic results. Using FDA-approved human epididymis protein of ovary IgG (HE4), prostate cancer cell line (PC3), and bladder cancer cell line (5637) ELISA tests, we successfully examined this mobile platform. The accuracies for the HE4, PC3, and 5637 tests were 93%, 97.5%, and 97.2%, respectively. By contrasting the findings with the measurements made using optical absorption EPOCH microplate readers and optical absorption Tecan microplate readers, this approach was found to be accurate and effective. As a result, digital image colorimetry on smart devices offered a practical, user-friendly, affordable, precise, and effective method for quickly identifying human cancer cell lines. Thus, healthcare providers might use this portable device to carry out high-throughput illness screening, epidemiological investigations or monitor vaccination campaigns.

Supra-Quantum Dot Assemblies to Maximize Color-Based Multiplexed Fluorescence Detection with a Smartphone Camera

Photoluminescence (PL) imaging and bioanalysis with smartphone-based devices are of growing interest for point-of-care/point-of-need diagnostics. Strategies for maximizing sensitivity have been explored in this context, but color multiplexing has been very limited, with its maximum level unexplored. Here, we evaluated color multiplexing with smartphone-based PL imaging by using supra-nanoparticle assemblies of quantum dots (supra-QDs). These materials were prepared as composite colors that were tailored to the red-green-blue (RGB) color space of smartphone cameras by coassembling different ratios of R-, G-, and B-emitting QDs on a silica nanoparticle scaffold. The supra-QDs were characterized and used to label cell-sized objects that were measured under flow with a smartphone-based device. Each color followed an approximately linear trajectory in the RGB space, and training of support vector machine models enabled color classification with overall accuracies ≥87% for 10-color multiplexing and better accuracies for fewer colors. Most misclassification occurred at low signal levels, such that establishing a nonclassifiable zone near the origin of RGB color space improved the overall 10-color classification accuracy to ≥94%. Similar improvements in accuracy with greater retention of data were possible with a probabilistic rather than a radial threshold. Simulations that were parameterized by experimental data suggested that ≥14-color multiplexing with accuracies ≥90% should be possible with an optimized supra-QD color set. This study is an important foundation for advancing RGB color-based multiplexing for imaging and analyses with smartphone cameras and related charge-coupled device and CMOS color image sensor technologies.

Design and Usability Study of a Point of Care mHealth App for Early Dry Eye Screening and Detection

Significantly increased eye blink rate and partial blinks have been well documented in patients with dry eye disease (DED), a multifactorial eye disorder with few effective methods for clinical diagnosis. In this study, a point of care mHealth App named "EyeScore" was developed, utilizing blink rate and patterns as early clinical biomarkers for DED. EyeScore utilizes an iPhone for a 1-min in-app recording of eyelid movements. The use of facial landmarks, eye aspect ratio (EAR) and derivatives enabled a comprehensive analysis of video frames for the determination of eye blink rate and partial blink counts. Smartphone videos from ten DED patients and ten non-DED controls were analyzed to optimize EAR-based thresholds, with eye blink and partial blink results in excellent agreement with manual counts. Importantly, a clinically relevant algorithm for the calculation of "eye healthiness score" was created, which took into consideration eye blink rate, partial blink counts as well as other demographic and clinical risk factors for DED. This 10-point score can be conveniently measured anytime with non-invasive manners and successfully led to the identification of three individuals with DED conditions from ten non-DED controls. Thus, EyeScore can be validated as a valuable mHealth App for early DED screening, detection and treatment monitoring.

Low-rate smartphone videoscopy for microsecond luminescence lifetime imaging with machine learning

Time-resolved techniques have been widely used in time-gated and luminescence lifetime imaging. However, traditional time-resolved systems require expensive lab equipment such as high-speed excitation sources and detectors or complicated mechanical choppers to achieve high repetition rates. Here, we present a cost-effective and miniaturized smartphone lifetime imaging system integrated with a pulsed ultraviolet (UV) light-emitting diode (LED) for 2D luminescence lifetime imaging using a videoscopy-based virtual chopper (V-chopper) mechanism combined with machine learning. The V-chopper method generates a series of time-delayed images between excitation pulses and smartphone gating so that the luminescence lifetime can be measured at each pixel using a relatively low acquisition frame rate (e.g. 30 frames per second [fps]) without the need for excitation synchronization. Europium (Eu) complex dyes with different luminescent lifetimes ranging from microseconds to seconds were used to demonstrate and evaluate the principle of V-chopper on a 3D-printed smartphone microscopy platform. A convolutional neural network (CNN) model was developed to automatically distinguish the gated images in different decay cycles with an accuracy of >99.5%. The current smartphone V-chopper system can detect lifetime down to ∼75 µs utilizing the default phase shift between the smartphone video rate and excitation pulses and in principle can detect much shorter lifetimes by accurately programming the time delay. This V-chopper methodology has eliminated the need for the expensive and complicated instruments used in traditional time-resolved detection and can greatly expand the applications of time-resolved lifetime technologies.

Smartphone-Based Chemiluminescence Glucose Biosensor Employing a Peroxidase-Mimicking, Guanosine-Based Self-Assembled Hydrogel

Chemiluminescence is widely used for hydrogen peroxide detection, mainly exploiting the highly sensitive peroxidase-luminol-H₂O₂ system. Hydrogen peroxide plays an important role in several physiological and pathological processes and is produced by oxidases, thus providing a straightforward way to quantify these enzymes and their substrates. Recently, biomolecular self-assembled materials obtained by guanosine and its derivatives and displaying peroxidase enzyme-like catalytic activity have received great interest for hydrogen peroxide biosensing. These soft materials are highly biocompatible and can incorporate foreign substances while preserving a benign environment for biosensing events. In this work, a self-assembled guanosine-derived hydrogel containing a chemiluminescent reagent (luminol) and a catalytic cofactor (hemin) was used as a H₂O₂-responsive material displaying peroxidase-like activity. Once loaded with glucose oxidase, the hydrogel provided increased enzyme stability and catalytic activity even in alkaline and oxidizing conditions. By exploiting 3D printing technology, a smartphone-based portable chemiluminescence biosensor for glucose was developed. The biosensor allowed the accurate measurement of glucose in serum, including both hypo- and hyperglycemic samples, with a limit of detection of 120 µmol L^-1. This approach could be applied for other oxidases, thus enabling the development of bioassays to quantify biomarkers of clinical interest at the point of care.

