The ability to design nanostructures with arbitrary shapes and controllable motions has made DNA nanomaterials used widely to construct diverse nanomachines with various structures and functions. The DNA nanostructures exhibit excellent properties, including programmability, stability, biocompatibility, and can be modified with different functional groups. Among these nanoscale architectures, DNA walker is one of the most popular nanodevices with ingenious design and flexible function. In the past several years, DNA walkers have made amazing progress ranging from structural design to biological applications including constructing biosensors for the detection of cancer‐associated biomarkers. In this review, the key driving forces of DNA walkers are first summarized. Then, the DNA walkers with different numbers of legs are introduced. Furthermore, the biosensing applications of DNA walkers including the detection‐ of nucleic acids, proteins, ions, and bacteria are summarized. Finally, the new frontiers and opportunities for developing DNA walker‐based biosensors are discussed.

DNA Walkers for Biosensing Development

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. 

/pdf/smartphone-based-platforms-implementing-microfluidic-2grh62qi.pdf

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

Hybrid microfluidic systems that are composed of multiple different types of substrates have been recognized as a versatile and superior platform, which can draw benefits from different substrates while avoiding their limitations. This review article introduces the recent innovations of different types of low-cost hybrid microfluidic devices, particularly focusing on cost-effective polymer- and paper-based hybrid microfluidic devices. In this article, the fabrication of these hybrid microfluidic devices is briefly described and summarized. We then highlight various hybrid microfluidic systems, including polydimethylsiloxane (PDMS)-based, thermoplastic-based, paper/polymer hybrid systems, as well as other emerging hybrid systems (such as thread-based). The special benefits of using these hybrid systems have been summarized accordingly. A broad range of biological and biomedical applications using these hybrid microfluidic devices are discussed in detail, including nucleic acid analysis, protein analysis, cellular analysis, 3D cell culture, organ-on-a-chip, and tissue engineering. The perspective trends of hybrid microfluidic systems involving the improvement of fabrication techniques and broader applications are also discussed at the end of the review.

Recent innovations in cost-effective polymer and paper hybrid microfluidic devices.

Naked-eye based point-of-care detection of E.coli O157: H7 by a signal-amplified microfluidic aptasensor.

Emerging and reemerging infections present an ever-increasing challenge to global health. Here, we report a nanoparticle-enabled smartphone (NES) system for rapid and sensitive virus detection. The virus is captured on a microchip and labeled with specifically designed platinum nanoprobes to induce gas bubble formation in the presence of hydrogen peroxide. The formed bubbles are controlled to make distinct visual patterns, allowing simple and sensitive virus detection using a convolutional neural network (CNN)–enabled smartphone system and without using any optical hardware smartphone attachment. We evaluated the developed CNN-NES for testing viruses such as hepatitis B virus (HBV), HCV, and Zika virus (ZIKV). The CNN-NES was tested with 134 ZIKV- and HBV-spiked and ZIKV- and HCV-infected patient plasma/serum samples. The sensitivity of the system in qualitatively detecting viral-infected samples with a clinically relevant virus concentration threshold of 250 copies/ml was 98.97% with a confidence interval of 94.39 to 99.97%.

https://advances.sciencemag.org/content/advances/6/51/eabd5354.full.pdf

Virus detection using nanoparticles and deep neural network-enabled smartphone system.

Quantitating ultra-low concentrations of protein biomarkers is critical for early disease diagnosis and treatment. However, most current point-of-care (POC) assays are limited in sensitivity. Herein, we introduce an ultra-sensitive and facile microbubbling assay for the quantification of protein biomarkers with a digital-readout method that requires only a smartphone camera. We used machine learning to develop a smartphone application for automated image analysis to facilitate accurate and robust counting. Using this method, post-prostatectomy surveillance of prostate specific antigen (PSA) can be achieved with a detection limit (LOD) of 2.1 fm (0.060 pg mL-1 ), and early pregnancy detection using βhCG can be achieved with a of 0.034 mIU mL-1 (2.84 pg mL-1 ). This work provides the proof-of-principle of the microbubbling assay with a digital readout as an ultra-sensitive technology with minimal requirement for power and accessories, facilitating future POC applications.

Quantitation of Femtomolar‐Level Protein Biomarkers Using a Simple Microbubbling Digital Assay and Bright‐Field Smartphone Imaging

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Quantitation of Femtomolar‐Level Protein Biomarkers Using a Simple Microbubbling Digital Assay and Bright‐Field Smartphone Imaging