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Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis

Overview of attention for article published in Scientific Reports, December 2017
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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4 X users
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5 patents

Citations

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26 Dimensions

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31 Mendeley
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Title
Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis
Published in
Scientific Reports, December 2017
DOI 10.1038/s41598-017-17000-1
Pubmed ID
Authors

Shiv D. Kale, Tariq Ayubi, Dawoon Chung, Nuria Tubau-Juni, Andrew Leber, Ha X. Dang, Saikumar Karyala, Raquel Hontecillas, Christopher B. Lawrence, Robert A. Cramer, Josep Bassaganya-Riera

Abstract

Incidences of invasive pulmonary aspergillosis, an infection caused predominantly by Aspergillus fumigatus, have increased due to the growing number of immunocompromised individuals. While A. fumigatus is reliant upon deficiencies in the host to facilitate invasive disease, the distinct mechanisms that govern the host-pathogen interaction remain enigmatic, particularly in the context of distinct immune modulating therapies. To gain insights into these mechanisms, RNA-Seq technology was utilized to sequence RNA derived from lungs of 2 clinically relevant, but immunologically distinct murine models of IPA on days 2 and 3 post inoculation when infection is established and active disease present. Our findings identify notable differences in host gene expression between the chemotherapeutic and steroid models at the interface of immunity and metabolism. RT-qPCR verified model specific and nonspecific expression of 23 immune-associated genes. Deep sequencing facilitated identification of highly expressed fungal genes. We utilized sequence similarity and gene expression to categorize the A. fumigatus putative in vivo secretome. RT-qPCR suggests model specific gene expression for nine putative fungal secreted proteins. Our analysis identifies contrasting responses by the host and fungus from day 2 to 3 between the two models. These differences may help tailor the identification, development, and deployment of host- and/or fungal-targeted therapeutics.

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 26%
Student > Bachelor 4 13%
Professor 3 10%
Student > Ph. D. Student 3 10%
Student > Master 3 10%
Other 2 6%
Unknown 8 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 19%
Biochemistry, Genetics and Molecular Biology 5 16%
Immunology and Microbiology 4 13%
Computer Science 2 6%
Medicine and Dentistry 2 6%
Other 2 6%
Unknown 10 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 20 June 2023.
All research outputs
#6,283,212
of 23,577,654 outputs
Outputs from Scientific Reports
#42,384
of 127,567 outputs
Outputs of similar age
#121,530
of 442,941 outputs
Outputs of similar age from Scientific Reports
#1,351
of 4,311 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 127,567 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.4. This one has gotten more attention than average, scoring higher than 66% 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 442,941 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 4,311 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.