A smartphone-based biomedical sensory system

On the Possibility of Fluorescent Capture Immunoassays on a Contact Lens

Blood samples and testing are routine in healthcare. Presently, there is a growing interest in using tear samples in place of blood. Tear samples can be obtained non-invasively and collection does not require the skills of a trained phlebotomist. Red blood cells and other cells are not present in tears, which avoids centrifugation. Importantly, basal tear samples contain most of the biomarkers present in blood. The difficulty is the small volume of basal tears, which is about 7 μL in each eye. Any contact with the eye results in additional reflex tears with a different chemical composition. The small tear samples are collected with capillary tubes and then sent out for amplified assays, such as enzyme-linked immunosorbent assay (ELISA) or polymerase chain reaction (PCR). The results are not available for several days or a week and, therefore, are less useful in an ophthalmology office. We propose the use of a contact lens that contains bound antibodies for fluorescence immunoassays. The lenses could be removed from the patient for point-of-care measurements at the bedside. To prove that this concept is possible, we performed a three-layer protein capture assay that mimics an immunoassay. For convenience, we used lysozyme (Lys), which spontaneously coats silicon hydrogel (SiHG) contact lenses (CL). Anti-lysozyme IgG was the second layer captured, with anti-lysozyme considered to be the target biomarker. The third layer was rhodamine or Alexa Fluor-labeled Ab against the IgG Fc region, considered to be the detection antibody. The multiple protein layers were stable and did not wash off the SiHG lenses. These results strongly suggest the contact lens can be used for capture immunoassays for a wide variety of biomarkers.

Colorimetric aptasensor coupled with a deep-learning-powered smartphone app for programmed death ligand-1 expressing extracellular vesicles

Lung cancer is a devastating public health threat and a leading cause of cancer-related deaths. Therefore, it is imperative to develop sophisticated techniques for the non-invasive detection of lung cancer. Extracellular vesicles expressing programmed death ligand-1 (PD-L1) markers (PD-L1@EVs) in the blood are reported to be indicative of lung cancer and response to immunotherapy. Our approach is the development of a colorimetric aptasensor by combining the rapid capturing efficiency of (Fe3O4)-SiO2-TiO2 for EV isolation with PD-L1 aptamer-triggered enzyme-linked hybridization chain reaction (HCR) for signal amplification. The numerous HRPs catalyze their substrate dopamine (colorless) into polydopamine (blackish brown). Change in chromaticity directly correlates with the concentration of PD-L1@EVs in the sample. The colorimetric aptasensor was able to detect PD-L1@EVs at concentrations as low as 3.6×102 EVs/mL with a wide linear range from 103 to 1010 EVs/mL with high specificity and successfully detected lung cancer patients' serum from healthy volunteers' serum. To transform the qualitative colorimetric approach into a quantitative operation, we developed an intelligent convolutional neural network (CNN)-powered quantitative analyzer for chromaticity in the form of a smartphone app named ExoP, thereby achieving the intelligent analysis of chromaticity with minimal user intervention or additional hardware attachments for the sensitive and specific quantification of PD-L1@EVs. This combined approach offers a simple, sensitive, and specific tool for lung cancer detection using PD-L1@EVs. The addition of a CNN-powered smartphone app further eliminates the need for specialized equipment, making the colorimetric aptasensor more accessible for low-resource settings.

Advances in Portable Optical Microscopy Using Cloud Technologies and Artificial Intelligence for Medical Applications

The need for faster and more accessible alternatives to laboratory microscopy is driving many innovations throughout the image and data acquisition chain in the biomedical field. Benchtop microscopes are bulky, lack communications capabilities, and require trained personnel for analysis. New technologies, such as compact 3D-printed devices integrated with the Internet of Things (IoT) for data sharing and cloud computing, as well as automated image processing using deep learning algorithms, can address these limitations and enhance the conventional imaging workflow. This review reports on recent advancements in microscope miniaturization, with a focus on emerging technologies such as photoacoustic microscopy and more established approaches like smartphone-based microscopy. The potential applications of IoT in microscopy are examined in detail. Furthermore, this review discusses the evolution of image processing in microscopy, transitioning from traditional to deep learning methods that facilitate image enhancement and data interpretation. Despite numerous advancements in the field, there is a noticeable lack of studies that holistically address the entire microscopy acquisition chain. This review aims to highlight the potential of IoT and artificial intelligence (AI) in combination with portable microscopy, emphasizing the importance of a comprehensive approach to the microscopy acquisition chain, from portability to image analysis.

