| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Levkin, Pavel A.
Karlsruhe Institute of Technology
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (5/5 displayed)
- 2024Solvent‐Independent 3D Printing of Organogelscitations
- 2023Tough PEGgels by In Situ Phase Separation for 4D Printing
- 2022Inverse Vulcanization of Norbornenylsilanes: Soluble Polymers with Controllable Molecular Properties via Siloxane Bondscitations
- 2021Droplet microarrays for cell culture: effect of surface properties and nanoliter culture volume on global transcriptomic landscapecitations
- 2018Improved extraction repeatability and spectral reproducibility for liquid extraction surface analysis–mass spectrometry using superhydrophobic–superhydrophilic patterningcitations
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article
Improved extraction repeatability and spectral reproducibility for liquid extraction surface analysis–mass spectrometry using superhydrophobic–superhydrophilic patterning
Abstract
A major problem limiting reproducible use of liquid extraction surface analysis (LESA) array sampling of dried surface-deposited liquid samples is the unwanted spread of extraction solvent beyond the dried sample limits, resulting in unreliable data. Here, we explore the use of the Droplet Microarray (DMA), which consists of an array of superhydrophilic spots bordered by a superhydrophobic material giving the potential to confine both the sample spot and the LESA extraction solvent in a defined area. We investigated the DMA method in comparison with a standard glass substrate using LESA analysis of a mixture of biologically relevant compounds with a wide mass range and different physicochemical properties. The optimized DMA method was subsequently applied to urine samples from a human intervention study. Relative standard deviations for the signal intensities were all reduced at least 3-fold when performing LESA-MS on the DMA surface compared with a standard glass surface. Principal component analysis revealed more tight clusters indicating improved spectral reproducibility for a human urine sample extracted from the DMA compared to glass. Lastly, in urine samples from an intervention study, more significant ions (145) were identified when using LESA-MS spectra of control and test urine extracted from the DMA. We demonstrate that DMA provides a surface-assisted LESA-MS method delivering significant improvement of the surface extraction repeatability leading to the acquisition of more robust and higher quality data. The DMA shows potential to be used for LESA-MS for controlled and reproducible surface extraction and for acquisition of high quality, qualitative data in a high-throughput manner.