Automated Author ProfileDooley, Steven
Dooley, Steven
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: 7.2 (sum of 13 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Additional file 2: Table S2. PRRX1 positively and negatively correlated genes in TCGA liver cancer data.
Authors
- Piorońska, Weronika ;
- Nwosu, Zeribe Chike ;
- Han, Mei ;
- Büttner, Michael ;
- Ebert, Matthias Philip ;
- Dooley, Steven ;
- Meyer, Christoph
Additional file 3: Table S10. Genes differentially expressed in PRRX1-high tumours relative to PRRX1-low tumours.
Authors
- Piorońska, Weronika ;
- Nwosu, Zeribe Chike ;
- Han, Mei ;
- Büttner, Michael ;
- Ebert, Matthias Philip ;
- Dooley, Steven ;
- Meyer, Christoph
Additional file 3: Table S10. Genes differentially expressed in PRRX1-high tumours relative to PRRX1-low tumours.
Authors
- Piorońska, Weronika ;
- Nwosu, Zeribe Chike ;
- Han, Mei ;
- Büttner, Michael ;
- Ebert, Matthias Philip ;
- Dooley, Steven ;
- Meyer, Christoph
Additional file 2: Table S2. PRRX1 positively and negatively correlated genes in TCGA liver cancer data.
Authors
- Piorońska, Weronika ;
- Nwosu, Zeribe Chike ;
- Han, Mei ;
- Büttner, Michael ;
- Ebert, Matthias Philip ;
- Dooley, Steven ;
- Meyer, Christoph
Table S4. Consistent genes in all four human HCC datasets analysed in this study. These are the genes differentially upregulated (in bold, n = 2017) or downregulated (n = 1547, P
Authors
- Zeribe Nwosu ;
- Battello, Nadia ;
- Rothley, Melanie ;
- Piorońska, Weronika ;
- Sitek, Barbara ;
- Ebert, Matthias ;
- Hofmann, Ute ;
- Sleeman, Jonathan ;
- Wölfl, Stefan ;
- Meyer, Christoph ;
- Megger, Dominik ;
- Dooley, Steven
Table S4. Consistent genes in all four human HCC datasets analysed in this study. These are the genes differentially upregulated (in bold, n = 2017) or downregulated (n = 1547, P
Authors
- Zeribe Nwosu ;
- Battello, Nadia ;
- Rothley, Melanie ;
- Piorońska, Weronika ;
- Sitek, Barbara ;
- Ebert, Matthias ;
- Hofmann, Ute ;
- Sleeman, Jonathan ;
- Wölfl, Stefan ;
- Meyer, Christoph ;
- Megger, Dominik ;
- Dooley, Steven
Table S6. Proteomics profile of HUH7 vs HLE cell lines. Expression pattern of proteins for which at least 2 peptides were detected in the cell lines after 48 h culture. When compared, 797 proteins emerged as more expressed in HLE cells whereas 616 proteins were more expressed in HUH7 (adjusted P
Authors
- Zeribe Nwosu ;
- Battello, Nadia ;
- Rothley, Melanie ;
- Piorońska, Weronika ;
- Sitek, Barbara ;
- Ebert, Matthias ;
- Hofmann, Ute ;
- Sleeman, Jonathan ;
- Wölfl, Stefan ;
- Meyer, Christoph ;
- Megger, Dominik ;
- Dooley, Steven
Table S6. Proteomics profile of HUH7 vs HLE cell lines. Expression pattern of proteins for which at least 2 peptides were detected in the cell lines after 48 h culture. When compared, 797 proteins emerged as more expressed in HLE cells whereas 616 proteins were more expressed in HUH7 (adjusted P
Authors
- Zeribe Nwosu ;
- Battello, Nadia ;
- Rothley, Melanie ;
- Piorońska, Weronika ;
- Sitek, Barbara ;
- Ebert, Matthias ;
- Hofmann, Ute ;
- Sleeman, Jonathan ;
- Wölfl, Stefan ;
- Meyer, Christoph ;
- Megger, Dominik ;
- Dooley, Steven