A Smartphone-Based Sensing for Portable and Sensitive Visual Detection of Hg (II) via Nitrogen Doped Carbon Quantum Dots Modified Paper Strip

The development of portable and cost-effective sensing system for Hg2+ quantitation is highly demanded for environmental monitoring. Herein, an on-site, rapid and portable smartphone readout device based Hg2+ sensing system integrating nitrogen-doped carbon quantum dots (NCDs) modified paper strip was proposed, and the physicochemical properties of NCDs were characterized by high resolution TEM, FTIR, UV-vis absorption spectrum and fluorescence spectral analysis. The modified paper strip was prepared via "ink-jet" printing technology and exhibits sensitive fluorescence response to Hg2+ with fluorescence color of bright blue (at the excitation/emission wavelength of 365/440 nm). This portable smartphone-based sensing platform is highly selective and sensitive to Hg2+ with the limit of detection (LOD) of 10.6 nM and the concentration range of 0-130 nM. In addition, the recoveries of tap water and local lake water were in the range of 89.4% to 109%. The cost-effective sensing system based on smartphone shows a great potential for trace amounts of Hg2+ monitoring in environmental water samples.

Current trends in digital camera-based bioassays for point-of-care tests

Point-of-care and bedside tests are analytical devices suitable for a growing role in the current healthcare system and provide the opportunity to achieve an exact diagnosis by an untrained person and in various conditions and sites where it is necessary. Using a digital camera integrated into a well-accessible device like a smartphone brings a new way in which a colorimetric point-of-care diagnostic test can provide unbiased data. This review summarizes basic facts about the colorimetric point-of-care tests, principles of how to use a portable device with a camera in the assay, applications of digital cameras for the current tests, and new devices described in the recent papers. An overview of the recent literature and a discussion of recent developments and future trends are provided.

Gradient Guided-Mode Resonance Biosensor with Smartphone Readout

Integrating biosensors with smartphones is becoming an increasingly popular method for detecting various biomolecules and could replace expensive laboratory-based instruments. In this work, we demonstrate a novel smartphone-based biosensor system with a gradient grating period guided-mode resonance (GGP-GMR) sensor. The sensor comprises numerous gratings which each correspond to and block the light of a specific resonant wavelength. This results in a dark band, which is observed using a CCD underneath the GGP-GMR sensor. By monitoring the shift in the dark band, the concentration of a molecule in a sample can be determined. The sensor is illuminated by a light-emitting diode, and the light transmitted through the GGP-GMR sensor is directly captured by a smartphone, which then displays the results. Experiments were performed to validate the proposed smartphone biosensor and a limit of detection (LOD) of 1.50 × 10-3 RIU was achieved for sucrose solutions. Additionally, multiplexed detection was demonstrated for albumin and creatinine solutions at concentrations of 0-500 and 0-1 mg/mL, respectively; the corresponding LODs were 1.18 and 20.56 μg/mL.

Cell phone microscopy enabled low-cost manufacturable colorimetric urine glucose test

Glucose serves as a pivotal biomarker crucial for the monitoring and diagnosis of a spectrum of medical conditions, encompassing hypoglycemia, hyperglycemia, and diabetes, all of which may precipitate severe clinical manifestations in individuals. As a result, there is a growing demand within the medical domain for the development of rapid, cost-effective, and user-friendly diagnostic tools. In this research article, we introduce an innovative glucose sensor that relies on microfluidic devices meticulously crafted from disposable, medical-grade tapes. These devices incorporate glucose urine analysis strips securely affixed to microscope glass slides. The microfluidic channels are intricately created through laser cutting, representing a departure from traditional cleanroom techniques. This approach streamlines production processes, enhances cost-efficiency, and obviates the need for specialized equipment. Subsequent to the absorption of the target solution, the disposable device is enclosed within a 3D-printed housing. Image capture is seamlessly facilitated through the use of a smartphone camera for subsequent colorimetric analysis. Our study adeptly demonstrates the glucose sensor's capability to accurately quantify glucose concentrations within sucrose solutions. This is achieved by employing an exponential regression model, elucidating the intricate relationship between glucose concentrations and average RGB (Red-Green-Blue) values. Furthermore, our comprehensive analysis reveals minimal variation in sensor performance across different instances. Significantly, this study underscores the potential adaptability and versatility of our solution for a wide array of assay types and smartphone-based sensor systems, making it particularly promising for deployment in resource-constrained settings and undeveloped countries. The robust correlation established between glucose concentrations and average RGB values, substantiated by an impressive R-square value of 0.98709, underscores the effectiveness and reliability of our pioneering approach within the medical field.

