Optofluidic fluorescent imaging cytometry on a cell phone

Towards ultra-low-cost smartphone microscopy

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here, we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼5 𝜇m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we used an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We used the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. RESEARCH HIGHLIGHTS: We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼5 𝜇m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.

Visualization and Analysis of Mapping Knowledge Domain of Fluid Flow Related to Microfluidic Chip

Microfluidic chips are important tools to study the microscopic flow of fluid. To better understand the research clues and development trends related to microfluidic chips, a bibliometric analysis of microfluidic chips was conducted based on 1115 paper records retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer software were used to analyze the distribution of annual paper quantity, country/region distribution, subject distribution, institution distribution, major source journals distribution, highly cited papers, coauthor cooperation relationship, research knowledge domain, research focuses, and research frontiers, and a knowledge domain map was drawn. The results show that the number of papers published on microfluidic chips increased from 2010 to 2023, among which China, the United States, Iran, Canada, and Japan were the most active countries in this field. The United States was the most influential country. Nanoscience, energy, and chemical industry and multidisciplinary materials science were the main fields of microfluidic chip research. Lab on a Chip, Microfluidics and Nanofluidics, and Journal of Petroleum Science and Engineering were the main sources of papers published. The fabrication of chips, as well as their applications in porous media flow and multiphase flow, is the main knowledge domain of microfluidic chips. Micromodeling, fluid displacement, wettability, and multiphase flow are the research focuses in this field currently. The research frontiers in this field are enhanced oil recovery, interfacial tension, and stability.

Smartphone Imaging Flow Cytometry for High-Throughput Single-Cell Analysis

We present a portable imaging flow cytometer comprising a smartphone, a small-footprint optical framework, and a PDMS-based microfluidic device. Flow cytometric analysis is performed in a sheathless manner via elasto-inertial focusing with a custom-written Android program, integrating a graphical user interface (GUI) that provides a high degree of user control over image acquisition. The proposed system offers two different operational modes. First, "post-processing" mode enables particle/cell sizing at throughputs of up to 67 000 particles/s. Alternatively, "real-time" mode allows for integrated cell/particle classification with machine learning at throughputs of 100 particles/s. To showcase the efficacy of our platform, polystyrene particles are accurately enumerated within heterogeneous populations using the post-processing mode. In real-time mode, an open-source machine learning algorithm is deployed within a custom-developed Android application to classify samples containing cells of similar size but with different morphologies. The flow cytometer can extract high-resolution bright-field images with a spatial resolution <700 nm using the developed machine learning-based algorithm, achieving classification accuracies of 97% and 93% for Jurkat and EL4 cells, respectively. Our results confirm that the smartphone imaging flow cytometer (sIFC) is capable of both enumerating single particles in flow and identifying morphological features with high resolution and minimal hardware.

Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence

The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms.

Moving toward smart biomedical sensing

The development of novel biomedical sensors as highly promising devices/tools in early diagnosis and therapy monitoring of many diseases and disorders has recently witnessed unprecedented growth; more and faster than ever. Nonetheless, on the eve of Industry 5.0 and by learning from defects of current sensors in smart diagnostics of pandemics, there is still a long way to go to achieve the ideal biomedical sensors capable of meeting the growing needs and expectations for smart biomedical/diagnostic sensing through eHealth systems. Herein, an overview is provided to highlight the importance and necessity of an inevitable transition in the era of digital health/Healthcare 4.0 towards smart biomedical/diagnostic sensing and how to approach it via new digital technologies including Internet of Things (IoT), artificial intelligence, IoT gateways (smartphones, readers), etc. This review will bring together the different types of smartphone/reader-based biomedical sensors, which have been employing for a wide variety of optical/electrical/electrochemical biosensing applications and paving the way for future eHealth diagnostic devices by moving towards smart biomedical sensing. Here, alongside highlighting the characteristics/criteria that should be met by the developed sensors towards smart biomedical sensing, the challenging issues ahead are delineated along with a comprehensive outlook on this extremely necessary field.

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.

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.

Development of a double monitoring system for the determination of Cr(VI) in different water matrices by HPLC-UV and digital image-based colorimetric detection method with the help of a metal sieve-linked double syringe system in complexation

This study reports a cheap, efficient, sensitive, and simple double monitoring analytical method for trace determination of Cr(VI), which is toxic and harmful even at very low concentrations. A metal sieve-linked double syringe (MSLDS) system was used to help the formation of chromium complex (Cr-diphenyl carbazide, DPC) subsequently determined by high-performance liquid chromatography-ultraviolet (HPLC-UV) and digital image-based colorimetry (DIC) systems. The metal complex was eluted through a Phenomenex-Aqua C18 with a mobile phase comprising of 50 mM ammonium formate solution (pH 4.0):acetonitrile (78:22, v/v) and detected by the UV detector at the wavelength of 581 nm. Under their optimum conditions, the HPLC-UV and DIC systems exhibited good linearity in ranges of 10-500 µg L^-1 and 100-1000 µg L^-1, respectively. The percent relative standard deviations (RSD%s) calculated for the lowest concentrations of both systems fell below 10%, and this confirmed good repeatability for replicate measurements. The accuracy of the proposed methods was evaluated by performing spike recovery experiments on wastewater, river water, and tap water samples. The calculated recovery results were in the range of 81.5-105.5% for HPLC-UV system and 93.8-111.1% for the DIC system. These results indicate that the proposed methods are suitable for routine Cr(VI) determination in terms of their rapidness, simplicity, good repeatability, and low cost.