A study establishing sensitivity and accuracy of smartphone photography in ophthalmologic community outreach programs: Review of a smart eye camera

Purpose

Diseases affecting the cornea are a major cause of corneal blindness globally. The pressing issue we are facing today is the lack of diagnostic devices in rural areas to diagnose these conditions. The aim of the study is to establish sensitivity and accuracy of smartphone photography using a smart eye camera (SEC) in ophthalmologic community outreach programs.

Methods

In this pilot study, a prospective non-randomized comparative analysis of inter-observer variability of anterior segment imaging recorded using an SEC was performed. Consecutive 100 patients with corneal pathologies, who visited the cornea specialty outpatient clinic, were enrolled. They were examined with a conventional non-portable slit lamp by a cornea consultant, and the diagnoses were recorded. This was compared with the diagnoses made by two other consultants based on SEC videos of the anterior segment of the same 100 patients. The accuracy of SEC was accessed using sensitivity, specificity, PPV, and NPV. Kappa statistics was used to find the agreement between two consultants by using STATA 17.0 (Texas, USA).

Results

There was agreement between the two consultants to diagnosing by using SEC. Above 90% agreements were found in all the diagnoses, which were statistically significant (P-value < 0.001). More than 90% sensitivity and a negative predictive value were found.

Conclusion

SEC can be used successfully in the community outreach programs like field visits, eye camps, teleophthalmology, and community centers, where either a clinical setup is lacking or ophthalmologists are not available.

Sample-to-answer platform for the clinical evaluation of COVID-19 using a deep learning-assisted smartphone-based assay

Since many lateral flow assays (LFA) are tested daily, the improvement in accuracy can greatly impact individual patient care and public health. However, current self-testing for COVID-19 detection suffers from low accuracy, mainly due to the LFA sensitivity and reading ambiguities. Here, we present deep learning-assisted smartphone-based LFA (SMART^AI-LFA) diagnostics to provide accurate decisions with higher sensitivity. Combining clinical data learning and two-step algorithms enables a cradle-free on-site assay with higher accuracy than the untrained individuals and human experts via blind tests of clinical data (n = 1500). We acquired 98% accuracy across 135 smartphone application-based clinical tests with different users/smartphones. Furthermore, with more low-titer tests, we observed that the accuracy of SMART^AI-LFA was maintained at over 99% while there was a significant decrease in human accuracy, indicating the reliable performance of SMART^AI-LFA. We envision a smartphone-based SMART^AI-LFA that allows continuously enhanced performance by adding clinical tests and satisfies the new criterion for digitalized real-time diagnostics.

Automated Wound Image Segmentation: Transfer Learning from Human to Pet via Active Semi-Supervised Learning

Wound management is a fundamental task in standard clinical practice. Automated solutions already exist for humans, but there is a lack of applications regarding wound management for pets. Precise and efficient wound assessment is helpful to improve diagnosis and to increase the effectiveness of treatment plans for chronic wounds. In this work, we introduced a novel pipeline for the segmentation of pet wound images. Starting from a model pre-trained on human-based wound images, we applied a combination of transfer learning (TL) and active semi-supervised learning (ASSL) to automatically label a large dataset. Additionally, we provided a guideline for future applications of TL+ASSL training strategy on image datasets. We compared the effectiveness of the proposed training strategy, monitoring the performance of an EfficientNet-b3 U-Net model against the lighter solution provided by a MobileNet-v2 U-Net model. We obtained 80% of correctly segmented images after five rounds of ASSL training. The EfficientNet-b3 U-Net model significantly outperformed the MobileNet-v2 one. We proved that the number of available samples is a key factor for the correct usage of ASSL training. The proposed approach is a viable solution to reduce the time required for the generation of a segmentation dataset.

Fully integrated point-of-care blood cell count using multi-frame morphology analysis

Point-of-care testing (POCT) of blood cell count (BCC) is an emerging approach that allows laypersons to identify and count whole blood cells through simple manipulation. To date, POCTs for BCC were mainly achieved by "stationary" images through blood smears or single-laity arranged cells in the microwell, making it difficult to obtain statistically sufficient numbers of cells. In this work, we present a fully integrated POCT device solely using "in-flow" imaging of 3 μL fingertip whole blood for improved identification and counting accuracy of BCC analysis. A miniaturized magnetic stirring module was integrated to maintain the temporal stability of cell concentration. A relatively high throughput (∼8000 cells/min) with a 30-fold dilution ratio of whole blood can be tested for as long as 1 h to examine sufficient numbers of cells, and the subclass cell concentration keeps constant. To improve the identification accuracy, multi-frame "in-flow" imaging was used to track the cell motion trails with multi-angle morphology analysis. This proof-of-concept was then validated with healthy whole blood samples and 75 cases of clinical patients with abnormal concentrations of red blood cells (RBCs), white blood cells (WBCs), and platelets (PLT). The average precision (AP) value of WBCs identification was improved from 0.8622 to 0.9934 using the multi-frame analysis method. And the high fitting degrees (>0.98) between our POCT device and the commercial clinical equipment indicated good agreement. This POCT device is user-friendly and cost-effective, making it a potential tool for diagnosing abnormal blood cell morphology or concentration in the field setting.

