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MicroRNA Fingerprints Identify miR-150 as a Plasma Prognostic Marker in Patients with Sepsis

Overview of attention for article published in PLOS ONE, October 2009
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Title
MicroRNA Fingerprints Identify miR-150 as a Plasma Prognostic Marker in Patients with Sepsis
Published in
PLOS ONE, October 2009
DOI 10.1371/journal.pone.0007405
Pubmed ID
Authors

Catalin Vasilescu, Simona Rossi, Masayoshi Shimizu, Stefan Tudor, Angelo Veronese, Manuela Ferracin, Milena S. Nicoloso, Elisa Barbarotto, Monica Popa, Oana Stanciulea, Michael H. Fernandez, Dan Tulbure, Carlos E. Bueso-Ramos, Massimo Negrini, George A. Calin

Abstract

The physiopathology of sepsis continues to be poorly understood, and despite recent advances in its management, sepsis is still a life-threatening condition with a poor outcome. If new diagnostic markers related to sepsis pathogenesis will be identified, new specific therapies might be developed and mortality reduced. Small regulatory non-coding RNAs, microRNAs (miRNAs), were recently linked to various diseases; the aim of our prospective study was to identify miRNAs that can differentiate patients with early-stage sepsis from healthy controls and to determine if miRNA levels correlate with the severity assessed by the Sequential Organ Failure Assessment (SOFA) score.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 185 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Germany 2 1%
China 1 <1%
Unknown 180 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 45 24%
Student > Ph. D. Student 26 14%
Student > Master 26 14%
Student > Bachelor 16 9%
Student > Doctoral Student 12 6%
Other 37 20%
Unknown 23 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 31%
Medicine and Dentistry 44 24%
Biochemistry, Genetics and Molecular Biology 25 14%
Immunology and Microbiology 8 4%
Engineering 3 2%
Other 19 10%
Unknown 29 16%