Confocal imaging dataset to assess endothelial cell orientation during extreme glucose conditions
(2022) In Scientific Data 9(1).- Abstract
Confocal microscopy offers a mean to extract quantitative data on spatially confined subcellular structures. Here, we provide an imaging dataset of confocal z-stacks on endothelial cells spatially confined on lines with different widths, visualizing the nucleus, F-actin, and zonula occludens-1 (ZO-1), as well as the lines. This dataset also includes confocal images of spatially confined endothelial cells challenged with different glucose conditions. We have validated the image quality by established analytical means using the MeasureImageQuality module of the CellProfilerTM software. We envision that this dataset could be used to extract data on both a population and a single cell level, as well as a learning set for the... (More)
Confocal microscopy offers a mean to extract quantitative data on spatially confined subcellular structures. Here, we provide an imaging dataset of confocal z-stacks on endothelial cells spatially confined on lines with different widths, visualizing the nucleus, F-actin, and zonula occludens-1 (ZO-1), as well as the lines. This dataset also includes confocal images of spatially confined endothelial cells challenged with different glucose conditions. We have validated the image quality by established analytical means using the MeasureImageQuality module of the CellProfilerTM software. We envision that this dataset could be used to extract data on both a population and a single cell level, as well as a learning set for the development of new image analysis tools.
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- author
- Porras Hernández, Ana María ; Barbe, Laurent ; Pohlit, Hannah ; Tenje, Maria and Antfolk, Maria LU
- organization
- publishing date
- 2022-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Scientific Data
- volume
- 9
- issue
- 1
- article number
- 26
- publisher
- Nature Publishing Group
- external identifiers
-
- scopus:85123831733
- pmid:35087120
- ISSN
- 2052-4463
- DOI
- 10.1038/s41597-022-01130-x
- language
- English
- LU publication?
- yes
- id
- baff79f0-fa98-4771-bec4-1d41d3fee28e
- date added to LUP
- 2022-03-24 16:15:17
- date last changed
- 2025-01-11 09:34:20
@article{baff79f0-fa98-4771-bec4-1d41d3fee28e, abstract = {{<p>Confocal microscopy offers a mean to extract quantitative data on spatially confined subcellular structures. Here, we provide an imaging dataset of confocal z-stacks on endothelial cells spatially confined on lines with different widths, visualizing the nucleus, F-actin, and zonula occludens-1 (ZO-1), as well as the lines. This dataset also includes confocal images of spatially confined endothelial cells challenged with different glucose conditions. We have validated the image quality by established analytical means using the MeasureImageQuality module of the CellProfiler<sup>TM</sup> software. We envision that this dataset could be used to extract data on both a population and a single cell level, as well as a learning set for the development of new image analysis tools.</p>}}, author = {{Porras Hernández, Ana María and Barbe, Laurent and Pohlit, Hannah and Tenje, Maria and Antfolk, Maria}}, issn = {{2052-4463}}, language = {{eng}}, number = {{1}}, publisher = {{Nature Publishing Group}}, series = {{Scientific Data}}, title = {{Confocal imaging dataset to assess endothelial cell orientation during extreme glucose conditions}}, url = {{http://dx.doi.org/10.1038/s41597-022-01130-x}}, doi = {{10.1038/s41597-022-01130-x}}, volume = {{9}}, year = {{2022}}, }