Spatial Metabolomics co-registered with Multiplex Phenotyping for the Evaluation of Human Kidney Tissue
ABSTRACT A workflow has been evaluated that utilises a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled analysis. The impact of varying DESI-MSI conditions (e.g., temperature, scan rate, acquisition time) on the detection of small molecules and on tissue quality for integration into typical clinical pathology workflows assessed in human kidney..
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Preprint| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
bioRxiv.org - (2023) vom: 17. Nov. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zickuhr, Greice M [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
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| doi: |
10.1101/2023.11.10.566529 |
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| PPN (Katalog-ID): |
XBI041555007 |
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| 520 | |a ABSTRACT A workflow has been evaluated that utilises a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled analysis. The impact of varying DESI-MSI conditions (e.g., temperature, scan rate, acquisition time) on the detection of small molecules and on tissue quality for integration into typical clinical pathology workflows assessed in human kidney. | ||
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