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Human activities, such as mining and manufacturing, expose society and the natural environment to harmful levels of metal ions. Recently, optical sensor arrays for metal ion detection have become popular owing to their favourable features, such as facile sample preparation and the requirement of less expensive instrumentation compared to traditional, spectrometry-based analysis techniques. Sensor arrays usually consist of numerous optical probes that are used in combination to generate unique analyte responses. In contrast, here we present an array that comprises a single fluorescent sensor, Coum4-DPA, that produces unique responses to metal ions in different pH environments. With this simple sensing platform, we were able to classify 10 metal ions in different water sources and quantify Pb2+ in tap water using just one fluorescent sensor, a few pH buffers and two sets of spectral data. This novel approach significantly decreases time and costs associated with probe synthesis and data collection, making it highly transferrable to real-world metal sensing applications.

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RESUMEN

Lead is a heavy metal which has long been known to have toxic effects on the body. However, much remains to be learnt about the labile lead pool and cellular uptake of lead. We report here RPb1 that undergoes a 100-fold increase in fluorescence emission in the presence of Pb2+, and which can be applied to study the labile lead pool within cells. We demonstrate the capacity of RPb1 for investigating labile lead pool in DLD-1 cells and changes in labile lead during differentiation of K562 cells.

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Toxic heavy metal detection in water sources is crucial due to the detrimental social and environmental threats these metals pose. Traditional methods of metal detection in water rely on expensive and sophisticated technologies, limiting their availability for on-site detection. Here, we report a six-member fluorescent sensor array for 100% successful classification of 9 metal ions in water. The array consists of the commercially available fluorescent dye, Calcein Blue, and 5 analogues that were all synthesised in three steps or less. To further increase simplicity, we report the reduction of the number of sensing elements from 6 to 3 using multivariate statistics to arrive at an array still capable of 100% correct classification. The utility of the three-member fluorescent sensing array was confirmed in environmental pond water samples. The array's flexibility was also demonstrated through its successful classification of micromolar concentrations of Pb2+ for quantitative analysis of heavy metals in water samples.