Authors
Huiling Jiang, Jing Shi, Chunyan He, Yanan Chen, Kang Wu, Anping Deng, Jianguo Li
Published in
Analytica chimica acta. Volume 1422. Pages 346075. Nov 08, 2026. Epub Aug 04, 2026.
Abstract
T-2 toxin threatens global food security and ecological stability due to its potent toxicity and environmental persistence. Thus, it is essential for addressing this threat. While electrochemiluminescence (ECL) offers sensitive mycotoxin detection, traditional systems suffer from low luminescent efficiency, complex interface modification, and notable matrix interference from real samples. In recent years, the emergence of aggregation-induced electrochemiluminescence (AIECL) materials, such as the styrene derivative V-TCPE, has provided new insights into signal amplification owing to their excellent luminescent properties in highly aggregated states.
A competitive AIECL biosensor anchored on V-TCPE was devised herein, employing CoMoO4@Au nanoflowers as a co-reaction accelerator for mycotoxin quantification. Capitalizing on the exceptional conductivity of the CoMoO4@Au nanoflowers alongside the prominent aggregation-induced emission properties of the coordination framework, the assembled platform demonstrated a linear response across seven orders of magnitude (0.0009∼1000 ng mL-1) and attained a discernment threshold of 0.28 pg mL-1 (S/N = 3), originating from facilitated charge propagation coupled with vigorous radiative output. Furthermore, selectivity, stability, and real-sample evaluations demonstrated robust anti-interference capability and practical applicability, offering a sensitive platform for T-2 toxin trace detection.
This study combined the AIECL properties of V-TCPE with the high conductivity of CoMoO4@Au nanoflowers within a competitive immunoassay for ultrasensitive detection. The vanadium coordination environment endows V-TCPE with superior AIECL performance and stability. This approach broadens vanadium-based AIECL materials in mycotoxin analysis and establishes a platform for monitoring trace contaminants in complex food matrices.
PMID:
42763143
Bibliographic data and abstract were imported from PubMed on 20 Sep 2026.
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