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Gold-Functionalized Multilayer Heterojunction Microarchitectures Enable High-Fidelity Serum Metabolite Profiling for

Daili Gao¹, Zihao Liu¹, Xinyi Li¹

¹School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, China.

|June 16, 2026

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This summary is machine-generated.

Researchers developed novel gold-modified multilayer heterojunctions for enhanced laser desorption/ionization mass spectrometry. This new method enables sensitive serum metabolite detection for accurate skin cancer and psoriasis classification.

Area of Science:

Biomaterials Science
Analytical Chemistry
Medical Diagnostics

Background:

Skin cancer and psoriasis significantly impact global health, necessitating early and accurate detection.
Serum metabolites offer a noninvasive window into physiological states, serving as potential disease biomarkers.
Current diagnostic methods may lack the sensitivity or noninvasiveness required for widespread screening.

Purpose of the Study:

To develop an advanced matrix for laser desorption/ionization mass spectrometry (LDI-MS) to improve serum metabolite detection.
To create a novel gold-modified rose-like multilayer heterojunction (G-RMHJ) material for enhanced analytical performance.
To establish a noninvasive, metabolomics-based framework for classifying skin cancer and psoriasis patients.

Main Methods:

Keywords:

LDI‐MS multiclass classification serum metabolic skin diseases subtype identification

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Fabrication of gold-modified rose-like multilayer heterojunctions (G-RMHJ).
Utilized G-RMHJ as a matrix for LDI-MS analysis of serum metabolites.
Applied machine learning models to metabolic fingerprints for disease classification.

Main Results:

G-RMHJ demonstrated enhanced light absorption, energy transfer, and ionization efficiency for sensitive serum metabolite detection.
Machine learning models achieved 100% test-set accuracy in distinguishing patients from healthy controls.
Identified eight key metabolites that reliably differentiated four disease types from healthy controls with high AUC values (0.933-1.000).

Conclusions:

Hierarchical microstructured heterojunctions offer a direct route to improved bioanalytical performance.
The G-RMHJ-assisted LDI-MS provides a generalizable and noninvasive platform for serum metabolomics.
This approach shows significant potential for early disease classification and skin cancer subtype identification.