Promise and perils of paper-based point-of-care nucleic acid detection for endemic and pandemic pathogens

Two-phase Porous Media Flow Model Based on the Incompressible Navier-Stokes Equation

Two-phase porous media flow is important in many applications from drug delivery to groundwater diffusion and oil recovery and is of particular interest to biomedical diagnostic test developers using cellulose and nitrocellulose membranes with limited fluid sample volumes. This work presents a new two-phase porous media flow model based on the incompressible Navier-Stokes equation. The model aims to address the limitations of existing methods by incorporating a partial saturation distribution in porous media to account for limited fluid volumes. The basic parameters of the model are the pore size distribution and the contact angle. To validate the model, we solved five analytical solutions and compared them to corresponding experimental data. The experimentally measured penetration length data agreed with the model predictions, demonstrating model accuracy. Our findings suggest that this new two-phase porous media flow model can provide a valuable tool for researchers developing fluidic assays in paper and other porous media.

A Point-of-Care Nucleic Acid Quantification Method by Counting Light Spots Formed by LAMP Amplicons on a Paper Membrane

Nucleic acid quantification, allowing us to accurately know the copy number of target nucleic acids, is significant for diagnosis, food safety, agricultural production, and environmental protection. However, current digital quantification methods require expensive instruments or complicated microfluidic chips, making it difficult to popularize in the point-of-care detection. Paper is an inexpensive and readily available material. In this study, we propose a simple and cost-effective paper membrane-based digital loop-mediated isothermal amplification (LAMP) method for nucleic acid quantification. In the presence of DNA fluorescence dyes, the high background signals will cover up the amplicons-formed bright spots. To reduce the background fluorescence signals, a quencher-fluorophore duplex was introduced in LAMP primers to replace non-specific fluorescence dyes. After that, the amplicons-formed spots on the paper membrane can be observed; thus, the target DNA can be quantified by counting the spots. Take Vibrio parahaemolyticus DNA detection as an instance, a good linear relationship is obtained between the light spots and the copy numbers of DNA. The paper membrane-based digital LAMP detection can detect 100 copies target DNA per reaction within 30 min. Overall, the proposed nucleic acid quantification method has the advantages of a simple workflow, short sample-in and answer-out time, low cost, and high signal-to-noise, which is promising for application in resourced limited areas.

Machine learning-assisted image label-free smartphone platform for rapid segmentation and robust multi-urinalysis

This study presents a groundbreaking approach for the early detection of chronic kidney disease (CKD) and other urological disorders through an image-label-free, multi-dipstick identification method, eliminating the need for complex machinery, label libraries, or preset coordinates. Our research successfully identified reaction pads on 187 multi-dipsticks, each with 11 pads, leveraging machine learning algorithms trained on human urine data. This technique aims to surpass traditional colourimetric methods and concentration-colour curve fitting, offering more robust and precise community screening and home monitoring capabilities. The developed algorithms enhance the generalizability of machine learning models by extracting primary colours and correcting urine colours on each reaction pad. This method's cost-effectiveness and portability are significant, as it requires no additional equipment beyond a standard smartphone. The system's performance rivals professional medical equipment without auxiliary lighting or flash under regular indoor light conditions, effectively managing false positives and negatives across various categories with remarkable accuracy. In a controlled experimental setting, we found that random forest algorithms, based on a Bagging strategy and applied in the HSV colour space, showed optimal results in smartphone-assisted urinalysis. This study also introduces a novel urine colour correction method, significantly improving machine learning model performance. Additionally, ISO parameters were identified as crucial factors influencing the accuracy of smartphone-based urinalysis in the absence of additional lighting or optical configurations, highlighting the potential of this technology in low-resource settings.

Lateral Flow Biosensor for On-Site Multiplex Detection of Viruses Based on One-Step Reverse Transcription and Strand Displacement Amplification

Respiratory pathogens pose a huge threat to public health, especially the highly mutant RNA viruses. Therefore, reliable, on-site, rapid diagnosis of such pathogens is an urgent need. Traditional assays such as nucleic acid amplification tests (NAATs) have good sensitivity and specificity, but these assays require complex sample pre-treatment and a long test time. Herein, we present an on-site biosensor for rapid and multiplex detection of RNA pathogens. Samples with viruses are first lysed in a lysis buffer containing carrier RNA to release the target RNAs. Then, the lysate is used for amplification by one-step reverse transcription and single-direction isothermal strand displacement amplification (SDA). The yield single-strand DNAs (ssDNAs) are visually detected by a lateral flow biosensor. With a secondary signal amplification system, as low as 20 copies/μL of virus can be detected in this study. This assay avoids the process of nucleic acid purification, making it equipment-independent and easier to operate, so it is more suitable for on-site molecular diagnostic applications.

UbiNAAT: a multiplexed point-of-care nucleic acid diagnostic platform for rapid at-home pathogen detection

The COVID-19 pandemic increased demands for respiratory disease testing to facilitate treatment and limit transmission, demonstrating in the process that most existing test options were too complex and expensive to perform in point-of-care or home scenarios. Lab-based molecular techniques can detect viral RNA in respiratory illnesses but are expensive and require trained personnel, while affordable antigen-based home tests lack sensitivity for early detection in newly infected or asymptomatic individuals. The few home RNA detection tests deployed were prohibitively expensive. Here, we demonstrate a point-of-care, paper-based rapid analysis device that simultaneously detects multiple viral RNAs; it is demonstrated on two common respiratory viruses (COVID-19 and influenza A) spiked onto a commercial nasal swab. The automated device requires no sample preparation by the user after insertion of the swab, minimizing user operation steps. We incorporated lyophilized amplification reagents immobilized in a porous matrix, a novel thermally actuated valve for multiplexed fluidic control, a printed circuit board that performs on-device lysis and amplification within a cell-phone-sized disposable device. Reverse transcription loop-mediated isothermal amplification (RT-LAMP) products are visualized via fluorescent dyes using a modified cell phone, resulting in detection of as few as 104 viral copies per swab across both pathogens within 30 minutes. This integrated platform could be commercialized in a form that would be inexpensive, portable, and sensitive; it can readily be multiplexed to detect as many as 8 different RNA or DNA sequences, and adapted to any desired RNA or DNA detection assays.

Evolution of the Probe-Based Loop-Mediated Isothermal Amplification (LAMP) Assays in Pathogen Detection

Loop-mediated isothermal amplification (LAMP), as the rank one alternative to a polymerase chain reaction (PCR), has been widely applied in point-of-care testing (POCT) due to its rapid, simple, and cost-effective characteristics. However, it is difficult to achieve real-time monitoring and multiplex detection with the traditional LAMP method. In addition, these approaches that use turbidimetry, sequence-independent intercalating dyes, or pH-sensitive indicators to indirectly reflect amplification can result in false-positive results if non-specific amplification occurs. To fulfill the needs of specific target detection and one-pot multiplex detection, a variety of probe-based LAMP assays have been developed. This review focuses on the principles of these assays, summarizes their applications in pathogen detection, and discusses their features and advantages over the traditional LAMP methods.