Emerging Roles of Microrobots for Enhancing the Sensitivity of Biosensors

To meet the increasing needs of point-of-care testing in clinical diagnosis and daily health monitoring, numerous cutting-edge techniques have emerged to upgrade current portable biosensors with higher sensitivity, smaller size, and better intelligence. In particular, due to the controlled locomotion characteristics in the micro/nano scale, microrobots can effectively enhance the sensitivity of biosensors by disrupting conventional passive diffusion into an active enrichment during the test. In addition, microrobots are ideal to create biosensors with functions of on-demand delivery, transportation, and multi-objective detections with the capability of actively controlled motion. In this review, five types of portable biosensors and their integration with microrobots are critically introduced. Microrobots can enhance the detection signal in fluorescence intensity and surface-enhanced Raman scattering detection via the active enrichment. The existence and quantity of detection substances also affect the motion state of microrobots for the locomotion-based detection. In addition, microrobots realize the indirect detection of the bio-molecules by functionalizing their surfaces in the electrochemical current and electrochemical impedance spectroscopy detections. We pay a special focus on the roles of microrobots with active locomotion to enhance the detection performance of portable sensors. At last, perspectives and future trends of microrobots in biosensing are also discussed.

Glyphosate Separating and Sensing for Precision Agriculture and Environmental Protection in the Era of Smart Materials

The present article critically and comprehensively reviews the most recent reports on smart sensors for determining glyphosate (GLP), an active agent of GLP-based herbicides (GBHs) traditionally used in agriculture over the past decades. Commercialized in 1974, GBHs have now reached 350 million hectares of crops in over 140 countries with an annual turnover of 11 billion USD worldwide. However, rolling exploitation of GLP and GBHs in the last decades has led to environmental pollution, animal intoxication, bacterial resistance, and sustained occupational exposure of the herbicide of farm and companies' workers. Intoxication with these herbicides dysregulates the microbiome-gut-brain axis, cholinergic neurotransmission, and endocrine system, causing paralytic ileus, hyperkalemia, oliguria, pulmonary edema, and cardiogenic shock. Precision agriculture, i.e., an (information technology)-enhanced approach to crop management, including a site-specific determination of agrochemicals, derives from the benefits of smart materials (SMs), data science, and nanosensors. Those typically feature fluorescent molecularly imprinted polymers or immunochemical aptamer artificial receptors integrated with electrochemical transducers. Fabricated as portable or wearable lab-on-chips, smartphones, and soft robotics and connected with SM-based devices that provide machine learning algorithms and online databases, they integrate, process, analyze, and interpret massive amounts of spatiotemporal data in a user-friendly and decision-making manner. Exploited for the ultrasensitive determination of toxins, including GLP, they will become practical tools in farmlands and point-of-care testing. Expectedly, smart sensors can be used for personalized diagnostics, real-time water, food, soil, and air quality monitoring, site-specific herbicide management, and crop control.

Micropatterning of functional lipid bilayer assays for quantitative bioanalysis

Interactions of the cell with its environment are mediated by the cell membrane and membrane-localized molecules. Supported lipid bilayers have enabled the recapitulation of the basic properties of cell membranes and have been broadly used to further our understanding of cellular behavior. Coupled with micropatterning techniques, lipid bilayer platforms have allowed for high throughput assays capable of performing quantitative analysis at a high spatiotemporal resolution. Here, an overview of the current methods of the lipid membrane patterning is presented. The fabrication and pattern characteristics are briefly described to present an idea of the quality and notable features of the methods, their utilizations for quantitative bioanalysis, as well as to highlight possible directions for the advanced micropatterning lipid membrane assays.

Excitation modalities for enhanced micro and nanoparticle imaging in a smartphone coupled 3D printed fluorescent microscope

Smartphone fluorescent microscopes (SFM) offer many functional characteristics similar to their benchtop counterparts at a fraction of the cost and have been shown to work for biomarker detection in many biomedical applications. However, imaging and quantification of bioparticles in the sub-micron and nanometer range remains challenging as it requires aggressive robustness and high-performance metrics of the building blocks of SFM. Here, we explored multiple excitation modalities and their performance on the imaging capability of an SFM. Employing spatial positional variations of the excitation source with respect to the imaging sample plane (i.e., parallel, perpendicular, oblique), we developed three distinct SFM variants. These SFM variants were tested using green-fluorescent beads of four different sizes (8.3, 2, 1, 0.8 μm). Optimal excitation voltage range was determined by imaging these beads at multiple excitation voltages to optimize for no data loss and acceptable noise levels for each SFM variant. The SFM with parallel excitation was able to only image 8.3 μm beads while the SFM variants with perpendicular and oblique excitation were able to image all four bead sizes. Relative performance of the SFM variants was quantified by calculating signal difference to noise ratio (SDNR) and contrast to noise ratio (CNR) from the captured images. SFM with oblique excitation generated the highest SDNR and CNR values, whereas, for power consumption, SFM with perpendicular excitation generated the best results. This study sheds light on significant findings related to performance of SFM systems and their potential utility in biomedical applications involving sub-micron imaging. Similarly, findings of this study are translatable to benchtop microscopy instruments as well as to enhance their imaging performance metrics.

