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Pre-clinical Imaging of Invasive Candidiasis Using ImmunoPET/MR

Overview of attention for article published in Frontiers in Microbiology, August 2018
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Title
Pre-clinical Imaging of Invasive Candidiasis Using ImmunoPET/MR
Published in
Frontiers in Microbiology, August 2018
DOI 10.3389/fmicb.2018.01996
Pubmed ID
Authors

Hassan O. J. Morad, Anna-Maria Wild, Stefan Wiehr, Genna Davies, Andreas Maurer, Bernd J. Pichler, Christopher R. Thornton

Abstract

The human commensal yeast Candida is the fourth most common cause of hospital-acquired bloodstream infections, with Candida albicans accounting for the majority of the >400,000 life-threatening infections annually. Diagnosis of invasive candidiasis (IC), a disease encompassing candidemia (blood-borne yeast infection) and deep-seated organ infections, is a major challenge since clinical manifestations of the disease are indistinguishable from viral, bacterial and other fungal diseases, and diagnostic tests for biomarkers in the bloodstream such as PCR, ELISA, and pan-fungal β-D-glucan lack either standardization, sensitivity, or specificity. Blood culture remains the gold standard for diagnosis, but test sensitivity is poor and turn-around time slow. Furthermore, cultures can only be obtained when the yeast resides in the bloodstream, with samples recovered from hematogenous infections often yielding negative results. Consequently, there is a pressing need for a diagnostic test that allows the identification of metastatic foci in deep-seated Candida infections, without the need for invasive biopsy. Here, we report the development of a highly specific mouse IgG3 monoclonal antibody (MC3) that binds to a putative β-1,2-mannan epitope present in high molecular weight mannoproteins and phospholipomannans on the surface of yeast and hyphal morphotypes of C. albicans, and its use as a [64Cu]NODAGA-labeled tracer for whole-body pre-clinical imaging of deep-seated C. albicans infections using antibody-guided positron emission tomography and magnetic resonance imaging (immunoPET/MRI). When used in a mouse intravenous (i.v.) challenge model that faithfully mimics disseminated C. albicans infections in humans, the [64Cu]NODAGA-MC3 tracer accurately detects infections of the kidney, the principal site of blood-borne candidiasis in this model. Using a strain of the emerging human pathogen Candida auris that reacts with MC3 in vitro, but which is non-infective in i.v. challenged mice, we demonstrate the accuracy of the tracer in diagnosing invasive infections in vivo. This pre-clinical study demonstrates the principle of using antibody-guided molecular imaging for detection of deep organ infections in IC, without the need for invasive tissue biopsy.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 104 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 14%
Student > Master 13 13%
Student > Bachelor 9 9%
Student > Ph. D. Student 6 6%
Student > Postgraduate 5 5%
Other 13 13%
Unknown 43 41%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 16%
Medicine and Dentistry 12 12%
Immunology and Microbiology 7 7%
Agricultural and Biological Sciences 6 6%
Unspecified 3 3%
Other 13 13%
Unknown 46 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 08 September 2018.
All research outputs
#23,271,944
of 25,935,829 outputs
Outputs from Frontiers in Microbiology
#24,841
of 29,984 outputs
Outputs of similar age
#301,997
of 344,428 outputs
Outputs of similar age from Frontiers in Microbiology
#628
of 719 outputs
Altmetric has tracked 25,935,829 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,984 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 344,428 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 719 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.