Inexpensive High-Throughput Multiplexed Biomarker Detection Using Enzymatic Metallization with Cellphone-Based Computer Vision

Multiplexed biomarker detection can play a critical role in reliable and comprehensive disease diagnosis and prediction of outcome. Enzyme-linked immunosorbent assay (ELISA) is the gold standard method for immunobinding-based biomarker detection. However, this is currently expensive, limited to centralized laboratories, and usually limited to the detection of a single biomarker at a time. We present a low-cost, smartphone-based portable biosensing platform for high-throughput, multiplexed, sensitive, and quantitative detection of biomarkers from single, low-volume drops (<1 μL) of clinical samples. Biomarker binding to spotted capture antigens is converted, via enzymatic metallization, to the localized surface deposition of amplified, dry-stable, silver metal spots whose darkness is proportional to biomarker concentration. A custom smartphone application is developed, which uses real-time computer vision to enable easy optical detection of the deposited metal spots and sensitive and reproducible quantification of the biomarkers. We demonstrate the use of this platform for high-throughput, multiplexed detection of multiple viral antigen-specific antibodies from convalescent COVID-19 patient serum as well as vaccine-elicited antibody responses from uninfected vaccine-recipient serum and show that distinct multiplexed antibody fingerprints are observed among them.

Smartphone-read phage lateral flow assay for point-of-care detection of infection

The COVID-19 pandemic has highlighted the urgent need for sensitive, affordable, and widely accessible testing at the point of care. Here we demonstrate a new, universal LFA platform technology using M13 phage conjugated with antibodies and HRP enzymes that offers high analytical sensitivity and excellent performance in a complex clinical matrix. We also report its complete integration into a sensitive chemiluminescence-based smartphone-readable lateral flow assay for the detection of SARS-CoV-2 nucleoprotein. We screened 84 anti-nucleoprotein monoclonal antibody pairs in phage LFA and identified an antibody pair that gave an LoD of 25 pg mL-1 nucleoprotein in nasal swab extract using a FluorChem gel documentation system and 100 pg mL-1 when the test was imaged and analyzed by an in-house-developed smartphone reader. The smartphone-read LFA signals for positive clinical samples tested (N = 15, with known Ct) were statistically different (p < 0.001) from signals for negative clinical samples (N = 11). The phage LFA technology combined with smartphone chemiluminescence imaging can enable the timely development of ultrasensitive, affordable point-of-care testing platforms for SARS-CoV-2 and beyond.

A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization

Diagnosis of soil-transmitted helminth (STH) and schistosome infections relies largely on conventional microscopy which has limited sensitivity, requires highly trained personnel and is error-prone. Rapid advances in miniaturization of optical systems, sensors and processors have enhanced research and development of digital and automated microscopes suitable for the detection of these diseases in resource-limited settings. While some studies have reported proof-of-principle results, others have evaluated the performance of working prototypes in field settings. The extensive commercialization of these innovative devices has, however, not yet been achieved. This review provides an overview of recent publications (2010–2022) on innovative field applicable optical devices which can be used for the diagnosis of STH and schistosome infections. Using an adapted technology readiness level (TRL) scale taking into account the WHO target product profile (TPP) for these diseases, the developmental stages of the devices were ranked to determine the readiness for practical applications in field settings. From the reviewed 18 articles, 19 innovative optical devices were identified and ranked. Almost all of the devices (85%) were ranked with a TRL score below 8 indicating that, most of the devices are not ready for commercialization and field use. The potential limitations of these innovative devices were discussed. We believe that the outcome of this review can guide the end-to-end development of automated digital microscopes aligned with the WHO TPP for the diagnosis of STH and schistosome infections in resource-limited settings.

Portable, Automated and Deep-Learning-Enabled Microscopy for Smartphone-Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review

Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone-based portable diagnostic devices are significantly efficient tools to user-friendly connect personalized health conditions and collect valuable optical information for rapid diagnosis and biomedical research through at-home screening. Deep learning algorithms for portable microscopes also help to enhance diagnostic accuracy by reducing the imaging resolution gap between benchtop and portable microscopes. This review highlighted recent progress and continued efforts in a smartphone-tethered optical platform through portable, automated, and deep-learning-enabled microscopy for personalized diagnostics and remote monitoring. In detail, the optical platforms through smartphone-based microscopes and lens-free holographic microscopy are introduced, and deep learning-based portable microscopic imaging is explained to improve the image resolution and accuracy of diagnostics. The challenges and prospects of portable optical systems with microfluidic channels and a compact microscope to screen COVID-19 in the current pandemic are also discussed. It has been believed that this review offers a novel guide for rapid diagnosis, biomedical imaging, and digital healthcare with low cost and portability.

Assessment of Immune Status Using Inexpensive Cytokines: A Literature Review and Learning Approaches

The emergence of point-of-care (POC) testing has lately been promoted to deliver rapid, reliable medical tests in critical life-threatening situations, especially in resource-limited settings. Recently, POC tests have witnessed further advances due to the technological revolution in smartphones. Smartphones are integrated as reliable readers to the POC results to improve their quantitative detection. This has enabled the use of more complex medical tests by the patient him/herself at home without the need for professional staff and sophisticated equipment. Cytokines, the important immune system biomarkers, are still measured today using the time-consuming Enzyme-Linked Immunosorbent Assay (ELISA), which can only be performed in specially equipped laboratories. Therefore, in this study, we investigate the current development of POC technologies suitable for the home testing of cytokines by conducting a PRISMA literature review. Then, we classify the collected technologies as inexpensive and expensive depending on whether the cytokines can be measured easily at home or not. Additionally, we propose a machine learning-based solution to even increase the efficiency of the cytokine measurement by leveraging the cytokines that can be inexpensively measured to predict the values of the expensive ones. In total, we identify 12 POCs for cytokine quantification. We find that Interleukin 1β (IL-1β), Interleukin 3 (IL-3), Interleukin 6 (IL-6), Interleukin 8 (IL-8) and Tumor necrosis factor (TNF) can be measured with inexpensive POC technology, namely at home. We build machine-learning models to predict the values of other expensive cytokines such as Interferon-gamma (IFN-γ), IL-10, IL-2, IL-17A, IL-17F, IL-4 and IL-5 by relying on the identified inexpensive ones in addition to the age of the individual. We evaluate to what extent the built machine learning models can use the inexpensive cytokines to predict the expensive ones on 351 healthy subjects from the public dataset 10k Immunomes. The models for IFN-γ show high results for the coefficient of determination: R2 = 0.743. The results for IL-5 and IL-4 are also promising, whereas the predictive model of IL-10 achieves only R2 = 0.126. Lastly, the results demonstrate the vital role of TNF and IL-6 in the immune system due to its high importance in the predictions of all the other expensive cytokines.