Multi-Mode Compact Microscopy for High-Contrast and High-Resolution Imaging

We report a multi-mode compact microscope (MCM) for high-contrast and high-resolution imaging. The MCM consists of two LED illuminations, a magnification lens, a lift stage, and a housing with image processing and LED control boards. The MCM allows multi-modal imaging, including reflection, transmission, and higher magnification modes. The dual illuminations also provide high-contrast imaging of various targets such as biological samples and microcircuits. The high dynamic range (HDR) imaging reconstruction of MCM increases the dynamic range of the acquired images by 1.36 times. The microlens array (MLA)-assisted MCM also improves image resolution through the magnified virtual image of MLA. The MLA-assisted MCM successfully provides a clear, magnified image by integrating a pinhole mask to prevent image overlap without additional alignment. The magnification of MLA-assisted MCM was increased by 3.92 times compared with that of MCM, and the higher magnification mode demonstrates the image resolution of 2.46 μm. The compact portable microscope can provide a new platform for defect inspection or disease detection on site.

A Cost-Effective Nucleic Acid Detection System Using a Portable Microscopic Device

A fluorescence microscope is one of the most important tools for biomedical research and laboratory diagnosis. However, its high cost and bulky size hinder the application of laboratory microscopes in space-limited and low-resource applications. Here, in this work, we proposed a portable and cost-effective fluorescence microscope. Assembled from a set of 3D print components and a webcam, it consists of a three-degree-of-freedom sliding platform and a microscopic imaging system. The microscope is capable of bright-field and fluorescence imaging with micron-level resolution. The resolution and field of view of the microscope were evaluated. Compared with a laboratory-grade inverted fluorescence microscope, the portable microscope shows satisfactory performance, both in the bright-field and fluorescence mode. From the configurations of local resources, the microscope costs around USD 100 to assemble. To demonstrate the capability of the portable fluorescence microscope, we proposed a quantitative polymerase chain reaction experiment for meat product authenticating applications. The portable and low-cost microscope platform demonstrates the benefits in space-constrained environments and shows high potential in telemedicine, point-of-care testing, and more.

A comprehensive review on LED-induced fluorescence in diagnostic pathology

Sensitivity, specificity, mobility, and affordability are important criteria to consider for developing diagnostic instruments in common use. Fluorescence spectroscopy has been demonstrating substantial potential in the clinical diagnosis of diseases and evaluating the underlying causes of pathogenesis. A higher degree of device integration with appropriate sensitivity and reasonable cost would further boost the value of the fluorescence techniques in clinical diagnosis and aid in the reduction of healthcare expenses, which is a key economic concern in emerging markets. Light-emitting diodes (LEDs), which are inexpensive and smaller are attractive alternatives to conventional excitation sources in fluorescence spectroscopy, are gaining a lot of momentum in the development of affordable, compact analytical instruments of clinical relevance. The commercial availability of a broad range of LED wavelengths (255-4600 nm) has opened up new avenues for targeting a wide range of clinically significant molecules (both endogenous and exogenous), thereby diagnosing a range of clinical illnesses. As a result, we have specifically examined the uses of LED-induced fluorescence (LED-IF) in preclinical and clinical evaluations of pathological conditions, considering the present advancements in the field.

Prototype Smartphone-Based Device for Flow Cytometry with Immunolabeling via Supra-nanoparticle Assemblies of Quantum Dots

Methods for the detection, enumeration, and typing of cells are important in many areas of research and healthcare. In this context, flow cytometers are a widely used research and clinical tool but are also an example of a large and expensive instrument that is limited to specialized laboratories. Smartphones have been shown to have excellent potential to serve as portable and lower-cost platforms for analyses that would normally be done in a laboratory. Here, we developed a prototype smartphone-based flow cytometer (FC). This compact 3D-printed device incorporated a laser diode and a microfluidic flow cell and used the built-in camera of a smartphone to track immunofluorescently labeled cells in suspension and measure their color. This capability was enabled by high-brightness supra-nanoparticle assemblies of colloidal semiconductor quantum dots (SiO₂@QDs) as well as a support vector machine (SVM) classification algorithm. The smartphone-based FC device detected and enumerated target cells against a background of other cells, simultaneously and selectively counted two different cell types in a mixture, and used multiple colors of SiO₂@QD-antibody conjugates to screen for and identify a particular cell type. The potential limits of multicolor detection are discussed alongside ideas for further development. Our results suggest that innovations in materials and engineering should enable eventual smartphone-based FC assays for clinical applications.

Examination of blood samples using deep learning and mobile microscopy

Background

Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and labor intensive. The development of a point-of-care system based on a mobile microscope and powerful algorithms would be beneficial for providing care directly at the patient's bedside. For this purpose human blood samples were visualized using a low-cost mobile microscope, an ocular camera and a smartphone. Training and optimisation of different deep learning methods for instance segmentation are used to detect and count the different blood cells. The accuracy of the results is assessed using quantitative and qualitative evaluation standards.

Results

Instance segmentation models such as Mask R-CNN, Mask Scoring R-CNN, D2Det and YOLACT were trained and optimised for the detection and classification of all blood cell types. These networks were not designed to detect very small objects in large numbers, so extensive modifications were necessary. Thus, segmentation of all blood cell types and their classification was feasible with great accuracy: qualitatively evaluated, mean average precision of 0.57 and mean average recall of 0.61 are achieved for all blood cell types. Quantitatively, 93% of ground truth blood cells can be detected.

Conclusions

Mobile blood testing as a point-of-care system can be performed with diagnostic accuracy using deep learning methods. In the future, this application could enable very fast, cheap, location- and knowledge-independent patient care.

