A Thermogalvanic Cell Microneedle Patch for Integrated Diagnosis and Treatment of UV-Induced Early Skin Cancer
Abstract
Early stage skin cancer exhibits a high cure rate; however, conventional noninvasive screening suffers from diagnostic inaccuracies, and treatment reliant on postlesion surgery remains inherently passivity. This work develops an all-in-one platform by coupling microneedle (MN) patches with a lateral flow immunoassay (LFIA), seamlessly integrating self-powered biomarker extraction, multimodal detection, and biomarker-responsive therapy for point-of-care testing (POCT) and personalized treatment of UV-induced early stage skin cancer. It incorporates a thermogalvanic cell (TGC) MN, which leverages photothermal-thermoelectric coupling to achieve external power-free transdermal extraction of the biomarker (8-OH-dG) within 10 min. The extracted 8-OH-dG triggers the structural change of the hairpin aptamer (HA) on the PtPB@PEG@HA (PPPA) nanoparticles (NPs), initiating a cascade amplification that generates abundant DNA nanozymes for colorimetric detection (100 pM to 60 nM). A convolutional neural network (CNN) is introduced for colorimetric quantification, coupled with artificial intelligence (AI) for disease risk assessment. Once captured in the LFIA detection zone by a capture probe, the open-loop PPPA NPs permit surface-enhanced Raman spectroscopy (SERS) detection of 8-OH-dG, enabling dual-mechanism cross-verification. Under near-infrared (NIR) irradiation, the PPPA NPs also serve as photothermal actuators to trigger the controlled release of quercetin from phase-transition MNs, effectively scavenging UV-induced oxidative stress. This innovation facilitates the home-based diagnosis and management of early stage skin cancer.
Fields of Study & Subjects
Advancements in Transdermal Drug Delivery
Skin Protection and Aging
Advanced biosensing and bioanalysis techniques
Publication details
- Journal / source
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Volume
- 98
- Issue
- 14
- Pages
- 10715–10727
- Publication date
- 1 April 2026
- Language
- EN