Reframing decentralized diagnostics with a programmable multi-dimensional microfluidic system

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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Publication Details

Journal
Nature Communications
Published
2026-10-05
DOI
https://doi.org/10.1038/s41467-026-77744-1
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
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article

Reframing decentralized diagnostics with a programmable multi-dimensional microfluidic system

Tao Xu, Peng Chen, Chao Wan, Qize Zhou et al.
Nature Communications
Biosensors and Analytical Detection
article

Reframing decentralized diagnostics with a programmable multi-dimensional microfluidic system

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

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.

Nature Communications
Guangdong Medical College (CN), Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN), Northeastern University (CN)
Good health and well-being
Openalex Percentile: Top 36%
Biosensors and Analytical Detection
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