Smartphone-Operated Wireless Chemical Sensors: A Review

Wireless chemical sensors have been developed as a result of advances in chemical sensing and wireless communication technology. Because of their mobility and widespread availability, smartphones have been extensively combined with sensors such as hand-held detectors, sensor chips, and test strips for biochemical detection. Smartphones are frequently used as controllers, analyzers, and displayers for quick, authentic, and point-of-care monitoring, which may considerably streamline the design and lower the cost of sensing systems. This study looks at the most recent wireless and smartphone-supported chemical sensors. The review is divided into four different topics that emphasize the basic types of wireless smartphone-operated chemical sensors. According to a study of 114 original research publications published during recent years, market opportunities for wireless and smartphone-supported chemical sensor systems include environmental monitoring, healthcare and medicine, food quality, sport, and fitness. The issues and illustrations for each of the primary chemical sensors relevant to many application areas are covered. In terms of performance, the advancement of technologies related to chemical sensors will result in smaller and more lightweight, cost-effective, versatile, and durable devices. Given the limitations, we suggest that wireless and smartphone-supported chemical sensor systems play a significant role in the sensor Internet of Things.

Portable on-chip colorimetric biosensing platform integrated with a smartphone for label/PCR-free detection of Cryptosporidium RNA

Cryptosporidium, a protozoan pathogen, is a leading threat to public health and the economy. Herein, we report the development of a portable, colorimetric biosensing platform for the sensitive, selective and label/PCR-free detection of Cryptosporidium RNA using oligonucleotides modified gold nanoparticles (AuNPs). A pair of specific thiolated oligonucleotides, complementary to adjacent sequences on Cryptosporidium RNA, were attached to AuNPs. The need for expensive laboratory-based equipment was eliminated by performing the colorimetric assay on a micro-fabricated chip in a 3D-printed holder assembly. A smartphone camera was used to capture an image of the color change for quantitative analysis. The detection was based on the aggregation of the gold nanoparticles due to the hybridization between the complementary Cryptosporidium RNA and the oligonucleotides immobilized on the AuNPs surface. In the complementary RNA's presence, a distinctive color change of the AuNPs (from red to blue) was observed by the naked eye. However, in the presence of non-complementary RNA, no color change was observed. The sensing platform showed wide linear responses between 5 and 100 µM with a low detection limit of 5 µM of Cryptosporidium RNA. Additionally, the sensor developed here can provide information about different Cryptosporidium species present in water resources. This cost-effective, easy-to-use, portable and smartphone integrated on-chip colorimetric biosensor has great potential to be used for real-time and portable POC pathogen monitoring and molecular diagnostics.

Generation of programmable dynamic flow patterns in microfluidics using audio signals

Customised audio signals, such as musical notes, can be readily generated by audio software on smartphones and played over audio speakers. Audio speakers translate electrical signals into the mechanical motion of the speaker cone. Coupling the inlet tube to the speaker cone causes the harmonic oscillation of the tube, which in turn changes the velocity profile and flow rate. We employ this strategy for generating programmable dynamic flow patterns in microfluidics. We show the generation of customised rib and vortex patterns through the application of multi-tone audio signals in water-based and whole blood samples. We demonstrate the precise capability to control the number and extent of the ribs and vortices by simply setting the frequency ratio of two- and three-tone audio signals. We exemplify potential applications of tube oscillation for studying the functional responses of circulating immune cells under pathophysiological shear rates. The system is programmable, compact, low-cost, biocompatible, and durable. These features make it suitable for a variety of applications across chemistry, biology, and physics.

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.

3D printed imaging platform for portable cell counting

Despite having widespread application in the biomedical sciences, flow cytometers have several limitations that prevent their application to point-of-care (POC) diagnostics in resource-limited environments. 3D printing provides a cost-effective approach to improve the accessibility of POC devices in resource-limited environments. Towards this goal, we introduce a 3D-printed imaging platform (3DPIP) capable of accurately counting particles and perform fluorescence microscopy. In our 3DPIP, captured microscopic images of particle flow are processed on a custom developed particle counter code to provide a particle count. This prototype uses a machine vision-based algorithm to identify particles from captured flow images and is flexible enough to allow for labeled and label-free particle counting. Additionally, the particle counter code returns particle coordinates with respect to time which can further be used to perform particle image velocimetry. These results can help estimate forces acting on particles, and identify and sort different types of cells/particles. We evaluated the performance of this prototype by counting 10 μm polystyrene particles diluted in deionized water at different concentrations and comparing the results with a commercial Beckman-Coulter Z2 particle counter. The 3DPIP can count particle concentrations down to ∼100 particles per mL with a standard deviation of ±20 particles, which is comparable to the results obtained on a commercial particle counter. Our platform produces accurate results at flow rates up to 9 mL h-1 for concentrations below 1000 particle per mL, while 5 mL h-1 produces accurate results above this concentration limit. Aside from performing flow-through experiments, our instrument is capable of performing static experiments that are comparable to a plate reader. In this configuration, our instrument is able to count between 10 and 250 cells per image, depending on the prepared concentration of bacteria samples (Citrobacter freundii; ATCC 8090). Overall, this platform represents a first step towards the development of an affordable fully 3D printable imaging flow cytometry instrument for use in resource-limited clinical environments.

Smartphone-Enabled Personalized Diagnostics: Current Status and Future Prospects

Smartphones are becoming increasingly versatile thanks to the wide variety of sensor and actuator systems packed in them. Mobile devices today go well beyond their original purpose as communication devices, and this enables important new applications, ranging from augmented reality to the Internet of Things. Personalized diagnostics is one of the areas where mobile devices can have the greatest impact. Hitherto, the camera and communication abilities of these devices have been barely exploited for point of care (POC) purposes. This short review covers the recent evolution of mobile devices in the area of POC diagnostics and puts forward some ideas that may facilitate the development of more advanced applications and devices in the area of personalized diagnostics. With this purpose, the potential exploitation of wireless power and actuation of sensors and biosensors using near field communication (NFC), the use of the screen as a light source for actuation and spectroscopic analysis, using the haptic module to enhance mass transport in micro volumes, and the use of magnetic sensors are discussed.