Smartphone-based digital image colorimetry for the determination of vancomycin in drugs

A simple smartphone-based digital image colorimetry is proposed for the determination of vancomycin in drugs. The analytical method relied on the reaction of vancomycin with copper(II) in ethanol–water medium with pH 4.3. The reaction resulted in the formation of a blue–grey complex, presenting an absorption maximum at 555 nm. A mobile application was used for smartphone-based analysis to decompose the individual channels of the colour model representations. The determination was performed using three smartphones followed by a comparison of the outcomes with spectrophotometric measurements. The most optimal analytical parameters were achieved for the H channel. The linear ranges obtained for the smartphone-based method proved to be comparable to the spectrophotometric range of 0.044–1.500 g dm−3 and were 0.049–1.500 g dm−3, 0.057–1.500 g dm−3, and 0.040–1.500 g dm−3 for Smartphones 1–3, respectively. Moreover, the determined coefficients of variance (CV, n = 9) and limits of detection (LOD) were 2.3% and 0.015 g dm−3, 6.2% and 0.017 g dm−3, and 2.5% and 0.012 g dm−3, respectively. Whereas for spectrophotometry, the obtained precision, CV was of 0.9% and a LOD of 0.013 g dm−3. The accuracy of the method was verified using model samples, generally the results were obtained with accuracy better than 10.9% (relative error). The method was applied to the determination of vancomycin in drugs. The results obtained by smartphone-based colorimetry did not differ from the expected values for more than 2.6%, were consistent with each other and with the results of spectrophotometric determinations.

Graphical abstract

A Low-Cost Handheld Impedimetric Biosensing System for Rapid Diagnostics of SARS-CoV-2 Infections

Current laboratory diagnostic approaches for virus detection give reliable results, but they require a lengthy procedure, trained personnel, and expensive equipment and reagents; hence, they are not a suitable choice for home monitoring purposes. This paper addresses this challenge by developing a portable impedimetric biosensing system for the identification of COVID-19 patients. This sensing system has two main parts: a throwaway two-working electrode (2-WE) strip and a novel read-out circuit, specifically designed for simultaneous signal acquisition from both working electrodes. Highly reliable electrochemical signal tracking from multiplex immunosensors provides a potential for flexible and portable multi-biomarker detection. The electrodes' surfaces were functionalized with SARS-CoV-2 Nucleocapsid Antibody enabling the selective detection of Nucleocapsid protein (N-protein) along with self-validation in the clinical nasopharyngeal swab specimens. The proposed programmable highly sensitive impedance read-out system allows for a wide dynamic detection range, which makes the sensor capable of detecting N-protein concentrations between 0.116 and 10,000 pg/mL. This lightweight and economical read-out arrangement is an ideal prospect for being mass-produced, especially during urgent pandemic situations. Also, such an impedimetric sensing platform has the potential to be redesigned for targeting not only other infectious diseases but also other critical disorders.

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.

A Simple and Reliable Dispersive Liquid-Liquid Microextraction with Smartphone-Based Digital Images for Determination of Carbaryl Residues in Andrographis paniculata Herbal Medicines Using Simple Peroxidase Extract from Senna siamea Lam. Bark

A simple and reliable dispersive liquid-liquid microextraction (DLLME) coupled with smartphone-based digital images using crude peroxidase extracts from cassia bark (Senna siamea Lam.) was proposed to determine carbaryl residues in Andrographis paniculata herbal medicines. The method was based on the reaction of 1-naphthol (hydrolysis of carbaryl) with 4-aminoantipyrine (4-AP) in the presence of hydrogen peroxide, using peroxidase enzyme simple extracts from cassia bark as biocatalysts under pH 6.0. The red product, after preconcentration by DLLME using dichloromethane as extraction solvent, was measured for blue intensity by daily life smartphone-based digital image analysis. Under optimized conditions, good linearity of the calibration graph was found at 0.10–0.50 mg·L⁻¹ (r² = 0.9932). Limits of detection (LOD) (3SD/slope) and quantification (LOQ) (10SD/slope) were 0.03 and 0.09 mg·L⁻¹, respectively, with a precision of less than 5%. Accuracy of the proposed method as percentage recovery gave satisfactory results. The proposed method was successfully applied to analyze carbaryl in Andrographis paniculata herbal medicines. Results agreed well with values obtained from the HPLC-UV method at 95% confidence level. This was simple, convenient, reliable, cost-effective and traceable as an alternative method for the determination of carbaryl.

