Engineering & Technologyarticle2026-10-05

Reframing decentralized diagnostics with a programmable multi-dimensional microfluidic system

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Abstract

Decentralized diagnostics are vital for infectious disease control, yet current point-of-care tools remain largely one-dimensional, failing to capture the multidimensional profiles required for precision management. Here, we show SID-WAVES (Smartphone-Integrated Diagnostics with Wax-encoded Amplified and Versatile Evaluation System), an intelligent, multimodal microfluidic platform. Integrating low-melting-point phase-change and dual-siphon valves with RPA–CRISPR/Cas12a nucleic acid detection and protein immunoassays, the platform enables automated, one-step, sample-to-answer operation via an AI-assisted smartphone readout that reduces operator-dependent variability. Spatial-temporal-signal encoding supports multiplexed, multi-sample, and multimodal analysis, achieving attomolar-level sensitivity (10−18 M) and >95% diagnostic accuracy across 225 clinical and self-collected molecular assays, demonstrating robust usability. For proteins, a triple-amplification strategy and hierarchical capture enhance sensitivity 125-fold, improving accuracy from 87.6% to 100% in 54 simulated samples. Functioning as a reconfigurable analytical framework where panels are changed by swapping targets and probes, this work helps mitigate the Sensitivity–Multiplexing–Accessibility trade-off, reframing decentralized diagnostics from single-target screening to multi-dimensional health profiling. Decentralized diagnostics has the potential to improve health equity as well as support a more rapid response to disease outbreaks. Here authors present SID-WAVES, a multimodal microfluidic platform which allows ‘sample-in, results-out’ detection of both nucleic acid and protein biomarkers.

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View paper (DOI)Open access versionOpenAlexNature CommunicationsPublished 2026-10-05

Authors: Tao Xu, Ying Zhang, Xin Tang, Hongguo Wei, Lingyan Kang, Qize Zhou, Shunji Li, Xudong Zhao, Jiashuo Li, Zimeng Zhang, Chao Wan, Yufei Zhang, Dongjuan Chen, Ye Tian, Bi-Feng Liu, Peng Chen

Institutions: Huazhong University of Science and Technology, Guangdong Medical College, Northeastern University, Wuhan National Laboratory for Optoelectronics