Imaging-based spectrometer-less optofluidic biosensors based on dielectric metasurfaces for detecting extracellular vesicles

Biosensors are indispensable tools for public, global, and personalized healthcare as they provide tests that can be used from early disease detection and treatment monitoring to preventing pandemics. We introduce single-wavelength imaging biosensors capable of reconstructing spectral shift information induced by biomarkers dynamically using an advanced data processing technique based on an optimal linear estimator. Our method achieves superior sensitivity without wavelength scanning or spectroscopy instruments. We engineered diatomic dielectric metasurfaces supporting bound states in the continuum that allows high-quality resonances with accessible near-fields by in-plane symmetry breaking. The large-area metasurface chips are configured as microarrays and integrated with microfluidics on an imaging platform for real-time detection of breast cancer extracellular vesicles encompassing exosomes. The optofluidic system has high sensing performance with nearly 70 1/RIU figure-of-merit enabling detection of on average 0.41 nanoparticle/µm2 and real-time measurements of extracellular vesicles binding from down to 204 femtomolar solutions. Our biosensors provide the robustness of spectrometric approaches while substituting complex instrumentation with a single-wavelength light source and a complementary-metal-oxide-semiconductor camera, paving the way toward miniaturized devices for point-of-care diagnostics.

Emerging point-of-care technologies for anemia detection

Anemia, characterized by low blood hemoglobin level, affects about 25% of the world's population with the heaviest burden borne by women and children. Anemia leads to impaired cognitive development in children, as well as high morbidity and early mortality among sufferers. Anemia can be caused by nutritional deficiencies, oncologic treatments and diseases, and infections such as malaria, as well as inherited hemoglobin or red cell disorders. Effective treatments are available for anemia upon early detection and the treatment method is highly dependent on the cause of anemia. There is a need for point-of-care (POC) screening, early diagnosis, and monitoring of anemia, which is currently not widely accessible due to technical challenges and cost, especially in low- and middle-income countries where anemia is most prevalent. This review first introduces the evolution of anemia detection methods followed by their implementation in current commercially available POC anemia diagnostic devices. Then, emerging POC anemia detection technologies leveraging new methods are reviewed. Finally, we highlight the future trends of integrating anemia detection with the diagnosis of relevant underlying disorders to accurately identify specific root causes and to facilitate personalized treatment and care.

Usability of Rapid Cholera Detection Device (OmniVis) for Water Quality Workers in Bangladesh: Iterative Convergent Mixed Methods Study

BACKGROUND

Cholera poses a significant global health burden. In Bangladesh, cholera is endemic and causes more than 100,000 cases each year. Established environmental reservoirs leave millions at risk of infection through the consumption of contaminated water. The Global Task Force for Cholera Control has called for increased environmental surveillance to detect contaminated water sources prior to human infection in an effort to reduce cases and deaths. The OmniVis rapid cholera detection device uses loop-mediated isothermal amplification and particle diffusometry detection methods integrated into a handheld hardware device that attaches to an iPhone 6 to identify and map contaminated water sources.

OBJECTIVE

The aim of this study was to evaluate the usability of the OmniVis device with targeted end users to advance the iterative prototyping process and ultimately design a device that easily integrates into users' workflow.

METHODS

Water quality workers were trained to use the device and subsequently completed an independent device trial and usability questionnaire. Pretraining and posttraining knowledge assessments were administered to ensure training quality did not confound trial and questionnaire.

RESULTS

Device trials identified common user errors and device malfunctions including incorrect test kit insertion and device powering issues. We did not observe meaningful differences in user errors or device malfunctions accumulated per participant across demographic groups. Over 25 trials, the mean time to complete a test was 47 minutes, a significant reduction compared with laboratory protocols, which take approximately 3 days. Overall, participants found the device easy to use and expressed confidence and comfort in using the device independently.

CONCLUSIONS

These results are used to advance the iterative prototyping process of the OmniVis rapid cholera detection device so it can achieve user uptake, workflow integration, and scale to ultimately impact cholera control and elimination strategies. We hope this methodology will promote robust usability evaluations of rapid pathogen detection technologies in device development.

Recent trends in smartphone-based detection for biomedical applications: a review

Smartphone-based imaging devices (SIDs) have shown to be versatile and have a wide range of biomedical applications. With the increasing demand for high-quality medical services, technological interventions such as portable devices that can be used in remote and resource-less conditions and have an impact on quantity and quality of care. Additionally, smartphone-based devices have shown their application in the field of teleimaging, food technology, education, etc. Depending on the application and imaging capability required, the optical arrangement of the SID varies which enables them to be used in multiple setups like bright-field, fluorescence, dark-field, and multiple arrays with certain changes in their optics and illumination. This comprehensive review discusses the numerous applications and development of SIDs towards histopathological examination, detection of bacteria and viruses, food technology, and routine diagnosis. Smartphone-based devices are complemented with deep learning methods to further increase the efficiency of the devices. Graphical Abstract.