Portable FRET-Based Biosensor Device for On-Site Lead Detection

Most methods for measuring environmental lead (Pb) content are time consuming, expensive, hazardous, and restricted to specific analytical systems. To provide a facile, safe tool to detect Pb, we created pMet-lead, a portable fluorescence resonance energy transfer (FRET)-based Pb-biosensor. The pMet-lead device comprises a 3D-printed frame housing a 405-nm laser diode-an excitation source for fluorescence emission images (YFP and CFP)-accompanied by optical filters, a customized sample holder with a Met-lead 1.44 M1 (the most recent version)-embedded biochip, and an optical lens aligned for smartphone compatibility. Measuring the emission ratios (Y/C) of the FRET components enabled Pb detection with a dynamic range of nearly 2 (1.96), a pMet-lead/Pb dissociation constant (K_d) 45.62 nM, and a limit of detection 24 nM (0.474 μg/dL, 4.74 ppb). To mitigate earlier problems with a lack of selectivity for Pb vs. zinc, we preincubated samples with tricine, a low-affinity zinc chelator. We validated the pMet-lead measurements of the characterized laboratory samples and unknown samples from six regions in Taiwan by inductively coupled plasma mass spectrometry (ICP-MS). Notably, two unknown samples had Y/C ratios significantly higher than that of the control (3.48 ± 0.08 and 3.74 ± 0.12 vs. 2.79 ± 0.02), along with Pb concentrations (10.6 ppb and 15.24 ppb) above the WHO-permitted level of 10 ppb in tap water, while the remaining four unknowns showed no detectable Pb upon ICP-MS. These results demonstrate that pMet-lead provides a rapid, sensitive means for on-site Pb detection in water from the environment and in living/drinking supply systems to prevent potential Pb poisoning.

On-board smartphone micromotor-based fluorescence assays

Herein, we describe the design of a portable device integrated with micromotors for real-time fluorescence sensing of (bio)markers. The system comprises a universal 3D printed platform to hold a commercial smartphone, which is equipped with an external magnification optical lens (20-400×) and tailor-made emission filters directly attached to the camera, an adjustable sample holder to accommodate a glass slide and laser excitation sources. On a first approach, we illustrate the suitability of the platform using magnetic Janus micromotors modified with fluorescent ZnS@CdxSe1-x quantum dots for real-time ON-OFF mercury detection. On a second approach, graphdiyne tubular catalytic micromotors modified with a rhodamine labelled affinity peptide are used for the OFF-ON detection of cholera toxin B. The micromotor-based smartphone for fluorescence sensing approach was compared to a high-performance optical microscope, and similar analytical features were obtained. This versatility allows for easy integration of micromotor fluorescence sensing strategies based on different propulsion mechanisms, allowing for its future use with a myriad of biomarkers and even multiplexed schemes.

Smartphone-Based Janus Micromotors Strategy for Motion-Based Detection of Glutathione

Herein, we describe a Janus micromotor smartphone platform for the motion-based detection of glutathione. The system compromises a universal three-dimensional (3D)-printed platform to hold a commercial smartphone, which is equipped with an external magnification optical lens (20-400×) directly attached to the camera, an adjustable sample holder to accommodate a glass slide, and a light-emitting diode (LED) source. The presence of glutathione in peroxide-rich sample media results in the decrease in the speed of 20 μm graphene-wrapped/PtNPs Janus micromotors due to poisoning of the catalytic layer by a thiol bond formation. The speed can be correlated with the concentration of glutathione, achieving a limit of detection of 0.90 μM, with percent recoveries and excellent selectivity under the presence of interfering amino acids and proteins. Naked-eye visualization of the speed decrease allows for the design of a test strip for fast glutathione detection (30 s), avoiding previous amplification strategies or sample preparation steps. The concept can be extended to other micromotor approaches relying on fluorescence or colorimetric detection for future multiplexed schemes.

Machine-Learning-Assisted Analysis of Colorimetric Assays on Paper Analytical Devices

Paper-based analytical devices (PADs) employing colorimetric detection and smartphone images have gained wider acceptance in a variety of measurement applications. PADs are primarily meant to be used in field settings where assay and imaging conditions greatly vary, resulting in less accurate results. Recently, machine-learning (ML)-assisted models have been used in image analysis. We evaluated a combination of four ML models-logistic regression, support vector machine (SVM), random forest, and artificial neural network (ANN)-as well as three image color spaces, RGB, HSV, and LAB, for their ability to accurately predict analyte concentrations. We used images of PADs taken at varying lighting conditions, with different cameras and users for food color and enzyme inhibition assays to create training and test datasets. The prediction accuracy was higher for food color than enzyme inhibition assays in most of the ML models and color space combinations. All models better predicted coarse-level classifications than fine-grained concentration classes. ML models using the sample color along with a reference color increased the models' ability to predict the result in which the reference color may have partially factored out the variation in ambient assay and imaging conditions. The best concentration class prediction accuracy obtained for food color was 0.966 when using the ANN model and LAB color space. The accuracy for enzyme inhibition assay was 0.908 when using the SVM model and LAB color space. Appropriate models and color space combinations can be useful to analyze large numbers of samples on PADs as a powerful low-cost quick field-testing tool.

