Nanoheterojunction-Based Self-Powered Biosensor Integrated with Smartphones for Early Cancer Detection.

PAPER pubmed Advanced healthcare materials 2026 Engineering / measurement Effect: unclear Evidence: Insufficient

Read original paper → DOI: 10.1002/adhm.202505453 PMID: 41703758 Evidence Lab

Abstract

Early diagnosis of cancer is critical for improving patient survival rates. As biomarkers closely associated with tumorigenesis, microRNAs (miRNAs) remain challenging to detect with sufficient sensitivity, simplicity, and portability. This study presents a self-powered, dual-readout electrothermal biosensing chip that integrates an enzyme-free catalytic hairpin assembly (CHA) amplification strategy with hierarchical SnO@MoS hollow spheres for highly sensitive and specific detection of microRNA-126 (miRNA-126). The target miRNA concentration is directly quantified via electrochemical signals, while a thermal transduction mechanism converts electrochemically generated intermediates into the photothermal agent Oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB). Both electrochemical and thermal signals are visualized in real time through a smartphone interface, enhancing detection reliability and interpretability. Compared with conventional single-mode electrochemical methods, this platform reduces cost and operational complexity through enzyme-free amplification, while dual-signal cross-validation improves accuracy. The energy-autonomous design eliminates the need for an external power supply, enabling portable, on-site rapid testing. Experimental results demonstrate a picomolar detection limit for miRNA-126 and excellent performance in serum samples. Overall, this study provides a promising strategy for sensitive and specific early cancer screening and point-of-care diagnostics.

AI evidence extraction

At a glance

Study type

Engineering / measurement

Effect direction

unclear

Population

—

Sample size

—

Exposure

smartphone

Evidence strength

Insufficient

Confidence: 66% · Peer-reviewed: yes

Main findings

A self-powered dual-readout electrothermal biosensing chip using enzyme-free CHA amplification and hierarchical SnO@MoS hollow spheres enabled real-time smartphone visualization of electrochemical and thermal signals. Experimental results reported a picomolar detection limit for miRNA-126 and good performance in serum samples.

Outcomes measured

Analytical detection of microRNA-126 (miRNA-126) using dual-readout electrochemical and thermal signals
Detection limit (picomolar) for miRNA-126
Performance in serum samples
Smartphone-based real-time visualization/interface for signals

View raw extracted JSON

{
    "study_type": "engineering",
    "exposure": {
        "band": null,
        "source": "smartphone",
        "frequency_mhz": null,
        "sar_wkg": null,
        "duration": null
    },
    "population": null,
    "sample_size": null,
    "outcomes": [
        "Analytical detection of microRNA-126 (miRNA-126) using dual-readout electrochemical and thermal signals",
        "Detection limit (picomolar) for miRNA-126",
        "Performance in serum samples",
        "Smartphone-based real-time visualization/interface for signals"
    ],
    "main_findings": "A self-powered dual-readout electrothermal biosensing chip using enzyme-free CHA amplification and hierarchical SnO@MoS hollow spheres enabled real-time smartphone visualization of electrochemical and thermal signals. Experimental results reported a picomolar detection limit for miRNA-126 and good performance in serum samples.",
    "effect_direction": "unclear",
    "limitations": [],
    "evidence_strength": "insufficient",
    "confidence": 0.66000000000000003108624468950438313186168670654296875,
    "peer_reviewed_likely": "yes",
    "keywords": [
        "biosensor",
        "self-powered",
        "smartphone interface",
        "microRNA-126",
        "CHA amplification",
        "electrochemical signal",
        "thermal transduction",
        "serum samples",
        "early cancer detection",
        "point-of-care diagnostics"
    ],
    "suggested_hubs": []
}

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AI-extracted fields are generated from the abstract/metadata and may be incomplete or incorrect. This content is for informational purposes only and is not medical advice.

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