In this paper, digital quantitative detection of nucleic acids was achieved at the single-molecule level by chemical initiation of over one thousand sequence-specific, nanoliter isothermal amplification reactions in parallel. Digital polymerase chain reaction (digital PCR), a method used for quantification of nucleic acids, counts the presence or absence of amplification of individual molecules. However, it still requires temperature cycling, which is undesirable under resource-limited conditions. This makes isothermal methods for nucleic acid amplification, such as recombinase polymerase amplification (RPA), more attractive. A microfluidic digital RPA SlipChip is described here for simultaneous initiation of over one thousand nL-scale RPA reactions by adding a chemical initiator to each reaction compartment with a simple slipping step after instrument-free pipet loading. Two designs of the SlipChip, two-step slipping and one-step slipping, were validated using digital RPA. By using the digital RPA SlipChip, false-positive results from preinitiation of the RPA amplification reaction before incubation were eliminated. End point fluorescence readout was used for "yes or no" digital quantification. The performance of digital RPA in a SlipChip was validated by amplifying and counting single molecules of the target nucleic acid, methicillin-resistant Staphylococcus aureus (MRSA) genomic DNA. The digital RPA on SlipChip was also tolerant to fluctuations of the incubation temperature (37-42 °C), and its performance was comparable to digital PCR on the same SlipChip design. The digital RPA SlipChip provides a simple method to quantify nucleic acids without requiring thermal cycling or kinetic measurements, with potential applications in diagnostics and environmental monitoring under resource-limited settings. The ability to initiate thousands of chemical reactions in parallel on the nanoliter scale using solvent-resistant glass devices is likely to be useful for a broader range of applications.
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http://dx.doi.org/10.1021/ac200247e | DOI Listing |
Digit Health
January 2025
The University of Sydney, Camperdown, Australia.
Background: The investigation of digital information sources and technologies specifically used by men with prostate cancer is scarce. This study seeks to address current gaps in the literature by investigating prostate cancer-specific internet and technology use by men with prostate cancer and factors associated with this use.
Methods: Cross-sectional surveys were conducted in three Australian urology clinics (local in Sydney, Western Sydney and Murrumbidgee) in 2023.
Anal Chim Acta
February 2025
Institute of Microfluidic Chip Development in Biomedical Engineering, College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China. Electronic address:
Background: Digital recombinase polymerase amplification (dRPA) is an effective tool for the absolute quantification of nucleic acids and the detection of rare mutations. Due to the high viscosity or other physical properties of the reagent, this can compromise the accuracy and reproducibility of detection results, which limits the broader adoption and practical application of this technology. In this study, we developed an asymmetric contact angle digital isothermal detection (ACA-DID) chip and optimized the ACA-DID chip structure to achieve rapid digital recombinase polymerase amplification.
View Article and Find Full Text PDFiScience
December 2024
Key Laboratory of Clinical Laboratory Diagnostics (Ministry of Education), School of Laboratory Medicine, Chongqing Medical University, 1 Xueyuan Road, Chongqing 400016, China.
Small Methods
January 2025
College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang Province, 310027, China.
Stud Health Technol Inform
November 2024
Department of Medical Rehabilitation, University of Medicine and Pharmacy "Victor Babes", Timişoara, Romania.
This paper proposes to create an Robotic Process Automation style application that can digitalize and extract data from handwritten medical forms. The RPA robot uses OpenAI ChatGPT4o model to extract handwritten medical data and transform it into typed data. The handwritten data is transcribed correctly at a rate of 100%.
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