Related Experiment Video
Updated: Jun 20, 2026

Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies
Published on: June 20, 2015
Development of a Charge-Mediated Disaggregation-Induced Fluorescence Enhancement Platform Using NS-Carbon Dots for
Yousef A Bin Jardan1, Mohamed M El-Wekil2, Mohamed R Elmasry3
1Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Abstract:
A novel ratiometric fluorometric sensor has been developed utilizing dual-emission nitrogen and sulfur co-doped carbon dots (NS-CDs) for the sensitive determination of metformin. The sensing mechanism relies on a unique disaggregation phenomenon observed under acidic conditions, where electrostatic repulsion between positively charged NS-CDs and metformin molecules leads to enhanced fluorescence emission. Upon metformin addition, the NS-CDs exhibit differential enhancement of their characteristic emission peaks, with the 562 nm peak showing markedly greater amplification than the 365 nm peak. This distinctive response enabled the development of a ratiometric detection approach using the F562/F365 intensity ratio as an analytical signal, providing enhanced measurement reliability by minimizing biological matrix interferences. The sensor demonstrated excellent analytical performance with a linear response range of 0.05-0.9 µM and an impressive detection limit of 15 nM, surpassing the sensitivity of many previously reported methods. The method exhibited remarkable selectivity toward metformin in the presence of common interferents including co-administered drugs, biomolecules, and ionic species typically present in plasma samples. The practical utility of the sensor was validated through successful application in pharmacokinetic studies in rabbit plasma following oral metformin administration, demonstrating its potential for therapeutic drug monitoring and bioanalytical applications. This sensing platform combines high sensitivity, excellent selectivity, and rapid response time, making it a promising tool for metformin quantification in complex biological matrices.