Point of care diagnosis of dry eye disease with a sensitive immunoassay for dual biomarker detection

Dry eye disease (DED) is a multifactorial eye disease with few effective methods for clinical diagnosis and treatment. It is the most common eye disease with significant health challenges of the unprecedented aging population. Recent proteomic studies and clinical research have led to the discovery of several biologically relevant biomarkers, with increased levels of Interleukin-6 (IL-6) and decreased levels of lactoferrin being clinically validated in the progression of DED. In this study, a sensitive point of care (POC) DED diagnostic method was developed for targeting dual biomarkers of IL-6 and lactoferrin in the tear samples. A paper-based lateral flow immunoassay (LFIA) was established in a double-antibody sandwich fashion with colloid gold nanoparticles acting as probes. The minimal detection concentrations were 0.1 ng/ml and 10 ng/ml for IL-6 and lactoferrin, respectively. Separated conventional ELISA tests were also performed with data confirming results from the LFIA tests. A trial study was conducted with 20 tear samples from DED patients and healthy controls. All DED tear samples exhibited significantly higher levels of IL-6 and decreased levels of lactoferrin, as compared to the normal controls. A quantitative analysis of LFIA images was carried out using ImageJ software for an accurate data interpretation. This dual biomarker detection method is sensitive and affordable with quick turnaround time. Design of a larger clinical study in the future can further validate this POC assay for early diagnosis as well as patients’ self-management of chronic states of DED.

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A point of care assay was established for in-home diagnosis of dry eye disease (DED).

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Two validated biomarkers were targeted to address the multifactorial nature of DED.

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The paper based lateral flow assays were validated by the conventional ELISA assays.

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Initial clinical trial tests were performed with 20 tear samples.

Flash Characterization of Smartphones Used in Point-of-Care Diagnostics

Rapidly growing interest in smartphone cameras as the basis of point-of-need diagnostic and bioanalytical technologies increases the importance of quantitative characterization of phone optical performance under real-world operating conditions. In the context of our development of lateral-flow immunoassays based on phosphorescent nanoparticles, we have developed a suite of tools for characterizing the temporal and spectral profiles of smartphone torch and flash emissions, and their dependence on phone power state. In this work, these tools are described and documented to make them easily available to others, and demonstrated by application to characterization of Apple iPhone 5s, iPhone 6s, iPhone 8, iPhone XR, and Samsung Note8 flash performance as a function of time and wavelength, at a variety of power settings. Flash and torch intensity and duration vary with phone state and among phone models. Flash has high variability when the battery charge is below 10%, thus, smartphone-based Point-of-Care (POC) tests should only be performed at a battery level of at least 15%. Some output variations could substantially affect the results of assays that rely on the smartphone flash.

Engineering a sustainable future for point-of-care diagnostics and single-use microfluidic devices

Single-use, disposable, point-of-care diagnostic devices carry great promise for global health, including meeting urgent needs for testing and diagnosis in places with limited laboratory facilities. Unfortunately, the production and disposal of single-use devices, whether in lateral flow assay, cartridges, cassettes, or lab-on-chip microfluidic format, also poses significant challenges for environmental and human health. Point-of-care devices are commonly manufactured from unsustainable polymeric materials derived from fossil sources. Their disposal often necessitates incineration to reduce infection risk, thereby creating additional release of CO2. Many devices also contain toxic chemicals, such as cyanide derivatives, that are damaging to environmental and human health if not disposed of safely. Yet, in the absence of government regulatory frameworks, safe and sustainable waste management for these novel medical devices is often left unaddressed. There is an urgent need to find novel solutions to avert environmental and human harm from these devices, especially in low- and middle-income countries where waste management infrastructure is often weak and where the use of point-of-care tests is projected to rise in coming years. We review here common materials used in the manufacture of single-use point-of-care diagnostic tests, examine the risks they pose to environmental and human health, and investigate replacement materials that can potentially reduce the impact of microfluidic devices on the production of harmful waste. We propose solutions available to point-of-care test developers to start embedding sustainability at an early stage in their design, and to reduce their non-renewable plastic consumption in research and product development.

Smartphone based aptasensors as intelligent biodevice for food contamination detection in food and soil samples: Recent advances

Nowadays, the integration of conventional analytical approaches with smartphones has been developed novel, emerging and affordable devices for improving on-site detection platforms in the fields of food safety. Smartphone-based aptasensors as the next generation of portable aptasensing technique has attracted considerable attention as it offers a semi-automated user interface that can be exploited by inexpert characters. Wireless data transferability is an undeniable advantage that home-testing platforms have as well as it can suggest high computational power. In addition, these types of biodevices can provide real-time monitoring in terms of exchanging digital networks in real-time. To elaborate, the ability of smartphones to connect through the Internet is one of the most critical advantages of smartphone-based aptasensor that can be uploaded to Cloud databases and results can be disseminated as spatio-temporal maps across the globe. This review focused on the recent progress and technical breakthroughs of aptasensor on the smartphone as a groundbreaking enterprise in the field of biochemical analysis, importantly in the aspect of the combination of different types of biosensors including electrochemical, optical and colorimetric. In our opinion, this review can broaden our understanding of using smartphones as a portable sensing approach by addressing the current challenges and future perspectives.