Applications of smartphone-based near-infrared (NIR) imaging, measurement, and spectroscopy technologies to point-of-care (POC) diagnostics

The role of point-of-care (POC) diagnostics is important in public health. With the support of smartphones, POC diagnostic technologies can be greatly improved. This opportunity has arisen from not only the large number and fast spread of cell-phones across the world but also their improved imaging/diagnostic functions. As a tool, the smartphone is regarded as part of a compact, portable, and low-cost system for real-time POC, even in areas with few resources. By combining near-infrared (NIR) imaging, measurement, and spectroscopy techniques, pathogens can be detected with high sensitivity. The whole process is rapid, accurate, and low-cost, and will set the future trend for POC diagnostics. In this review, the development of smartphone-based NIR fluorescent imaging technology was described, and the quality and potential of POC applications were discussed.

Aspects of Point-of-Care Diagnostics for Personalized Health Wellness

Advancements in analytical diagnostic systems for point-of-care (POC) application have gained considerable attention because of their rapid operation at the site required to manage severe diseases, even in a personalized manner. The POC diagnostic devices offer easy operation, fast analytical outcome, and affordable cost, which promote their advanced research and versatile adoptability. Keeping advantages in view, considerable efforts are being made to design and develop smart sensing components such as miniaturized transduction, interdigitated electrodes-based sensing chips, selective detection at low level, portable packaging, and sustainable durability to promote POC diagnostics according to the needs of patient care. Such effective diagnostics systems are in demand, which creates the challenge to make them more efficient in every aspect to generate a desired bio-informatic needed for better health access and management. Keeping advantages and scope in view, this mini review focuses on practical scenarios associated with miniaturized analytical diagnostic devices at POC application for targeted disease diagnostics smartly and efficiently. Moreover, advancements in technologies, such as smartphone-based operation, paper-based sensing assays, and lab-on-a-chip (LOC) which made POC more sensitive, informative, and suitable for major infectious disease diagnosis, are the main focus here. Besides, POC diagnostics based on automated patient sample integration with a sensing platform is continuously improving therapeutics interventions against specific infectious disease. This review also discussed challenges associated with state-of-the-art technology along with future research opportunities to design and develop next generation POC diagnostic systems needed to manage infectious diseases in a personalized manner.

Bead-based multiplex detection of dengue biomarkers in a portable imaging device

Dengue is one of the most rapidly spreading mosquito-borne viral diseases in the world. Differential diagnosis is a crucial step for the management of the disease and its epidemiology. Point-of-care testing of blood-borne dengue biomarkers provides an advantageous approach in many health care settings, and the ability to follow more than one biomarker at once could significantly improve the management of the disease. Bead-based multiplex technologies (suspension array) can measure multiple biomarker targets simultaneously by using recognition molecules immobilized on microsphere beads. The overarching objective of our work is to develop a portable detection device for the simultaneous measurement of multiple biomarkers important in dengue diagnosis, monitoring and treatment. Here, we present a bead-based assay for the detection of one of the four serotypes of dengue virus non-structural protein (DENV-NS1) as well as its cognate human IgG. In this system, the fluorescent microspheres containing the classification fluorophore and detection fluorophore are imaged through a microfluidic chip using an infinity-corrected microscope system. Calibration curves were plotted for median fluorescence intensity against known concentrations of DENV-NS1 protein and anti-NS1 human IgG. The limit of quantitation was 7.8 ng/mL and 15.6 ng/mL, respectively. The results of this study demonstrate the feasibility of the multiplex detection of dengue biomarkers and present its analytical performance parameters. The proposed imaging device holds potential for point-of-care testing of biomarkers on a highly portable system, and it may facilitate the diagnosis and prevention of dengue as well as other infectious diseases.

An aptamer-based magnetic flow cytometer using matched filtering

Facing unprecedented population-ageing, the management of noncommunicable diseases (NCDs) urgently needs a point-of-care (PoC) testing infrastructure. Magnetic flow cytometers are one such solution for rapid cancer cellular detection in a PoC setting. In this work, we report a giant magnetoresistive spin-valve (GMR SV) biosensor array with a multi-stripe sensor geometry and matched filtering to improve detection accuracy without compromising throughput. The carefully designed sensor geometry generates a characteristic signature when cells labeled with magnetic nanoparticles (MNPs) pass by thus enabling multi-parametric measurement like optical flow cytometers (FCMs). Enumeration and multi-parametric information were successfully measured across two decades of throughput (37 - 2730 cells/min). 10-μm polymer microspheres were used as a biomimetic model where MNPs and MNP-decorated polymer conjugates were flown over the GMR SV sensor array and detected with a signal-to-noise ratio (SNR) as low as 2.5 dB due to the processing gain afforded by the matched filtering. The performance was compared against optical observation, exhibiting a 92% detection efficiency. The system achieved a 95% counting accuracy for biomimetic models and 98% for aptamer-based pancreatic cancer cell detection. This system demonstrates the ability to perform reliable flow cytometry toward PoC diagnostics to benefit NCD control plans.

Rapid Characterization of Biomolecules' Thermal Stability in a Segmented Flow-Through Optofluidic Microsystem

Optofluidic devices combining optics and microfluidics have recently attracted attention for biomolecular analysis due to their high detection sensitivity. Here, we show a silicon chip with tubular microchannels buried inside the substrate featuring temperature gradient (∇T) along the microchannel. We set up an optical fluorescence system consisting of a power-modulated laser light source of 470 nm coupled to the microchannel serving as a light guide via optical fiber. Fluorescence was detected on the other side of the microchannel using a photomultiplier tube connected to an optical fiber via a fluorescein isothiocyanate filter. The PMT output was connected to a lock-in amplifier for signal processing. We performed a melting curve analysis of a short dsDNA - SYBR Green I complex with a known melting temperature (TM) in a flow-through configuration without gradient to verify the functionality of the proposed detection system. We then used the segmented flow configuration and measured the fluorescence amplitude of a droplet exposed to ∇T of ≈ 2.31 °C mm-1, determining the heat transfer time as ≈ 554 ms. The proposed platform can be used as a fast and cost-effective system for performing either MCA of dsDNAs or for measuring protein unfolding for drug-screening applications.