5G-Enabled intelligent construction of a chest pain center with up-conversion lateral flow immunoassay

Acute myocardial infarction (AMI) has become a worldwide health problem because of its rapid onset and high mortality. Cardiac troponin I (cTnI) is the gold standard for diagnosis of AMI, and its rapid and accurate detection is critical for early diagnosis and management of AMI. Using a lateral flow immunoassay with upconverting nanoparticles as fluorescent probes, we developed an up-conversion fluorescence reader capable of rapidly quantifying the cTnI concentration in serum based upon the fluorescence intensity of the test and control lines on the test strip. Reliable detection of cTnI in the range 0.1-50 ng mL^-1 could be achieved in 15 min, with a lower detection limit of 0.1 ng mL^-1. The reader was also adapted for use on a 5th generation (5G) mobile network enabled intelligent chest pain center. Through Bluetooth wireless communication, the results achieved using the reader on an ambulance heading to a central hospital could be transmitted to a 5G smartphone and uploaded for real-time edge computing and cloud storage. An application in the 5G smartphone allows users to upload their medical information to establish dedicated electronic health records and doctors to monitor patients' health status and provide remote medical services. Combined with mobile internet and big data, the 5G-enabled intelligent chest pain center with up-conversion lateral flow immunoassay may predict the onset of AMI and save valuable time for patients suffering an AMI.

Multiplexed Profiling of Extracellular Vesicles for Biomarker Development

Extracellular vesicles (EVs) are cell-derived membranous particles that play a crucial role in molecular trafficking, intercellular transport and the egress of unwanted proteins. They have been implicated in many diseases including cancer and neurodegeneration. EVs are detected in all bodily fluids, and their protein and nucleic acid content offers a means of assessing the status of the cells from which they originated. As such, they provide opportunities in biomarker discovery for diagnosis, prognosis or the stratification of diseases as well as an objective monitoring of therapies. The simultaneous assaying of multiple EV-derived markers will be required for an impactful practical application, and multiplexing platforms have evolved with the potential to achieve this. Herein, we provide a comprehensive overview of the currently available multiplexing platforms for EV analysis, with a primary focus on miniaturized and integrated devices that offer potential step changes in analytical power, throughput and consistency.

Fluorescence Nano Particle Detection in a Liquid Sample Using the Smartphone for Biomedical Application

In this paper, we present a Smartphone-based Fluorescence Nanoparticle Detector (SPF-NPD) that can be used for identifying biological agents in biomedical applications. The experimental setup consists of an LED light source and an Eppendorf tube holder placed inside a dark chamber with an optimally located slit for aligning the camera of a smartphone. The camera acquires the fluorescence intensity variations in the target liquid sample placed in the Eppendorf tube and passes it to a dedicated android application running in the smartphone. Using the principle of fluorescence-based pathogen detection, the android application detects the pathogens and displays the results within a few seconds. Since, all smartphones are equipped with high-resolution cameras, the proposed SPF-NPD provides a simple and elegant solution for instantaneous detection of fluorescence nano particles and has a great potential for healthcare applications for live detection of pathogens. The intensity measurement in SPF-NPD algorithm uses 5-pixel method, that is, the center pixel followed by four immediate neighbor pixels, because of which, minimal sample quantity is sufficient for precise measurements. We establish the robustness of SPF-NPD through exhaustive experiments with various smartphone cameras having different resolutions ranging from 8 to 20 Megapixels. The results of the proposed SPF-NPD method are validated against those obtained from standard devices such as Perkin-Elmer Picoflor and Perkin-Elmer Enspire. The advantages of the proposed method are highlighted.

Application of centrifugal microfluidics in immunoassay, biochemical analysis and molecular diagnosis

Rapid diagnosis plays a vital role in daily life and is effective in reducing treatment costs and increasing curability, especially in remote areas with limited availability of resources. Among the various common methods of rapid diagnosis, centrifugal microfluidics has many unique advantages, such as less sample consumption, more precise valve control for sequential loading of samples, and accurately separated module design in a microfluidic network to minimize cross-contamination. Therefore, in recent years, centrifugal microfluidics has been extensively researched, and it has been found to play important roles in biology, chemistry, and medicine. Here, we review the latest developments in centrifugal microfluidic platforms in immunoassays, biochemical analyses, and molecular diagnosis, in recent years. In immunoassays, we focus on the application of enzyme-linked immunosorbent assay (ELISA); in biochemical analysis, we introduce the application of plasma and blood cell separation; and in molecular diagnosis, we highlight the application of nucleic acid amplification tests. Additionally, we discuss the characteristics of the methods under each platform as well as the enhancement of the corresponding performance parameters, such as the limit of detection, separation efficiency, etc. Finally, we discuss the limitations associated with the existing applications and potential breakthroughs that can be achieved in this field in the future.

