Automated Author ProfileKubankova, Marketa
0000-0001-7086-8938
Kubankova, Marketa
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 11.3 (sum of 16 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This dataset contains measurements of the physical phenotype of single cells dissociated from mouse liver using a tissue grinder device or by enzymatic dissociation. The datasets include two runs from each experiment.
Measurements were performed using real-time fluorescent deformability cytometry.
TG.zip-contains data acquired during the measurements in 'rtdc' format from tissues dissociated using a tissue grinder.
Enzymatic.zip-contains data acquired during the measurements in 'rtdc' format from tissues dissociated using an enzymatic protocol.
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of mouse cells mechanically dissociated from the spleen, thymus, and kidney using a tissue grinder device.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
TG.zip-contains data acquired during the measurements in '.rtdc' format of spleen or thymus cells dissociated using a tissue grinder (TG) device).
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of mouse cells mechanically dissociated from the spleen, thymus, and kidney using a tissue grinder device.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
TG.zip-contains data acquired during the measurements in '.rtdc' format of spleen or thymus cells dissociated using a tissue grinder (TG) device).
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of single cells dissociated from mouse liver using a tissue grinder device or by enzymatic dissociation. The datasets include two runs from each experiment.
Measurements were performed using real-time fluorescent deformability cytometry.
TG.zip-contains data acquired during the measurements in 'rtdc' format from tissues dissociated using a tissue grinder.
Enzymatic.zip-contains data acquired during the measurements in 'rtdc' format from tissues dissociated using an enzymatic protocol.
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
Clinical syndrome coronavirus disease 2019 (COVID-19) induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by rapid spreading and high mortality worldwide. While the pathology is not yet fully understood, hyper-inflammatory response and coagulation disorders leading to congestions of microvessels are considered to be key drivers of the still increasing death toll. Until now, physical changes of blood cells have not been considered to play a role in COVID-19 related vascular occlusion and organ damage. Here we report an evaluation of multiple physical parameters including the mechanical features of five frequent blood cell types, namely erythrocytes, lymphocytes, monocytes, neutrophils, and eosinophils. More than 4 million blood cells of 17 COVID-19 patients at different levels of severity, 24 volunteers free from infectious or inflammatory diseases, and 14 recovered COVID-19 patients were analyzed. We found significant changes in lymphocyte stiffness, monocyte size, neutrophil size and deformability, and heterogeneity of erythrocyte deformation and size. While some of these changes recovered to normal values after hospitalization, others persisted for months after hospital discharge, evidencing the long-term imprint of COVID-19 on the body.
Authors
- Kubánková, Markéta ;
- Hohberger, Bettina ;
- Hoffmanns, Jakob ;
- Fürst, Julia ;
- Herrmann, Martin ;
- Guck, Jochen ;
- Kräter, Martin
Clinical syndrome coronavirus disease 2019 (COVID-19) induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by rapid spreading and high mortality worldwide. While the pathology is not yet fully understood, hyper-inflammatory response and coagulation disorders leading to congestions of microvessels are considered to be key drivers of the still increasing death toll. Until now, physical changes of blood cells have not been considered to play a role in COVID-19 related vascular occlusion and organ damage. Here we report an evaluation of multiple physical parameters including the mechanical features of five frequent blood cell types, namely erythrocytes, lymphocytes, monocytes, neutrophils, and eosinophils. More than 4 million blood cells of 17 COVID-19 patients at different levels of severity, 24 volunteers free from infectious or inflammatory diseases, and 14 recovered COVID-19 patients were analyzed. We found significant changes in lymphocyte stiffness, monocyte size, neutrophil size and deformability, and heterogeneity of erythrocyte deformation and size. While some of these changes recovered to normal values after hospitalization, others persisted for months after hospital discharge, evidencing the long-term imprint of COVID-19 on the body.
Authors
- Kubánková, Markéta ;
- Hohberger, Bettina ;
- Hoffmanns, Jakob ;
- Fürst, Julia ;
- Herrmann, Martin ;
- Guck, Jochen ;
- Kräter, Martin
This dataset contains measurements of the physical phenotype of mouse cells mechanically dissociated from the mouse colon using a tissue grinder device. The datasets include a control group, i.e. healthy mouse colon and a transfer colitis group; where immunodeficient mice were injected intraperitoneally with CD4+CD25- T cells three weeks prior to extracting and analysing colon cells.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
.zip-contains data acquired during the measurements in 'rtdc' format
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of single cells mechanically dissociated from mouse liver, colon and kidney using a tissue grinder device.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
.rtdc-contains data acquired during the measurements in 'rtdc' format.
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of single cells mechanically dissociated from mouse liver, colon and kidney using a tissue grinder device.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
.rtdc-contains data acquired during the measurements in 'rtdc' format.
Authors
- Soteriou, Despina ;
- Kubankova, Marketa
This dataset contains measurements of the physical phenotype of mouse cells mechanically dissociated from the mouse colon using a tissue grinder device. The datasets include a control group, i.e. healthy mouse colon and a transfer colitis group; where immunodeficient mice were injected intraperitoneally with CD4+CD25- T cells three weeks prior to extracting and analysing colon cells.
Measurements were performed using real-time fluorescent deformability cytometry. Fluorescent antibodies used: CD31-PE, CD45-FITC and EpCAM-APC.
.zip-contains data acquired during the measurements in 'rtdc' format
Authors
- Soteriou, Despina ;
- Kubankova, Marketa