A Nut-and-Bolt Microfluidic Mixing System for the Rapid Labeling of Immune Cells with Antibodies

A nut-and-bolt microfluidic system was previously developed for a point-of-care (POC) human immunodeficiency virus (HIV) test and was able to acquire images of CD4 (cluster of differentiation 4) + T-lymphocytes in a sample drop of blood followed by image analysis. However, as the system was not fully integrated with a sample reaction module, the mixing of the sample with the antibody reagent was carried out manually. To achieve a rapid reaction with a reduced amount of costly reagent in a POC diagnostic system, an efficient sample mixing function must be implemented. Here, we propose a novel method to drastically accelerate the process of sample mixing and increase the reaction rate in the nut-and-bolt microfluidic system, where the sample is mixed with the reagent in a reaction chamber formed by connecting a nut with a bolt-like sample cartridge. The mixing is facilitated by rotating the sample cartridge bidirectionally using a DC motor, which agitates the sample in a chaotic manner. A microbead complex formed by the avidin–biotin interaction was used as a model reaction system to examine the feasibility of our mixing module. We found that the reaction time for the avidin–biotin binding by mixing was 7.5 times shorter than in the incubation method, achieving a reaction efficiency of over 95%. The performance of our mixing system was further demonstrated by measuring the concentration of CD4 cells labeled with a fluorescent antibody in the blood sample. The antigen–antibody reaction mixing was faster by a factor of 20, reaching a reaction efficiency comparable to the conventional incubation method.

A smartphone-based biomedical sensory system

Disease diagnostics, food safety monitoring and environmental quality monitoring are the key means to safeguard human health. However, conventional detection devices for health care are costly, bulky and complex, restricting their applications in resource-limited areas of the world. With the rapid development of biosensors and the popularization of smartphones, smartphone-based sensing systems have emerged as novel detection devices that combine the sensitivity of biosensors and diverse functions of smartphones to provide a rapid, low-cost and convenient detection method. In these systems, a smartphone is used as a microscope to observe and count cells, as a camera to record fluorescence images, as an analytical platform to analyze experimental data, and as an effective tool to connect detection devices and online doctors. These systems are widely used for cell analysis, biochemical analysis, immunoassays, and molecular diagnosis, which are applied in the fields of disease diagnostics, food safety monitoring and environmental quality monitoring. Therefore, we discuss four types of smartphone-based sensing systems in this review paper, specifically in terms of the structure, performance and efficiency of these systems. Finally, we give some suggestions for improvement and future prospective trends.

Recent progress, challenges, and prospects of fully integrated mobile and wearable point-of-care testing systems for self-testing

The rapid growth of research in the areas of chemical and biochemical sensors, lab-on-a-chip, mobile technology, and wearable electronics offers an unprecedented opportunity in the development of mobile and wearable point-of-care testing (POCT) systems for self-testing. Successful implementation of such POCT technologies leads to minimal user intervention during operation to reduce user errors; user-friendly, easy-to-use and simple detection platforms; high diagnostic sensitivity and specificity; immediate clinical assessment; and low manufacturing and consumables costs. In this review, we discuss recent developments in the field of highly integrated mobile and wearable POCT systems. In particular, aspects of sample handling platforms, recognition elements and sensing methods, and new materials for signal transducers and powering devices for integration into mobile or wearable POCT systems will be highlighted. We also summarize current challenges and future prospects for providing personal healthcare with sample-in result-out mobile and wearable POCT.

Label-Free Leukemia Monitoring by Computer Vision

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. While there are a number of well‐recognized prognostic biomarkers at diagnosis, the most powerful independent prognostic factor is the response of the leukemia to induction chemotherapy (Campana and Pui: Blood 129 (2017) 1913–1918). Given the potential for machine learning to improve precision medicine, we tested its capacity to monitor disease in children undergoing ALL treatment. Diagnostic and on‐treatment bone marrow samples were labeled with an ALL‐discriminating antibody combination and analyzed by imaging flow cytometry. Ignoring the fluorescent markers and using only features extracted from bright‐field and dark‐field cell images, a deep learning model was able to identify ALL cells at an accuracy of >88%. This antibody‐free, single cell method is cheap, quick, and could be adapted to a simple, laser‐free cytometer to allow automated, point‐of‐care testing to detect slow early responders. Adaptation to other types of leukemia is feasible, which would revolutionize residual disease monitoring. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Smartphone Biosensor System with Multi-Testing Unit Based on Localized Surface Plasmon Resonance Integrated with Microfluidics Chip

Detecting biomarkers is an efficient method to diagnose and monitor patients’ stages. For more accurate diagnoses, continuously detecting and monitoring multiple biomarkers are needed. To achieve point-of-care testing (POCT) of multiple biomarkers, a smartphone biosensor system with the multi-testing-unit (SBSM) based on localized surface plasmon resonance (LSPR) integrated multi-channel microfluidics was presented. The SBSM could simultaneously record nine sensor units to achieve the detection of multiple biomarkers. Additional 72 sensor units were fabricated for further verification. Well-designed modularized attachments consist of a light source, lenses, a grating, a case, and a smartphone shell. The attachments can be well assembled and attached to a smartphone. The sensitivity of the SBSM was 161.0 nm/RIU, and the limit of detection (LoD) reached 4.2 U/mL for CA125 and 0.87 U/mL for CA15-3 through several clinical serum specimens testing on the SBSM. The testing results indicated that the SBSM was a useful tool for detecting multi-biomarkers. Comparing with the enzyme-linked immunosorbent assays (ELISA) results, the results from the SBSM were correlated and reliable. Meanwhile, the SBSM was convenient to operate without much professional skill. Therefore, the SBSM could become useful equipment for point-of-care testing due to its small size, multi-testing unit, usability, and customizable design.