Smartphone-Based Multiplexed Biosensing Tools for Health Monitoring

Many emerging technologies have the potential to improve health care by providing more personalized approaches or early diagnostic methods. In this review, we cover smartphone-based multiplexed sensors as affordable and portable sensing platforms for point-of-care devices. Multiplexing has been gaining attention recently for clinical diagnosis considering certain diseases require analysis of complex biological networks instead of single-marker analysis. Smartphones offer tremendous possibilities for on-site detection analysis due to their portability, high accessibility, fast sample processing, and robust imaging capabilities. Straightforward digital analysis and convenient user interfaces support networked health care systems and individualized health monitoring. Detailed biomarker profiling provides fast and accurate analysis for disease diagnosis for limited sample volume collection. Here, multiplexed smartphone-based assays with optical and electrochemical components are covered. Possible wireless or wired communication actuators and portable and wearable sensing integration for various sensing applications are discussed. The crucial features and the weaknesses of these devices are critically evaluated.

Bluetooth-Connected Pocket Spectrometer and Chemometrics for Olive Oil Applications

Unsaturated fatty acids are renowned for their beneficial effects on the cardiovascular system. The high content of unsaturated fatty acids is a benefit of vegetable fats and an important nutraceutical indicator. The ability to quickly check fat composition of an edible oil could be advantageous for both consumers and retailers. A Bluetooth-connected pocket spectrometer operating in NIR band was used for analyzing olive oils of different qualities. Reference data for fatty acid composition were obtained from a certified analytical laboratory. Chemometrics was used for processing data, and predictive models were created for determining saturated and unsaturated fatty acid content. The NIR spectrum also demonstrated good capability in classifying extra virgin and non-extra virgin olive oils. The pocket spectrometer used in this study has a relatively low cost, which makes it affordable for a wide class of users. Therefore, it may open the opportunity for quick and non-destructive testing of edible oil, which can be of interest for consumer, retailers, and for small/medium-size producers, which lack easy access to conventional analytics.

Cost-Effective Fiber Optic Solutions for Biosensing

In the last years, optical fiber sensors have proven to be a reliable and versatile biosensing tool. Optical fiber biosensors (OFBs) are analytical devices that use optical fibers as transducers, with the advantages of being easily coated and biofunctionalized, allowing the monitorization of all functionalization and detection in real-time, as well as being small in size and geometrically flexible, thus allowing device miniaturization and portability for point-of-care (POC) testing. Knowing the potential of such biosensing tools, this paper reviews the reported OFBs which are, at the moment, the most cost-effective. Different fiber configurations are highlighted, namely, end-face reflected, unclad, D- and U-shaped, tips, ball resonators, tapered, light-diffusing, and specialty fibers. Packaging techniques to enhance OFBs' application in the medical field, namely for implementing in subcutaneous, percutaneous, and endoscopic operations as well as in wearable structures, are presented and discussed. Interrogation approaches of OFBs using smartphones' hardware are a great way to obtain cost-effective sensing approaches. In this review paper, different architectures of such interrogation methods and their respective applications are presented. Finally, the application of OFBs in monitoring three crucial fields of human life and wellbeing are reported: detection of cancer biomarkers, detection of cardiovascular biomarkers, and environmental monitoring.

Tuberculosis Phenotypic and Genotypic Drug Susceptibility Testing and Immunodiagnostics: A Review

Tuberculosis (TB), considered an ancient disease, is still killing one person every 21 seconds. Diagnosis of Mycobacterium tuberculosis (M.tb) still has many challenges, especially in low and middle-income countries with high burden disease rates. Over the last two decades, the amount of drug-resistant (DR)-TB cases has been increasing, from mono-resistant (mainly for isoniazid or rifampicin resistance) to extremely drug resistant TB. DR-TB is problematic to diagnose and treat, and thus, needs more resources to manage it. Together with+ TB clinical symptoms, phenotypic and genotypic diagnosis of TB includes a series of tests that can be used on different specimens to determine if a person has TB, as well as if the M.tb strain+ causing the disease is drug susceptible or resistant. Here, we review and discuss advantages and disadvantages of phenotypic vs. genotypic drug susceptibility testing for DR-TB, advances in TB immunodiagnostics, and propose a call to improve deployable and low-cost TB diagnostic tests to control the DR-TB burden, especially in light of the increase of the global burden of bacterial antimicrobial resistance, and the potentially long term impact of the coronavirus disease 2019 (COVID-19) disruption on TB programs.

Technologies for Frugal and Sensitive Point-of-Care Immunoassays

Immunoassays are a powerful tool for sensitive and quantitative analysis of a wide range of biomolecular analytes in the clinic and in research laboratories. However, enzyme-linked immunosorbent assay (ELISA)-the gold-standard assay-requires significant user intervention, time, and clinical resources, making its deployment at the point-of-care (POC) impractical. Researchers have made great strides toward democratizing access to clinical quality immunoassays at the POC and at an affordable price. In this review, we first summarize the commercially available options that offer high performance, albeit at high cost. Next, we describe strategies for the development of frugal POC assays that repurpose consumer electronics and smartphones for the quantitative detection of analytes. Finally, we discuss innovative assay formats that enable highly sensitive analysis in the field with simple instrumentation.

PD-LAMP smartphone detection of SARS-CoV-2 on chip

In 2019 the COVID-19 pandemic, caused by SARS-CoV-2, demonstrated the urgent need for rapid, reliable, and portable diagnostics. The COVID-19 pandemic was declared in January 2020 and surges of the outbreak continue to reoccur. It is clear that early identification of infected individuals, especially asymptomatic carriers, plays a huge role in preventing the spread of the disease. The current gold standard diagnostic for SARS-CoV-2 is quantitative reverse transcription polymerase chain reaction (qRT-PCR) test based on the detection of the viral RNA. While RT-PCR is reliable and sensitive, it requires expensive centralized equipment and is time consuming (∼2 h or more); limiting its applicability in low resource areas. The FDA issued Emergency Use Authorizations (EUAs) for several COVID-19 diagnostics with an emphasis on point-of care (PoC) testing. Numerous RT-PCR and serological tests were approved for use at the point of care. Abbott's ID NOW, and Cue Health's COVID-19 test are of particular interest, which use isothermal amplification methods for rapid detection in under 20 min. We look to expand on the range of current PoC testing platforms with a new rapid and portable isothermal nucleic acid detection device. We pair reverse transcription loop mediated isothermal amplification (RT-LAMP) with a particle imaging technique, particle diffusometry (PD), to successfully detect SARS-CoV-2 in only 35 min on a portable chip with integrated heating. A smartphone device is used to image the samples containing fluorescent beads post-RT-LAMP and correlates decreased diffusivity to positive samples. We detect as little as 30 virus particles per μL from a RT-LAMP reaction in a microfluidic chip using a portable heating unit. Further, we can perform RT-LAMP from a diluted unprocessed saliva sample without RNA extraction. Additionally, we lyophilize SARS-CoV-2-specific RT-LAMP reactions that target both the N gene and the ORF1ab gene in the microfluidic chip, eliminating the need for cold storage. Our assay meets specific target product profiles outlined by the World Health Organization: it is specific to SARS-CoV-2, does not require cold storage, is compatible with digital connectivity, and has a detection limit of less than 35 × 10⁴ viral particles per mL in saliva. PD-LAMP is rapid, simple, and attractive for screening and use at the point of care.

