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Development of a Zebrafish Sepsis Model for High-Throughput Drug Discovery

Overview of attention for article published in Molecular Medicine, June 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

patent
2 patents

Citations

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39 Dimensions

Readers on

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95 Mendeley
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Title
Development of a Zebrafish Sepsis Model for High-Throughput Drug Discovery
Published in
Molecular Medicine, June 2017
DOI 10.2119/molmed.2016.00188
Pubmed ID
Authors

Anju M. Philip, Youdong Wang, Antonio Mauro, Suzan El-Rass, John C. Marshall, Warren L. Lee, Arthur S. Slutsky, Claudia C. dos Santos, Xiao-Yan Wen

Abstract

Sepsis is a leading cause of death worldwide. Current treatment modalities remain largely supportive. Intervention strategies focused on inhibiting specific mediators of the inflammatory host response have been largely unsuccessful, a consequence of an inadequate understanding of the complexity and heterogeneity of the innate immune response. Moreover, the conventional drug development pipeline is time consuming and expensive and the low success rates associated with cell-based screens underline the need for whole organism screening strategies, especially for complex pathological processes. Here, we established an LPS-induced zebrafish endotoxemia model, which exhibits the major hallmarks of human sepsis including, edema and tissue/organ damage, increased vascular permeability and vascular leakage accompanied by an altered expression of cellular junction proteins, increased cytokine expression, immune cell activation and ROS production, reduced circulation and increased platelet aggregation. We tested the suitability of the model for phenotype-based drug screening using three primary readouts: mortality, vascular leakage, and ROS production. Preliminary screening identified fasudil, a drug known to protect against vascular leakage in murine models, as a lead hit thereby validating the utility of our model for sepsis drug screens. This zebrafish sepsis model has the potential to rapidly analyze sepsis associated pathologies and cellular processes in the whole organism, as well as to screen and validate large numbers of compounds that can modify sepsis pathology in vivo.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 95 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 26 27%
Researcher 12 13%
Student > Master 8 8%
Other 5 5%
Student > Postgraduate 5 5%
Other 10 11%
Unknown 29 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 19%
Agricultural and Biological Sciences 13 14%
Medicine and Dentistry 11 12%
Pharmacology, Toxicology and Pharmaceutical Science 7 7%
Neuroscience 4 4%
Other 11 12%
Unknown 31 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 August 2022.
All research outputs
#4,767,124
of 23,063,209 outputs
Outputs from Molecular Medicine
#188
of 1,151 outputs
Outputs of similar age
#84,100
of 317,469 outputs
Outputs of similar age from Molecular Medicine
#1
of 5 outputs
Altmetric has tracked 23,063,209 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,151 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,469 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them