A Smartphone-based Diffusometric Immunoassay for Detecting C-Reactive Protein

In this study, we developed a portable smartphone-based diffusometry for analyzing the C-reactive protein (CRP) concentration. An optimized fluorescence microscopic add-on system for a smartphone was used to image the 300 nm fluorescent beads. Sequential nanobead images were recorded for a period and the image data were used for fluorescence correlation spectrometric (FCS) analysis. Through the analysis, the nanobeads' diffusion coefficient was obtained. Further, the diffusion coefficients of the anti-CRP-coated nanobeads, which were suspended in the samples with various CRP concentrations, were estimated using smartphone-based diffusometry. After 10 min of reaction, the anti-CRP-coated nanobeads in a higher CRP concentration solution led to a lower diffusion coefficient. Based on the experiments, a linear sensing range of 1~8 µg/mL was found.

Compact and Filter-Free Luminescence Biosensor for Mobile in Vitro Diagnoses

We report a sensitive and versatile biosensing approach, LUCID (luminescence compact in vitro diagnostics), for quantitative molecular and cellular analyses. LUCID uses upconversion nanoparticles (UCNPs) as luminescent reporters in mutually exclusive photoexcitation and read-out sequences implemented on a smartphone. The strategy improves imaging signal-to-noise ratios, eliminating interference from excitation sources and minimizing autofluorescence, and thus enables filterless imaging. Here we developed a miniaturized detection system and optimized UCNPs for the system and biological applications. Nanoparticle luminescence lifetime was extended by controlling particle structure and composition. When tested with a range of biological targets, LUCID achieved high detection sensitivity (0.5 pM for protein and 0.1 pM for nucleic acids), differentiated bacterial samples, and allowed profiling of cells. In proof-of-concept clinical use, LUCID demonstrated effective screening of cancer cells in cervical brushing specimens, identifying patients at high risk for malignancy. These results suggest that LUCID could serve as a broadly applicable and inexpensive diagnostic platform.

Mobile imaging platform for digital influenza virus counting

Droplet-based digital bioassays enable highly sensitive and quantitative analysis of biomolecules, and are thought to be suitable for point-of-care diagnosis. However, digital bioassays generally require fluorescence microscopy for detection, which is too large for point-of-care testing. Here, we developed a simple smartphone-based mobile imaging platform for digital bioassays. The size of the mobile imaging platform was 23 × 10 × 7 cm (length × width × height). With this platform, a digital enzyme assay of bovine alkaline phosphatase was successfully completed. Digital influenza virus counting-based on a fluorogenic assay for neuraminidase activity of the virus-was also demonstrated. Distinct fluorescence spots derived from single virus particles were observed with the mobile imaging platform. The number of detected fluorescence spots showed good linearity against the virus titer, suggesting that high sensitivity and quantification were achieved, although the imaging with the mobile platform detected 60% of influenza virus particles that were identified with conventional fluorescence microscopy. The lower detection efficiency is due to its relatively lower signal-to-noise ratio than that found with conventional microscopes, and unavoidable intrinsic heterogeneity of neuraminidase activity among virus particles. Digital influenza virus counting with the mobile imaging platform still showed 100 times greater sensitivity than that with a commercial rapid influenza test kit. Virus detection of clinical samples was also successfully demonstrated, suggesting the potential to realize a highly sensitive point-of-care system for influenza virus detection with smartphones.

Colour compound lenses for a portable fluorescence microscope

In this article, we demonstrated a handheld smartphone fluorescence microscope (HSFM) that integrates dual-functional polymer lenses with a smartphone. The HSFM consists of a smartphone, a field-portable illumination source, and a dual-functional polymer lens that performs both optical imaging and filtering. Therefore, compared with the existing smartphone fluorescence microscope, the HSFM does not need any additional optical filters. Although fluorescence imaging has traditionally played an indispensable role in biomedical and clinical applications due to its high specificity and sensitivity for detecting cells, proteins, DNAs/RNAs, etc., the bulky elements of conventional fluorescence microscopes make them inconvenient for use in point-of-care diagnosis. The HSFM demonstrated in this article solves this problem by providing a multifunctional, miniature, small-form-factor fluorescence module. This multifunctional fluorescence module can be seamlessly attached to any smartphone camera for both bright-field and fluorescence imaging at cellular-scale resolutions without the use of additional bulky lenses/filters; in fact, the HSFM achieves magnification and light filtration using a single lens. Cell and tissue observation, cell counting, plasmid transfection evaluation, and superoxide production analysis were performed using this device. Notably, this lens system has the unique capability of functioning with numerous smartphones, irrespective of the smartphone model and the camera technology housed within each device. As such, this HSFM has the potential to pave the way for real-time point-of-care diagnosis and opens up countless possibilities for personalized medicine.

