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• W4313488873 abstract "Skin metabolites show huge potential for use in clinical diagnostics. However, skin sampling and analysis workflows are tedious and time-consuming. Here, we demonstrate a vending-machine-style skin excretion sensing platform based on hydrogel-assisted sampling of skin metabolites. In this sensing platform, a sampling probe with hydrogel is held by a robotic arm. The robotic arm manoeuvres the probe to press it onto the forearm of a human subject. Due to the highly hydrophilic nature of the hydrogel, water-soluble metabolites─released by skin─are collected into the hydrogel, leaving behind the nonpolar metabolites. The probe is then inserted into a custom-made open port sampling interface coupled to an electrospray ion source of a high-resolution quadrupole-time-of-flight mass spectrometer. Metabolites in the hydrogel are immediately extracted by a solvent liquid junction in the interface and analyzed using the mass spectrometer. The ion current of the target analyte is displayed on a customized graphical user interface, which can also be used to control the key components of the analytical platform. The automated sampling and analysis workflow starts after the user inserts coins or presents an insurance card, presses a button, and extends an arm on the sampling area. The platform relies on low-cost mechanical and electronic modules (a robotic arm, a single-board computer, and two microcontroller boards). The limits of detection for standard analytes─arginine, citrulline, and histidine─embedded in agarose gel beds were 148, 205, and 199 nM, respectively. Various low-molecular-weight metabolites from human skin have been identified with the high-resolution mass spectrometer." @default.
• W4313488873 created "2023-01-06" @default.
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• W4313488873 date "2023-01-04" @default.
• W4313488873 modified "2023-09-26" @default.
• W4313488873 title "Vending-Machine-Style Skin Excretion Sensing" @default.
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• W4313488873 doi "https://doi.org/10.1021/acssensors.2c02325" @default.
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• W4313488873 hasPublicationYear "2023" @default.
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