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Comparative proteomics of cerebrospinal fluid reveals a predictive model for differential diagnosis of pneumococcal, meningococcal, and enteroviral meningitis, and novel putative therapeutic targets

Overview of attention for article published in BMC Genomics, May 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

patent
1 patent

Citations

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12 Dimensions

Readers on

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51 Mendeley
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Title
Comparative proteomics of cerebrospinal fluid reveals a predictive model for differential diagnosis of pneumococcal, meningococcal, and enteroviral meningitis, and novel putative therapeutic targets
Published in
BMC Genomics, May 2015
DOI 10.1186/1471-2164-16-s5-s11
Pubmed ID
Authors

Ana Paula Cordeiro, Rosiane Aparecida Silva Pereira, Alex Chapeaurouge, Clarice Semião Coimbra, Jonas Perales, Guilherme Oliveira, Talitah Michel Sanchez Candiani, Roney Santos Coimbra

Abstract

Meningitis is the inflammation of the meninges in response to infection or chemical agents. While aseptic meningitis, most frequently caused by enteroviruses, is usually benign with a self-limiting course, bacterial meningitis remains associated with high morbidity and mortality rates, despite advances in antimicrobial therapy and intensive care. Fast and accurate differential diagnosis is crucial for assertive choice of the appropriate therapeutic approach for each form of meningitis. We used 2D-PAGE and mass spectrometry to identify the cerebrospinal fluid proteome specifically related to the host response to pneumococcal, meningococcal, and enteroviral meningitis. The disease-specific proteome signatures were inspected by pathway analysis. Unique cerebrospinal fluid proteome signatures were found to the three aetiological forms of meningitis investigated, and a qualitative predictive model with four protein markers was developed for the differential diagnosis of these diseases. Nevertheless, pathway analysis of the disease-specific proteomes unveiled that Kallikrein-kinin system may play a crucial role in the pathophysiological mechanisms leading to brain damage in bacterial meningitis. Proteins taking part in this cellular process are proposed as putative targets to novel adjunctive therapies. Comparative proteomics of cerebrospinal fluid disclosed candidate biomarkers, which were combined in a qualitative and sequential predictive model with potential to improve the differential diagnosis of pneumococcal, meningococcal and enteroviral meningitis. Moreover, we present the first evidence of the possible implication of Kallikrein-kinin system in the pathophysiology of bacterial meningitis.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 16%
Student > Ph. D. Student 7 14%
Other 5 10%
Student > Bachelor 5 10%
Professor 4 8%
Other 12 24%
Unknown 10 20%
Readers by discipline Count As %
Medicine and Dentistry 16 31%
Biochemistry, Genetics and Molecular Biology 9 18%
Pharmacology, Toxicology and Pharmaceutical Science 3 6%
Veterinary Science and Veterinary Medicine 2 4%
Agricultural and Biological Sciences 2 4%
Other 6 12%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 16 August 2017.
All research outputs
#7,551,483
of 23,036,991 outputs
Outputs from BMC Genomics
#3,632
of 10,697 outputs
Outputs of similar age
#91,302
of 267,232 outputs
Outputs of similar age from BMC Genomics
#84
of 258 outputs
Altmetric has tracked 23,036,991 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,697 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 59% 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 267,232 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 56% of its contemporaries.
We're also able to compare this research output to 258 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 63% of its contemporaries.