Automatic skin disease diagnosis using deep learning from clinical image and patient information

Background

Skin diseases are the fourth most common cause of human illness which results in enormous non‐fatal burden in daily life activities. They are caused by chemical, physical and biological factors. Visual assessment in combination with clinical information is the common diagnostic procedure for diseases. However, these procedures are manual, time‐consuming, and require experience and excellent visual perception.

Objectives

In this study, an automated system is proposed for the diagnosis of five common skin diseases by using data from clinical images and patient information using deep learning pre‐trained mobilenet‐v2 model.

Methods

Clinical images were acquired using different smartphone cameras and patient's information were collected during patient registration. Different data preprocessing and augmentation techniques were applied to boost the performance of the model prior to training.

Results

A multiclass classification accuracy of 97.5%, sensitivity of 97.7% and precision of 97.7% has been achieved using the proposed technique for the common five skin disease. The results demonstrate that, the developed system provides excellent diagnosis performance for the five skin diseases.

Conclusion

The system has been designed as a smartphone application and it has the potential to be used as a decision support system in low resource settings, where both the expert dermatologist and the means are limited.

Extracellular vesicles as a source of prostate cancer biomarkers in liquid biopsies: a decade of research

Prostate cancer is a global cancer burden and considerable effort has been made through the years to identify biomarkers for the disease. Approximately a decade ago, the potential of analysing extracellular vesicles in liquid biopsies started to be envisaged. This was the beginning of a new exciting area of research investigating the rich molecular treasure found in extracellular vesicles to identify biomarkers for a variety of diseases. Vesicles released from prostate cancer cells and cells of the tumour microenvironment carry molecular information about the disease that can be analysed in several biological fluids. Numerous studies document the interest of researchers in this field of research. However, methodological issues such as the isolation of vesicles have been challenging. Remarkably, novel technologies, including those based on nanotechnology, show promise for the further development and clinical use of extracellular vesicles as liquid biomarkers. Development of biomarkers is a long and complicated process, and there are still not many biomarkers based on extracellular vesicles in clinical use. However, the knowledge acquired during the last decade constitutes a solid basis for the future development of liquid biopsy tests for prostate cancer. These are urgently needed to bring prostate cancer treatment to the next level in precision medicine.

Comprehensive review of conventional and state-of-the-art detection methods of Cryptosporidium

Cryptosporidium is a critical waterborne protozoan pathogen found in water resources that have been a major cause of death and serious illnesses worldwide, costing millions of dollars annually for its detection and treatment. Over the past several decades, substantial efforts have been made towards developing techniques for the detection of Cryptosporidium. Early diagnostic techniques were established based on the existing tools in laboratories, such as microscopes. Advancements in fluorescence microscopy, immunological, and molecular techniques have led to the development of several kits for the detection of Cryptosporidium spp. However, these methods have several limitations, such as long processing times, large sample volumes, the requirement for bulky and expensive laboratory tools, and the high cost of reagents. There is an urgent need to improve these existing techniques and develop low-cost, portable and rapid detection tools for applications in the water quality industry. In this review, we compare recent advances in nanotechnology, biosensing and microfluidics that have facilitated the development of sophisticated tools for the detection of Cryptosporidium spp.Finally, we highlight the advantages and disadvantages, of these state-of-the-art detection methods compared to current analytical methodologies and discuss the need for future developments to improve such methods for detecting Cryptosporidium in the water supply chain to enable real-time and on-site monitoring in water resources and remote areas.

Lab-on-a-Chip Devices for Point-of-Care Medical Diagnostics

The recent coronavirus (COVID-19) pandemic has underscored the need to move from traditional lab-centralized diagnostics to point-of-care (PoC) settings. Lab-on-a-chip (LoC) platforms facilitate the translation to PoC settings via the miniaturization, portability, integration, and automation of multiple assay functions onto a single chip. For this purpose, paper-based assays and microfluidic platforms are currently being extensively studied, and much focus is being directed towards simplifying their design while simultaneously improving multiplexing and automation capabilities. Signal amplification strategies are being applied to improve the performance of assays with respect to both sensitivity and selectivity, while smartphones are being integrated to expand the analytical power of the technology and promote its accessibility. In this chapter, we review the main technologies in the field of LoC platforms for PoC medical diagnostics and survey recent approaches for improving these assays.

Recent advances in biological detection with rolling circle amplification: design strategy, biosensing mechanism, and practical applications

Rolling circle amplification (RCA) is a simple and isothermal DNA amplification technique that is used to generate thousands of repeating DNA sequences using circular templates under the catalysis of DNA polymerase.

Requirements and study designs for US regulatory approval of influenza home tests

Home testing for infectious disease has come to the forefront during the COVID-19 pandemic. There is now considerable commercial interest in developing complete home tests for a variety of viral and bacterial pathogens. However, the regulatory science around home infectious disease test approval, and procedures test manufacturers and laboratory professionals will need to follow, have not yet been formalized by US FDA, with the exception of EUA guidance for COVID-19 tests. We describe the state of home-based testing for influenza with a focus on sample-to-result home tests, discuss the various regulatory pathways by which these products can reach populations, and provide recommendations for study designs, patient samples, and other important features necessary to gain market access. These recommendations have potential application for home use tests being developed for other viral respiratory infections, such as COVID-19, as guidance moves from EUA designation into 510(k) requirements.

