Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 20221881. Detection of SARS-CoV-2 Transmission on a College Campus using a Combined Contact Tracing and Molecular Strategycitations
  • 20221890. Molecular Biology of SARS-CoV-2 and its Evolution within the Princeton University Campus Communitycitations

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Chart of shared publication
Notterman, Daniel
2 / 2 shared
Daskalaki, Irini
2 / 2 shared
Wang, Wei
2 / 19 shared
Yang, Qiqi
1 / 1 shared
Chart of publication period
2022

Co-Authors (by relevance)

  • Notterman, Daniel
  • Daskalaki, Irini
  • Wang, Wei
  • Yang, Qiqi
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article

1881. Detection of SARS-CoV-2 Transmission on a College Campus using a Combined Contact Tracing and Molecular Strategy

  • Aranovich, Irina
  • Notterman, Daniel
  • Daskalaki, Irini
  • Wang, Wei
Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>SARS-CoV-2 has caused unprecedented global disruption following its introduction into the human population. Beginning in August 2021, a residential college initiated an asymptomatic testing protocol using PCR-based detection of human saliva samples (Thermofisher, TaqPath SARS-CoV-2 Assay; QuantStudio v1.3). In January 2021 all students were invited to campus and were required to test once or twice weekly in an effort to isolate those positive (cases) as early as possible and minimize transmission.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Cases were contacted within 12 hours by trained clinical staff and interviewed with a standardized questionnaire to determine contacts and exposures. Positive samples were submitted for RNA-Seq analysis (ARTIC amplicon sequencing protocol, Illumina MiSeq) and analyzed using Nextclade and USHER (comparison data from GISAID). Using this sequence data, we monitored the evolution, transmission, and emergence of variants over time in the campus community.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In March 2022 a one-week break and the activities preceding it were followed by an outbreak of COVID among campus members. All cases were attributed to the Omicron variant. Based on traditional contact tracing 10 presumed clusters of transmission were identified (34 students). Sequence data from these 34 samples were assembled to identify phylogenetic and molecular patterns of similarity. Several molecular signatures were identified. In a group of 5 cases, all were Omicron BA.2.9; these individuals comprised a clinical cluster of students who had travelled together. Other lineages were BA.2 (N=26), BA.1(N=2), BA.2.12. (N=3), BA.2.3 (N=1) and an Omicron Clade 21M variant that appeared to be a BA.1/BA.2 recombinant (N=2). The BA.2.12 samples were contributed over 2 days; they were found in two different clusters (a social club and an artistic group), demonstrating likely transmission between members. The BA.2 samples were distributed across a wide number of student groups, and while not identical with one another, did not fall into the clusters identified by contact tracing, suggesting endemic transmission across our campus.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>This analysis demonstrates that molecular analysis of SARS-CoV-2 transmission can supplement and inform the data provided by clinical/epidemiological analysis of cases.</jats:p></jats:sec><jats:sec><jats:title>Disclosures</jats:title><jats:p>All Authors: No reported disclosures.</jats:p></jats:sec>

Topics
  • cluster
  • size-exclusion chromatography