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Early prediction of cerebral malaria by 1H NMR based metabolomics

Overview of attention for article published in Malaria Journal, April 2016
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Title
Early prediction of cerebral malaria by 1H NMR based metabolomics
Published in
Malaria Journal, April 2016
DOI 10.1186/s12936-016-1256-z
Pubmed ID
Authors

Soumita Ghosh, Arjun Sengupta, Shobhona Sharma, Haripalsingh M. Sonawat

Abstract

Cerebral malaria (CM) is a life-threatening disease, caused mainly by Plasmodium falciparum in humans. In adults only 1-2 % of P. falciparum-infected hosts transit to the cerebral form of the disease while most exhibit non-cerebral malaria (NCM). The perturbed metabolic pathways of CM and NCM have been reported. Early marker(s) of CM is(are) not known and by the time a patient exhibits the pathological symptoms of CM, the disease has progressed. Murine CM, like the human disease, is difficult to assign to specific animals at early stage and hence the challenge to treat CM at pre-clinical stage of the disease. This is the first report of prediction of CM in mice using a novel strategy based on (1)H nuclear magnetic resonance (NMR)-based metabolomics. Mice were infected with malarial parasites, and serum was collected from all the animals (CM/NCM) before CM symptoms were apparent. The assignment of mice as NCM/CM at an early time point is based on their symptoms at days 8-9 post-infection (pi). The serum samples were subjected to (1)H NMR-based metabolomics. (1)H NMR spectra of the serum samples, collected at various time points (pi) in multiple sets of experiments, were subjected to multivariate analyses. The results from orthogonal partial least square discriminant analyses (OPLS-DA) suggest that the animals with CM start to diverge out in metabolic profile and were distinct on day 4 pi, although by physical observation they were indistinguishable from the NCM. The metabolites that appeared to contribute to this distinction were serum lipids and lipoproteins, and 14-19 % enhancement was observed in mice afflicted with CM. A cut-off of 14 % change of total lipoproteins in serum predicts 54-71 % CM in different experiments at day 4 pi. This study clearly demonstrates the possibility of differentiating and identifying animals with CM at an early, pre-clinical stage. The strategy, based on metabolite profile of serum, tested with different batches of animals in both the sex and across different times of the year, is found to be robust. This is the first such study of pre-clinical prognosis of CM.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 3%
Brazil 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 32%
Student > Bachelor 5 14%
Researcher 4 11%
Student > Master 4 11%
Student > Postgraduate 3 8%
Other 3 8%
Unknown 6 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 19%
Medicine and Dentistry 6 16%
Computer Science 3 8%
Immunology and Microbiology 3 8%
Biochemistry, Genetics and Molecular Biology 2 5%
Other 7 19%
Unknown 9 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 19 April 2016.
All research outputs
#14,718,157
of 22,865,319 outputs
Outputs from Malaria Journal
#4,205
of 5,573 outputs
Outputs of similar age
#168,836
of 300,904 outputs
Outputs of similar age from Malaria Journal
#136
of 175 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,573 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 23rd percentile – i.e., 23% 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 300,904 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 175 others from the same source and published within six weeks on either side of this one. This one is in the 21st percentile – i.e., 21% of its contemporaries scored the same or lower than it.