Smartphone-assisted point-of-care colorimetric biosensor for the detection of urea via pH-mediated AgNPs growth

Smartphone-assisted point-of-care (POC) bioassay has brought a giant leap in personal healthcare system and environmental monitoring advancements. In this study, we developed a rapid and reliable colorimetric urea biosensor assisted by a smartphone. We employed hydrolysis of urea into NH₃ by urease, which activates the reduction power of tannic acid, to generate silver nanoparticles for a dramatic colorimetric response. The proposed urea biosensor was validated in a solution to provide high selectivity against various interferents in human urine. It had high sensitivity, with a limit of detection as low as 0.0036 mM, and a high reliability of 99% ± 2.9% via the standard addition method. The urea biosensor was successfully implanted on a paper to facilitate smartphone-assisted POC readout with a limit of detection of 0.58 mM and wide detection range of 500 mM, whereby direct diagnosis of human urine without dilution was realized. Our smartphone-assisted POC colorimetric urea biosensor will pave the way for daily monitoring systems of renal and hepatic dysfunction diseases.

Substrate Materials for Biomolecular Immobilization within Electrochemical Biosensors

Electrochemical biosensors have potential applications for agriculture, food safety, environmental monitoring, sports medicine, biomedicine, and other fields. One of the primary challenges in this field is the immobilization of biomolecular probes atop a solid substrate material with adequate stability, storage lifetime, and reproducibility. This review summarizes the current state of the art for covalent bonding of biomolecules onto solid substrate materials. Early research focused on the use of Au electrodes, with immobilization of biomolecules through ω-functionalized Au-thiol self-assembled monolayers (SAMs), but stability is usually inadequate due to the weak Au-S bond strength. Other noble substrates such as C, Pt, and Si have also been studied. While their nobility has the advantage of ensuring biocompatibility, it also has the disadvantage of making them relatively unreactive towards covalent bond formation. With the exception of Sn-doped In2O3 (indium tin oxide, ITO), most metal oxides are not electrically conductive enough for use within electrochemical biosensors. Recent research has focused on transition metal dichalcogenides (TMDs) such as MoS2 and on electrically conductive polymers such as polyaniline, polypyrrole, and polythiophene. In addition, the deposition of functionalized thin films from aryldiazonium cations has attracted significant attention as a substrate-independent method for biofunctionalization.

Pushbutton-activated microfluidic cartridge as a user-friendly sample preparation tool for diagnostics

Microfluidic technologies have several advantages in sample preparation for diagnostics but suffer from the need for an external operation system that hampers user-friendliness. To overcome this limitation in microfluidic technologies, a number of user-friendly methods utilizing capillary force, degassed poly(dimethylsiloxane), pushbutton-driven pressure, a syringe, or a pipette have been reported. Among these methods, the pushbutton-driven, pressure-based method has a great potential to be widely used as a user-friendly sample preparation tool for point-of-care testing or portable diagnostics. In this Perspective, we focus on the pushbutton-activated microfluidic technologies toward a user-friendly sample preparation tool. The working principle and recent advances in pushbutton-activated microfluidic technologies are briefly reviewed, and future perspectives for wide application are discussed in terms of integration with the signal analysis system, user-dependent variation, and universal and facile use.

A novel smartphone-based colorimetric aptasensor for on-site detection of Escherichia coli O157:H7 in milk

Effective testing tools for Escherichia coli O157:H7 can prevent outbreaks of foodborne illness. In this paper, a smartphone-based colorimetric aptasensor was developed using functionalized gold nanoparticles (GNP) and multi-walled carbon nanotubes (MWCNT) for monitoring E. coli O157:H7 in milk. The maximum absorption peak of GNP bonded with aptamer (Apt) generated evident transformation from 518 to 524 nm. The excess GNP-Apt was removed by functionalized MWCNT magnetized with carbonyl iron powder (CIP) and hybridized with a DNA probe, whereas the GNP-Apt immobilized on E. coli O157:H7 remained in the system. In the presence of a high-salt solution, the GNP-Apt that captured E. coli O157:H7 remained red, but the free GNP-Apt aggregated and appeared blue. The chromogenic results were analyzed by a smartphone-based colorimetric device that was fabricated using acrylic plates, a light-emitting diode, and a mobile power pack. To our knowledge, this was the first attempt to use a smartphone-based colorimetric aptasensor employing the capture of GNP-Apt coupled with separation of MWCNT@CIP probe to detect E. coli O157:H7. The aptasensor exhibited good reproducibility and no cross-reaction for other bacteria. A concentration of 8.43 × 10³ cfu/mL of E. coli O157:H7 could be tested in pure culture, and 5.24 × 10² cfu/mL of E. coli O157:H7 could be detected in artificially contaminated milk after 1 h of incubation. Therefore, the smartphone-based colorimetric aptasensor was an efficient tool for the detection of E. coli O157:H7 in milk.