Electrochromic, Closed-Bipolar Electrodes Employing Aptamer-Based Recognition for Direct Colorimetric Sensing Visualization

In this paper, we adapt the electrochemical, aptamer-based (E-AB) sensor platform to develop colorimetric aptamer-based sensors using a closed-bipolar electrode (C-BPE) system. The C-BPE E-AB sensors provide quantitative detection of target molecules based on the rate of color change of an electrochromic Prussian blue (PB) thin-film indicator electrode. The C-BPE cathode, or sensing electrode, is modified with a redox-labeled aptamer that binds to a specific target. More specifically, we employed sequences specific for adenosine triphosphate (ATP) and tobramycin as test-bed targets because these sequences are well vetted. The C-BPE anode, or indicator electrode, was coated with an electrochromic thin film comprising Prussian white (PW) that, when reduced to PB, is accompanied by a corresponding color change used for analytical detection. The rate of color change from PW to PB is facilitated by a potassium ferricyanide-catalyzed oxidation of leucomethylene blue (LB) to methylene blue (MB), the redox label conjugated to the aptamer on the sensing electrode. We demonstrate that the rate of color change is quantitatively related to the concentration of target analyte, which provides a means for naked eye determination. When combined with smartphone-based colorimetric detection, these C-BPE E-AB sensors present a user-friendly alternative to traditional E-AB sensors that rely on voltammetric analysis and a potentiostat, opening up the possibility of point-of-use applications.

Electronic profiling of membrane antigen expression via immunomagnetic cell manipulation

Membrane antigens control cell function by regulating biochemical interactions and hence are routinely used as diagnostic and prognostic targets in biomedicine. Fluorescent labeling and subsequent optical interrogation of cell membrane antigens, while highly effective, limit expression profiling to centralized facilities that can afford and operate complex instrumentation. Here, we introduce a cytometry technique that computes surface expression of immunomagnetically labeled cells by electrically tracking their trajectory under a magnetic field gradient on a microfluidic chip with a throughput of >500 cells per min. In addition to enabling the creation of a frugal cytometry platform, this immunomagnetic cell manipulation-based measurement approach allows direct expression profiling of target subpopulations from non-purified samples. We applied our technology to measure epithelial cell adhesion molecule expression on human breast cancer cells. Once calibrated, surface expression and size measurements match remarkably well with fluorescence-based measurements from a commercial flow cytometer. Quantitative measurements of biochemical and biophysical cell characteristics with a disposable cytometer have the potential to impact point of care testing of clinical samples particularly in resource limited settings.

Handheld Microflow Cytometer Based on a Motorized Smart Pipette, a Microfluidic Cell Concentrator, and a Miniaturized Fluorescence Microscope

Miniaturizing flow cytometry requires a comprehensive approach to redesigning the conventional fluidic and optical systems to have a small footprint and simple usage and to enable rapid cell analysis. Microfluidic methods have addressed some challenges in limiting the realization of microflow cytometry, but most microfluidics-based flow cytometry techniques still rely on bulky equipment (e.g., high-precision syringe pumps and bench-top microscopes). Here, we describe a comprehensive approach that achieves high-throughput white blood cell (WBC) counting in a portable and handheld manner, thereby allowing the complete miniaturization of flow cytometry. Our approach integrates three major components: a motorized smart pipette for accurate volume metering and controllable liquid pumping, a microfluidic cell concentrator for target cell enrichment, and a miniaturized fluorescence microscope for portable flow cytometric analysis. We first validated the capability of each component by precisely metering various fluid samples and controlling flow rates in a range from 219.5 to 840.5 μL/min, achieving high sample-volume reduction via on-chip WBC enrichment, and successfully counting single WBCs flowing through a region of interrogation. We synergistically combined the three major components to create a handheld, integrated microflow cytometer and operated it with a simple protocol of drawing up a blood sample via pipetting and injecting the sample into the microfluidic concentrator by powering the motorized smart pipette. We then demonstrated the utility of the microflow cytometer as a quality control means for leukoreduced blood products, quantitatively analyzing residual WBCs (rWBCs) in blood samples present at concentrations as low as 0.1 rWBCs/μL. These portable, controllable, high-throughput, and quantitative microflow cytometric technologies provide promising ways of miniaturizing flow cytometry.

Micro-optical Components for Bioimaging on Tissues, Cells and Subcellular Structures

Bioimaging generally indicates imaging techniques that acquire biological information from living forms. Among different imaging techniques, optical microscopy plays a predominant role in observing tissues, cells and biomolecules. Along with the fast development of microtechnology, developing miniaturized and integrated optical imaging systems has become essential to provide new imaging solutions for point-of-care applications. In this review, we will introduce the basic micro-optical components and their fabrication technologies first, and further emphasize the development of integrated optical systems for in vitro and in vivo bioimaging, respectively. We will conclude by giving our perspectives on micro-optical components for bioimaging applications in the near future.

A microfluidic biosensor for online and sensitive detection of Salmonella typhimurium using fluorescence labeling and smartphone video processing

Early screening of foodborne pathogens is a key to ensure food safety. In this study, we developed a microfluidic biosensor for online and sensitive detection of Salmonella based on immunomagnetic separation, fluorescence labeling and smartphone video processing. First, the immune magnetic nanoparticles were used to specifically separate and efficiently concentrate the target bacteria and the magnetic bacteria were formed. Then, the magnetic bacteria were labeled with the immune fluorescent microspheres and the fluorescent bacteria were formed. Finally, the fluorescent bacteria were continuously injected into the microfluidic chip on the smartphone-based fluorescent microscopic system, and the fluorescent spots were online counted using the smartphone App based on inter-frame difference algorithm to obtain the amount of the target bacteria. Under the optimal conditions, this proposed biosensor was able to quantitatively detect Salmonella typhimurium ranging from 1.4 × 10² to 1.4 × 10⁶ CFU/mL, and its lower detection limit was 58 CFU/mL. This biosensor could be extended for detection of multiple foodborne pathogens using different fluorescent materials.