A Smartphone Optical Device for Point-of-Care Testing of Glucose and Cholesterol Using Ag NPs/UiO-66-NH2-Based Ratiometric Fluorescent Probe

Point-of-care testing (POCT) with the advantages of simplicity, rapidity, portability, and low-cost is of great importance to improve healthcare, especially in resource-limited settings and home healthcare settings. Moreover, it is a great challenge to quantitative POCT of multiplexed biomarkers within a single accessible assay but provides enhanced diagnostic accuracy and improved diagnostic efficiency. Herein, a smartphone optical device has been designed for POCT of glucose and cholesterol in metabolic syndrome patients using a ratiometric fluorescent sensor. The sensing system of Ag NPs/UiO-66-NH₂ and o-phenylenediamine presents a dual-emission response to H₂O₂ (the main product of glucose and cholesterol catalyzed by glucose oxidase and cholesterol oxidase) on account of the inner filter effect, resulting in an increase in the response of the fluorescence intensity ratio (F_555 nm/F_425 nm) accompanied by a distinguishable color transition from blue to yellow green. After compositing probes with a flexible substrate, the obtained test strip can be integrated with a smartphone-based portable platform to read RGB values for accurate testing of glucose and cholesterol with both detection limits of 10 μmol L^-1, which are hundreds of times lower than their concentrations in human serum. With the advantages of low-cost, ease of operation, and broad adaptability, this smartphone optical device holds great potential for portable detection of numerous targets in personalized healthcare and clinical diagnosis.

Willingness of Chinese Men Who Have Sex With Men to Use Smartphone-Based Electronic Readers for HIV Self-testing: Web-Based Cross-sectional Study

BACKGROUND

The need for strategies to encourage user-initiated reporting of results after HIV self-testing (HIVST) persists. Smartphone-based electronic readers (SERs) have been shown capable of reading diagnostics results accurately in point-of-care diagnostics and could bridge the current gaps between HIVST and linkage to care.

OBJECTIVE

Our study aimed to assess the willingness of Chinese men who have sex with men (MSM) in the Jiangsu province to use an SER for HIVST through a web-based cross-sectional study.

METHODS

From February to April 2020, we conducted a convenience web-based survey among Chinese MSM by using a pretested structured questionnaire. Survey items were adapted from previous HIVST feasibility studies and modified as required. Prior to answering reader-related questions, participants watched a video showcasing a prototype SER. Statistical analysis included descriptive analysis, chi-squared test, and multivariable logistic regression. P values less than .05 were deemed statistically significant.

RESULTS

Of 692 participants, 369 (53.3%) were aged 26-40 years, 456 (65.9%) had ever self-tested for HIV, and 493 (71.2%) were willing to use an SER for HIVST. Approximately 98% (483/493) of the willing participants, 85.3% (459/538) of ever self-tested and never self-tested, and 40% (46/115) of unwilling participants reported that SERs would increase their HIVST frequency. Engaging in unprotected anal intercourse with regular partners compared to consistently using condoms (adjusted odds ratio [AOR] 3.04, 95% CI 1.19-7.74) increased the odds of willingness to use an SER for HIVST. Participants who had ever considered HIVST at home with a partner right before sex compared to those who had not (AOR 2.99, 95% CI 1.13-7.90) were also more willing to use an SER for HIVST. Playing receptive roles during anal intercourse compared to playing insertive roles (AOR 0.05, 95% CI 0.02-0.14) was associated with decreased odds of being willing to use an SER for HIVST. The majority of the participants (447/608, 73.5%) preferred to purchase readers from local Centers of Disease Control and Prevention offices and 51.2% (311/608) of the participants were willing to pay less than US $4.70 for a reader device.

CONCLUSIONS

The majority of the Chinese MSM, especially those with high sexual risk behaviors, were willing to use an SER for HIVST. Many MSM were also willing to self-test more frequently for HIV with an SER. Further research is needed to ascertain the diagnostic and real-time data-capturing capacity of prototype SERs during HIVST.

Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study

Background:

Maternal serum alpha-fetoprotein (MSAFP) concentration typically increases during pregnancy and is routinely measured during the second trimester as a part of screening for fetal neural tube defects and Down syndrome. However, most pregnancy screening tests are not available in the settings they are needed the most. A mobile device–enabled technology based on MSAFP for screening birth defects could enable the rapid screening and triage of high-risk pregnancies, especially where maternal serum screening and fetal ultrasound scan facilities are not easily accessible. Shifting the approach from clinic- and laboratory-dependent care to a mobile platform based on our point-of-care approach will enable translation to resource-limited settings and the global health care market.

Objective:

The objective of this study is to develop and perform proof-of-concept testing of a lateral flow immunoassay on a mobile platform for rapid, point-of-care quantification of serum alpha-fetoprotein (AFP) levels, from a drop of human serum, within a few minutes.

Methods:

The development of the immunoassay involved the selection of commercially available antibodies and optimization of their concentrations by an iterative method to achieve the required detection limits. We compared the performance of our method with that of commercially obtained human serum samples, with known AFP concentrations quantified by the Abbott ARCHITECT chemiluminescent magnetic microparticle immunoassay (CMIA).

Results:

We tested commercially obtained serum samples (N=20) with concentrations ranging from 2.2 to 446 ng/mL to compare the results of our point-of-care assay with results from the Abbott ARCHITECT CMIA. A correlation of 0.98 (P<.001) was observed on preliminary testing and comparison with the CMIA. The detection range of our point-of-care assay covers the range of maternal serum AFP levels observed during pregnancy.

