Automated Author ProfileAnderson, Mark
University of California, San Francisco
Anderson, Mark
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: 1.5 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Some individuals do not return to baseline health following SARS-CoV-2 infection, leading to a condition known as Long COVID. The underlying pathophysiology of Long COVID remains unknown. Given that autoantibodies have been found to play a role in severity of COVID infection and certain other post-COVID sequelae, their potential role in Long COVID is important to investigate. Here we apply a well-established, unbiased, proteome-wide autoantibody detection technology (PhIP-Seq) to a robustly phenotyped cohort of 121 individuals with Long COVID, 64 individuals with prior COVID-19 who reported full recovery, and 57 pre-COVID controls. While a distinct autoreactive signature was detected which separates individuals with prior COVID infection from those never exposed to COVID, we did not detect patterns of autoreactivity that separate individuals with Long COVID relative to individuals fully recovered from SARS-CoV-2 infection. These data suggest that there are robust alterations in autoreactive antibody profiles due to infection; however, no association between autoreactive antibodies and Long COVID was apparent by this assay.
Authors
- Bodansky, Aaron ;
- Wang, Chung-Yu ;
- Saxena, Aditi ;
- Mitchell, Anthea ;
- Kung, Andrew ;
- Takahashi, Saki ;
- Anglin, Khamal ;
- Huang, Beatrice ;
- Hoh, Rebecca ;
- Lu, Scott ;
- Goldberg, Sarah ;
- Romero, Justin ;
- Tran, Brandon ;
- Kiritikar, Raushun ;
- Grebe, Halle ;
- So, Matthew ;
- Greenhouse, Bryan ;
- Durstenfeld, Matthew ;
- Hsue, Priscilla ;
- Hellmuth, Joanna ;
- Kelly, Daniel ;
- Martin, Jeffrey ;
- Anderson, Mark ;
- Deeks, Steven ;
- Henrich, Timothy ;
- DeRisi, Joseph ;
- Peluso, Michael