Serotonin measurement by lab-on-a-contact lens in porcine and human tears.

Authors

Minwoo Kim, Sang Won Lee, Chenguang Zhang, Wenyi Zeng, Liangshu Liu, Aliesha Danielle Garrett, Reihaneh Haghniaz, Dawn Meyer, Jianjun Chen, Juchen Guo, A Janet Tomiyama, Pete S Kollbaum, Yangzhi Zhu

Published in

Science translational medicine. Volume 18. Issue 867. Pages eadv9538. Sep 16, 2026. Epub Sep 16, 2026.

Abstract

Stress-related endocrine responses are critical for understanding human performance and mental health. Conventional assessments rely heavily on subjective self-report questionnaires or invasive sampling such as venipuncture. Tears offer a noninvasive source of neurochemical biomarkers, including serotonin, a key regulator of stress and mood. However, real-time and continuous monitoring of tear serotonin has not yet been fully realized. Here, we present a reversible lab-on-a-contact lens platform that integrates a printable, stretchable ferrocene-based electrochemical sensor for in situ detection of serotonin in tear fluid. The device is fabricated on a soft hydrogel lens and uses an electrochemically refreshable redox surface to restore baseline between measurements. Calibration in artificial tears established a limit of detection of 72 picomolar and a dynamic range of 0.1 to 500 nanomolar. Function was maintained for more than 28 days in a tear-like environment and under repeated mechanical deformations (flipping, folding, stretching, and twisting), with stability confirmed by periodic redox cycling. Ocular safety and biocompatibility were demonstrated in a porcine eye model. In a chronic stress mouse model, tear serotonin concentrations inversely correlated with cortisol in both serum and tears, and a first-in-human pilot study further supported the relationship between tear serotonin and stress with off-line analysis by the lab-on-a-contact lens platform. This platform could enable applications in decentralized, noninvasive endocrine monitoring and holds promise as a clinically translatable tool for real-time mental health biomarker assessment.

PMID:
42748216
Bibliographic data and abstract were imported from PubMed on 17 Sep 2026.

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