Smartphone-based Detection Platform Research Articles

Automatic offline-capable smartphone paper-based microfluidic device for efficient biomarker detection of Alzheimer's disease

BackgroundAlzheimer's disease (AD) is a prevalent neurodegenerative disease with no effective treatment. Efficient and rapid detection plays a crucial role in mitigating and managing AD progression. Deep learning-assisted smartphone-based microfluidic paper analysis devices (μPADs) offer the advantages of low cost, good sensitivity, and rapid detection, providing a strategic pathway to address large-scale disease screening in resource-limited areas. However, existing smartphone-based detection platforms usually rely on large devices or cloud servers for data transfer and processing. Additionally, the implementation of automated colorimetric enzyme-linked immunoassay (c-ELISA) on μPADs can further facilitate the realization of smartphone μPADs platforms for efficient disease detection. ResultsThis paper introduces a new deep learning-assisted offline smartphone platform for early AD screening, offering rapid disease detection in low-resource areas. The proposed platform features a simple mechanical rotating structure controlled by a smartphone, enabling fully automated c-ELISA on μPADs. Our platform successfully applied sandwich c-ELISA for detecting the β-amyloid peptide 1–42 (Aβ 1–42, a crucial AD biomarker) and demonstrated its efficacy in 38 artificial plasma samples (healthy: 19, unhealthy: 19, N = 6). Moreover, we employed the YOLOv5 deep learning model and achieved an impressive 97 % accuracy on a dataset of 1824 images, which is 10.16 % higher than the traditional method of curve-fitting results. The trained YOLOv5 model was seamlessly integrated into the smartphone using the NCNN (Tencent's Neural Network Inference Framework), enabling deep learning-assisted offline detection. A user-friendly smartphone application was developed to control the entire process, realizing a streamlined “samples in, answers out” approach. SignificanceThis deep learning-assisted, low-cost, user-friendly, highly stable, and rapid-response automated offline smartphone-based detection platform represents a good advancement in point-of-care testing (POCT). Moreover, our platform provides a feasible approach for efficient AD detection by examining the level of Aβ 1–42, particularly in areas with low resources and limited communication infrastructure.

Dual-mode aptasensor based on a coumarin–benzothiazole fluorescent and colorimetric probe for label-free and visual detection of ochratoxin A

Ochratoxin A (OTA) is regarded as a harmful mycotoxin that severely influences human health by increasing the risk of diseases. Although conventional quantitative methods for OTA detection have been developed, there remain drawbacks of limited signal transduction, bulky instrument requirements, high cost, and sophisticated sample pretreatment. Herein, we successfully synthesize a coumarin-benzothiazole molecule named DR1 to construct a dual-mode aptasensor (DR1/OBA) by simultaneously producing fluorescent and colorimetric signals when binding to OTA binding aptamer (OBA). In fluorescent mode, the fluorescence of DR1/OBA will be switched off and provide rapid, label-free, and sensitive detection efficacies via the OTA competition. In colorimetric mode, the purple-color of DR1 tends to a blue-color state with a red-shifted absorbance by forming DR1/OBA. The blue-shifted absorbance will be observed with OTA competition and the purple-color state of DR1 can be recovered. Based on this unique phenomenon, a smartphone-based detection platform has been established to convert the color change into RGB values and realize the visual detection for spiked OTA quantification in real samples. As expected, the dual-mode aptasensor allows portable, reliable, sensitive, and visual detection for OTA in sophisticated scenarios. It will hold great potential in advancing research in mycotoxins and the development of aptamer-based biosensing.

A point-of-care detection platform for Escherichia coli O157:H7 by integration of smartphone and the structural colour of photonic microsphere

A smartphone-based sensitive, rapid, label-free and high-throughput detection platform for Escherichia coli O157:H7 was established. The specific recognition capability of this platform was dependent of the aptamer modified on the silica photonic microsphere (SPM), whose structural colour was utilized for the quantification of the target bacterium. Gold nanoparticles and silver staining technique were employed to improve the sensitivity of the detection platform. Such smartphone-based detection platform gave a wide linear detection range of 102 ∼ 108 CFU/mL with a low limit of detection (LOD) of 68 CFU/mL and high specificity for Escherichia coli O157:H7. Moreover, the recovery rates of the detection method were measured in the range of 99 ∼ 108% in the milk, pork and purified water samples. Furthermore, the developed detection platform did not require complex sample pretreatment and could be easily manipulated, displaying great application potential in the fields of food safety, environmental monitoring and disease diagnosis.

A smartphone-based platform for point-of-use determination of alkaline phosphatase as an indicator of water eutrophication.