Conclusions:

The preliminary test results from the AFP test on the mobile platform performed in this study represent a proof of concept that will pave the way for our future work focused on developing a mobile device–enabled quad-screen point-of-care testing with the potential to enable the screening of high-risk pregnancies in various settings. The AFP test on the mobile platform can be applied to enable screening for high-risk pregnancies, within a few minutes, at the point of care even in remote areas where maternal serum tests and fetal ultrasound scans are not easily accessible; assessment of whether clinical follow-up and diagnostic testing may be needed after a positive initial screening evaluation; and development of surveillance tools for birth defects.

A plug, print & play inkjet printing and impedance-based biosensing technology operating through a smartphone for clinical diagnostics

Simplicity is one of the key feature for the spread of any successful technological product. Here, a method for rapid and low-cost fabrication of electrochemical biosensors is presented. This "plug, print & play" method involves inkjet-printing even in an office-like environment, without the need of highly specialized expertise or equipment, guaranteeing an ultra-fast idea to (scaled) prototype production time. The printed biosensors can be connected to a smartphone through its audio input for their impedance readout, demonstrating the validity of the system for point-of-care biosensing. Proper electrodes layout guarantees high sensitivity and is validated by finite element simulations. The introduction of a passivation method (wax printing) allowed to complete the devices fabrication process, increasing their sensitivity. Indeed, the wax allowed reducing the interference related to the parasitic currents flowing through the permeable coating of the employed substrates, which was used for the chemical sintering, thus avoiding the common thermal treatment after printing. As a case study, we used the devices to develop an electrochemical aptamer-based sensor for the rapid detection of neutrophil gelatinase-associated lipocalin (NGAL) in urine - a clinically important marker of acute kidney injury. The aptasensor platform is capable of detecting clinically relevant concentrations of NGAL with a simple and rapid smartphone readout. The developed technology may be extended in the future to continuous monitoring, taking advantage of its flexibility to integrate it in tubes, or to other diagnostic applications where cost/efficiency and rapidity of the research, development and implementation of point of care devices is a must.

Performance of the point-of-care circulating cathodic antigen test in the diagnosis of schistosomiasis japonica in a human cohort from Northern Samar, the Philippines

BACKGROUND

Zoonotic schistosomiasis, caused by Schistosoma japonicum, remains a major public health problem in the Philippines. This study aimed to evaluate the commercially available rapid diagnostic point-of-care circulating cathodic antigen (POC-CCA) test in detecting individuals infected with S. japonicum in a human cohort from an endemic area for schistosomiasis japonica in the Philippines.

METHODS

Clinical samples were collectedin 18 barangays endemic for S. japonicum infection in Laoang and Palapag municipalities, Northern Samar, the Philippines, in 2015. The presence of CCA in filter-concentrated urine samples (n = 412) was evaluated using the commercial kits and the results were converted to images, which were further analyzed by ImageJ software to calculate R values. The diagnostic performance of the immunochromatographic POC-CCA test was compared using the Kato-Katz (KK) procedure, in-house enzyme-linked immunosorbent assays (ELISAs) and droplet digital (dd) PCR assays as reference.

RESULTS

The POC-CCA test was able to detect S. japonicum-infected individuals in the cohort with an eggs per gram of faeces (EPG) more than or equal to 10 with sensitivity/specificity values of 63.3%/93.3%. However, the assay showed an inability to diagnose schistosomiasis japonica infections in all cohort KK-positive individuals, of which the majority had an extremely low egg burden (EPG: 1-9). The prevalence of S. japonicum infection in the total cohort determined by the POC-CCA test was 12.4%, only half of that determined by the KK method (26.2%). When compared with the ELISAs and ddPCR assays as a reference, the POC-CCA assay was further shown to be a test with low sensitivity. Nevertheless, the assay exhibited significant positive correlations with egg burden determined by the KK technique and the target gene copy number index values determined by the ddPCR assays within the entire cohort.

CONCLUSIONS

By using in silico image analysis, the POC-CCA cassette test could be converted to a quantitative assay to avoid reader-variability. Because of its low sensitivity, the commercially available POC-CCA assay had limited potential for determining the status of a S. japonicum infection in the target cohort. The assay should be applied with caution in populations where schistosome parasites (especially S. japonicum) are present at low infection intensity.

Identifying Enablers of Participant Engagement in Clinical Trials of Consumer Health Technologies: Qualitative Study of Influenza Home Testing

Background

A rise in the recent trend of self-managing health using consumer health technologies highlights the importance of efficient and successful consumer health technology trials. Trials are particularly essential to support large-scale implementations of consumer health technologies, such as smartphone-supported home tests. However, trials are generally fraught with challenges, such as inadequate enrollment, lack of fidelity to interventions, and high dropout rates. Understanding the reasons underlying individuals’ participation in trials can inform the design and execution of future trials of smartphone-supported home tests.

Objective

This study aims to identify the enablers of potential participants’ trial engagement for clinical trials of smartphone-supported home tests. We use influenza home testing as our instantiation of a consumer health technology subject to trial to investigate the dispositional and situational enablers that influenced trial engagement.

Methods

We conducted semistructured interviews with 31 trial participants using purposive sampling to facilitate demographic diversity. The interviews included a discussion of participants’ personal characteristics and external factors that enabled their trial engagement with a smartphone-supported home test for influenza. We performed both deductive and inductive thematic analyses to analyze the interview transcripts and identify enabler themes.

Results

Our thematic analyses revealed a structure of dispositional and situational enablers that enhanced trial engagement. Situationally, clinical affiliation, personal advice, promotional recruitment strategies, financial incentives, and insurance status influenced trial engagement. In addition, digital health literacy, motivation to advance medical research, personal innovativeness, altruism, curiosity, positive attitude, and potential to minimize doctors’ visits were identified as the dispositional enablers for trial engagement in our study.

Conclusions

We organized the identified themes for dispositional and situational enablers of trial engagement with a smartphone-supported home test into a research framework that can guide future research as well as the trial design and execution of smartphone-supported home tests. We suggest several trial design and engagement strategies to enhance the financial and scientific viability of these trials that pave the way for advancements in patient care. Furthermore, our study also offers practical strategies to trial organizers to enhance participants’ enrollment and engagement in clinical trials of these home tests.