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Lateral flow assays (LFAs) are widely adopted for fast, on-site molecular diagnostics. Obtaining high-precision assay results, however, remains challenging and often requires a dedicated optical setup to control the imaging environment. Here, we describe quick light normalization exam (qLiNE) that transforms ubiquitous smartphones into a robust LFA reader. qLiNE used a reference card, printed with geometric patterns and color standards, for real-time optical calibration: a photo of an LFA test strip was taken along with the card, and the image was processed using a smartphone app to correct shape distortion, illumination brightness, and color imbalances. This approach yielded consistent optical signal, enabling quantitative molecular analyses under different illumination conditions. We adapted qLiNE to detect cortisol, a known stress hormone, in saliva samples at point-of-use settings. The assay was fast (15 min) and sensitive (detection limit, 0.16 ng/mL). The serial qLiNE assay detected diurnal cycles of cortisol levels as well as stress-induced cortisol increase.

Normalizing the Optical Signal Enables Robust Assays with Lateral Flow Biosensors