Diabetes mellitus type 2 (T2DM), insulin therapy, and hyperinsulinemia are independent risk factors of liver cancer. Recently, the use of a novel inhibitor of insulin degrading enzyme (IDE) was proposed as a new therapeutic strategy in T2DM. However, IDE inhibition might stimulate liver cell proliferation via increased intracellular insulin concentration. The aim of this study was to characterize effects of inhibition of IDE activity in HepG2 hepatoma cells and to analyze liver specific expression of IDE in subjects with T2DM. HepG2 cells were treated with 10 nM insulin for 24 h with or without inhibition of IDE activity using IDE RNAi, and cell transcriptome and proliferation rate were analyzed. Human liver samples (n=22) were used for the gene expression profiling by microarrays. In HepG2 cells, IDE knockdown changed expression of genes involved in cell cycle and apoptosis pathways. Proliferation rate was lower in IDE knockdown cells than in controls. Microarray analysis revealed the decrease of hepatic IDE expression in subjects with T2DM accompanied by the downregulation of the p53-dependent genes FAS and CCNG2, but not by the upregulation of proliferation markers MKI67, MCM2 and PCNA. Similar results were found in the liver microarray dataset from GEO Profiles database. In conclusion, IDE expression is decreased in liver of subjects with T2DM which is accompanied by the dysregulation of p53 pathway. Prolonged use of IDE inhibitors for T2DM treatment should be carefully tested in animal studies regarding its potential effect on hepatic tumorigenesis.
Authors
- Pivovarova, Olga ;
- Loeffelholz, Christian Von ;
- Ilkavets, Iryna ;
- Sticht, Carsten ;
- Zhuk, Sergei ;
- Murahovschi, Veronica ;
- Lukowski, Sonja ;
- Döcke, Stephanie ;
- Kriebel, Jennifer ;
- Gala, Tonia De Las Heras ;
- Malashicheva, Anna ;
- Kostareva, Anna ;
- Lock, Johan F ;
- Stockmann, Martin ;
- Grallert, Harald ;
- Gretz, Norbert ;
- Dooley, Steven ;
- Pfeiffer, Andreas FH ;
- Rudovich, Natalia
Diabetes mellitus type 2 (T2DM), insulin therapy, and hyperinsulinemia are independent risk factors of liver cancer. Recently, the use of a novel inhibitor of insulin degrading enzyme (IDE) was proposed as a new therapeutic strategy in T2DM. However, IDE inhibition might stimulate liver cell proliferation via increased intracellular insulin concentration. The aim of this study was to characterize effects of inhibition of IDE activity in HepG2 hepatoma cells and to analyze liver specific expression of IDE in subjects with T2DM. HepG2 cells were treated with 10 nM insulin for 24 h with or without inhibition of IDE activity using IDE RNAi, and cell transcriptome and proliferation rate were analyzed. Human liver samples (n = 22) were used for the gene expression profiling by microarrays. In HepG2 cells, IDE knockdown changed expression of genes involved in cell cycle and apoptosis pathways. Proliferation rate was lower in IDE knockdown cells than in controls. Microarray analysis revealed the decrease of hepatic IDE expression in subjects with T2DM accompanied by the downregulation of the p53-dependent genes FAS and CCNG2, but not by the upregulation of proliferation markers MKI67, MCM2 and PCNA. Similar results were found in the liver microarray dataset from GEO Profiles database. In conclusion, IDE expression is decreased in liver of subjects with T2DM which is accompanied by the dysregulation of p53 pathway. Prolonged use of IDE inhibitors for T2DM treatment should be carefully tested in animal studies regarding its potential effect on hepatic tumorigenesis.
Authors
- Pivovarova, Olga ;
- Loeffelholz, Christian Von ;
- Ilkavets, Iryna ;
- Sticht, Carsten ;
- Zhuk, Sergei ;
- Murahovschi, Veronica ;
- Lukowski, Sonja ;
- Döcke, Stephanie ;
- Kriebel, Jennifer ;
- Gala, Tonia De Las Heras ;
- Malashicheva, Anna ;
- Kostareva, Anna ;
- Lock, Johan F ;
- Stockmann, Martin ;
- Grallert, Harald ;
- Gretz, Norbert ;
- Dooley, Steven ;
- Pfeiffer, Andreas FH ;
- Rudovich, Natalia