No abstract

This work introduces a low-cost adhesive tape combined with a hydroxylamine/polyvinyl alcohol/polyethylene oxide (HA/PVA/PEO) blend film to fabricate novel devices for improving sensitivity of gold nanoparticle (AuNP)-based lateral flow immunoassays (LFIAs) via two platforms: (1) LFIA device with integrated gold enhancement and (2) LFIA device with two independent sample inlets. The detection of ferritin has been used for proof-of-concept. The adhesive tape inserted in the devices assists to separate two solutions independently flowing from two different inlets toward a nitrocellulose membrane. On-device gold enhancement was achieved by the enlargement of AuNPs via the catalytic reaction of KAuCl4 and HA using the HA/PVA/PEO blend film easily prepared via a solution-casting technique, which could delay the flow of HA released from the film for 180s and improve storage stability of the device. Under optimal conditions evaluated by naked eyes, the gold enhancement (LOD = 0.5 ng/mL) and double-sample inlet (LOD = 2 ng/mL) devices exhibited 20-fold and fivefold higher sensitivity respectively than a conventional device, verifying the sensitivity improvement. Furthermore, the proposed device was successfully detected ferritin in human serum samples within 10 min via naked-eye observation, exhibiting rapidity and simplicity of use, and the capability to perform on-site assays.

We report on the development of an electrochemical sensor platform based on modi ed cotton bers for the non-enzymatic detection of uric acid (UA), an important biomarker for gout disease. To create the exible electrode, a cotton thread was coated with carbon ink followed by the electrodeposition of AuNPs.Then, differential pulse voltammetry (DPV) was used to evaluate the sensor performances, and a linear detection range between 10 µM and 5.0 mM of uric acid was obtained. The sensor has a low detection limit of 0.12 µM, which is optimal for use in the patients suffering from gout disease which commonly experience concentrations of uric acid in urine higher than 4.46 mM. Furthermore, we found that the detection sensitivity of the platform was not affected by the presence of other physiological compounds present in human urine. The described platform has the potential for integration in a diaper hence enabling rapid detection and screening for gout disease.

Background: The demand for point-of-care testing (POCT) devices has rapidly grown since they offer immediate test results with ease of use, makingthem suitable for home self-testing patients and caretakers. However, the POCT development has faced the challenges of increased cost and limited resources. Therefore, the paper substrate as a low-cost material has been employed to develop a cost-effective POCT device, known as “Microfluidic paper-based analytical devices (μPADs)”. This device is gaining attention as a promising tool for medicinal diagnostic applications owing to its unique features of simple fabrication, low cost, enabling manipulation flow (capillarydriven flow), the ability to store reagents, and accommodating multistep assay requirements. Objective: This review comprehensively examines the fabrication methods and device designs (2D/3D configuration) and their advantages and disadvantages, focusing on updated μPADs applications for motif identification. Methods: The evolution of paper-based devices, starting from the traditional devices of dipstick and lateral flow assay (LFA) with μPADs, has been described. Patterned structure fabrication of each technique has been compared among the equipment used, benefits, and drawbacks. Microfluidic device designs, including 2D and 3D configurations, have been introduced as well as their modifications. Various designs of μPADs have been integrated with many powerful detection methods such as colorimetry, electrochemistry, fluorescence, chemiluminescence, electrochemiluminescence, and SER-based sensors for medicinal diagnosis applications. Conclusion: The μPADs potential to deal with commercialization in terms of the state-of-the-art of μPADs in medicinal diagnosis has been discussed. A great prototype, which is currently in a reallife application breakthrough, has been updated.

No abstract