A smartphone-based detection platform for the determination of alkaline phosphatase (ALP) is described. The method is based on the rational design of the stimulus-response of 7-methoxycoumarin-3-carboxylic acid (7-MC-3-COOH)-functionalized Eu-AMP infinite coordination polymer (ICP) nanoparticles. The blue fluorescence of 7-MC-3-COOH at 403nm was suppressed, while the red fluorescence of Eu3+ at 615nm was sensitized after the formation of 7-MC-3-COOH@Eu-AMP ICP. Upon exposure to ALP, the dephosphorylation of AMP resulted in the destruction of 7-MC-3-COOH@Eu-AMP ICP, and thereby, the blue fluorescence of 7-MC-3-COOH recovered; in the meantime, the sensitized red fluorescence was quenched. With the fluorescence intensity ratio F615/F430 as the signal readout, ALP can be detected within a concentration range 0.001 to 0.15UmL-1, and the limit of detection (LOD) was 0.00035UmL-1. Moreover, fluorescence color changes from red to blue could also be recognized by a portable device with the smartphone as a signal reader, and direct point-of-use testing (POUT) for ALP within a concentration range 0.005 to 0.7UmL-1 could be realized, with LOD of0.0015UmL-1. Endowed with high sensitivity and superior reliability, the assay enabled direct monitoring of P-related water eutrophication in a freshwater lake with ALP as an indicator. Graphical abstract A smartphone-based platform for point-of-use determination of alkaline phosphatase.

Surface lanthanide activator doping for constructing highly efficient energy transfer-based nanoprobes for the on-site monitoring of atmospheric sulfur dioxide.

The sensitive and on-site detection of sulfur dioxide (SO2) is in great demand in the fields of food safety and environmental protection. Here, we developed a novel upconversion nanoprobe based on the luminescence energy transfer mechanism for monitoring the atmospheric SO2 concentrations. The lanthanide emitters, Tm3+ ions, were optimized to be doped on the surface layer of the upconversion nanoparticles to improve their energy transfer efficiency by minimizing the distance between the emitters and the surface quencher, a cyanine dye. As a proof-of-concept, the optimal nanoprobe was utilized to detect SO2 water derivatives, bisulfite ions, exhibiting a linear luminescence increase in the range of 1 nM to 10 nM. Furthermore, we assembled the cyanine-modified upconversion nanoparticles onto a test paper, and used a smartphone-based detection platform to achieve portable and visual detection of SO2. The test paper showed a strong luminescence stability, homogeneity and good anti-interference. The limit of detection for SO2 gas was found to be 1 ng L-1. This novel upconversion test paper was also demonstrated to directly monitor the concentration of SO2 gas in atmosphere.

A rapid, maskless 3D prototyping for fabrication of capillary circuits: Toward urinary protein detection.

Proteinuria is an established risk marker for progressive renal function loss and patients would significantly benefit from a point-of-care testing. Although extensive work has been done to develop the microfluidic devices for the detection of urinary protein, they need the complicated operation and bulky peripherals. Here, we present a rapid, maskless 3D prototyping for fabrication of capillary fluidic circuits using laser engraving. The capillary circuits can be fabricated in a short amount of time (<10 min) without the requirements of clean-room facilities and photomasks. The advanced capillary components (e.g., trigger valves, retention valves and retention bursting valves) were fabricated, enabling the sequential liquid delivery and sample-reagent mixing. With the integration of smartphone-based detection platform, the microfluidic device can quantify the urinary protein via a colorimetric analysis. By eliminating the bulky and expensive equipment, this smartphone-based detection platform is portable for on-site quantitative detection.

Smartphone based bacterial detection using biofunctionalized fluorescent nanoparticles

We are describing immunochromatographic test strips with smart phone-based fluorescence readout. They are intended for use in the detection of the foodborne bacterial pathogens Salmonella spp. and Escherichia coli O157. Silica nanoparticles (SiNPs) were doped with FITC and Ru(bpy), conjugated to the respective antibodies, and then used in a conventional lateral flow immunoassay (LFIA). Fluorescence was recorded by inserting the nitrocellulose strip into a smart phone-based fluorimeter consisting of a light weight (40 g) optical module containing an LED light source, a fluorescence filter set and a lens attached to the integrated camera of the cell phone in order to acquire high-resolution fluorescence images. The images were analysed by exploiting the quick image processing application of the cell phone and enable the detection of pathogens within few minutes. This LFIA is capable of detecting pathogens in concentrations as low as 105 cfu mL−1 directly from test samples without pre-enrichment. The detection is one order of magnitude better compared to gold nanoparticle-based LFIAs under similar condition. The successful combination of fluorescent nanoparticle-based pathogen detection by LFIAs with a smart phone-based detection platform has resulted in a portable device with improved diagnosis features and having potential application in diagnostics and environmental monitoring.