Herpesviruses in Reptiles

Since the 1970s, several species of herpesviruses have been identified and associated with significant diseases in reptiles. Earlier discoveries placed these viruses into different taxonomic groups on the basis of morphological and biological characteristics, while advancements in molecular methods have led to more recent descriptions of novel reptilian herpesviruses, as well as providing insight into the phylogenetic relationship of these viruses. Herpesvirus infections in reptiles are often characterised by non-pathognomonic signs including stomatitis, encephalitis, conjunctivitis, hepatitis and proliferative lesions. With the exception of fibropapillomatosis in marine turtles, the absence of specific clinical signs has fostered misdiagnosis and underreporting of the actual disease burden in reptilian populations and hampered potential investigations that could lead to the effective control of these diseases. In addition, complex life histories, sampling bias and poor monitoring systems have limited the assessment of the impact of herpesvirus infections in wild populations and captive collections. Here we review the current published knowledge of the taxonomy, pathogenesis, pathology and epidemiology of reptilian herpesviruses.

FEAST of biosensors: Food, environmental and agricultural sensing technologies (FEAST) in North America

We review the challenges and opportunities for biosensor research in North America aimed to accelerate translational research. We call for platform approaches based on: i) tools that can support interoperability between food, environment and agriculture, ii) open-source tools for analytics, iii) algorithms used for data and information arbitrage, and iv) use-inspired sensor design. We summarize select mobile devices and phone-based biosensors that couple analytical systems with biosensors for improving decision support. Over 100 biosensors developed by labs in North America were analyzed, including lab-based and portable devices. The results of this literature review show that nearly one quarter of the manuscripts focused on fundamental platform development or material characterization. Among the biosensors analyzed for food (post-harvest) or environmental applications, most devices were based on optical transduction (whether a lab assay or portable device). Most biosensors for agricultural applications were based on electrochemical transduction and few utilized a mobile platform. Presently, the FEAST of biosensors has produced a wealth of opportunity but faces a famine of actionable information without a platform for analytics.

Magnetic Nanoparticle-Based Ligand Replacement Strategy for Chemical Luminescence Determination of Cholesterol

Determination of serum cholesterol (Chol) is important for disease diagnosis, and has attracted great attention during the last few decades. Herein, a new magnetic nanoparticle-based ligand replacement strategy has been presented for chemical luminescence detection of Chol. The detection depends on ligand replacement from ferrocene (Fc) to Chol through a β-cyclodextrin (β-CD)-based host-guest interaction, which releases Fc-Hemin as a catalyst for the luminol/hydrogen peroxide chemical luminescence system. More importantly, the luminescence signal can be captured by the camera of a smartphone, thus realizing Chol detection with less instrument dependency. The limit of detection of this method is calculated to be 0.18 μM, which is comparable to some of the developed methods. Moreover, this method has been used successfully to quantify Chol from serum samples with a simple extraction process.

Digital image colorimetry detection of carbaryl in food samples based on liquid phase microextraction coupled with a microfluidic thread-based analytical device

This research used a digital image colorimetry (DIC) method to detect carbaryl in food samples using effervescence-assisted liquid phase microextraction based on solidification of switchable hydrophilicity solvent combined with a microfluidic thread-based analytical device (EA-LPME-SSHS-μTAD). 1-naphthol, the hydrolysate of carbaryl, was extracted into octanoic acid by the adjustment of pH values of the sample solution and separated through solidification in an ice bath. Then 1-naphthol contained in the extracted solution was coupled with 4-methoxybenzenediazonlum tetrafluoroborate (MBDF) fixed on the μTAD to produce tangerine compounds. The inherent colour variation was captured by a smartphone and processed to calculate the intensity (I). Under the optimal conditions, the limit of quantification was within 0.020-0.027 mg kg^-1. The recovery was varied in the range from 92.3% to 105.9% with a relative standard deviation (RSD) below 5%. The developed method provides an alternative strategy to extract and detect pesticides for food samples.

Electrochemiluminescence Mechanisms Investigated with Smartphone-Based Sensor Data Modeling, Parameter Estimation and Sensitivity Analysis

The present study introduces a unified framework combining a mechanistic model with a genetic algorithm (GA) for the parameter estimation of electrochemiluminescence (ECL) kinetics of the Ru(bpy)32+/TPrA system occurring in a smartphone-based sensor. The framework allows a straightforward solution for simultaneous estimation of multiple parameters which can be, otherwise, time-consuming and lead to non-convergence. Model parameters are estimated by achieving a high correlation between the model prediction and the measured ECL intensity from the ECL sensor. The developed model is used to perform a sensitivity analysis (SA), which provides quantitative effects of the model parameters on the concentrations of chemical species involved in the system. The results demonstrate that the GA-based parameter estimation and the SA approaches are effective in analyzing the kinetics of the ECL mechanism. Therefore, these approaches can be incorporated as analysis tools in the ECL kinetics study with practical application in the calibration of mechanistic models for any required sensing condition.