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SERPING1 mRNA overexpression in monocytes from HIV+ patients

Overview of attention for article published in Inflammation Research, September 2017
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Title
SERPING1 mRNA overexpression in monocytes from HIV+ patients
Published in
Inflammation Research, September 2017
DOI 10.1007/s00011-017-1091-x
Pubmed ID
Authors

C. Sanfilippo, D. Cambria, A. Longo, M. Palumbo, R. Avola, M. Pinzone, G. Nunnari, F. Condorelli, G. Musumeci, R. Imbesi, P. Castogiovanni, L. Malaguarnera, Michelino Di Rosa

Abstract

The HIV-1 virus activates the complement system, an essential element of the immune system. SERPING1 is a protease inhibitor that disables C1r/C1s in the C1 complex of the classical complement pathway. In this paper, we performed an analysis of several microarrays deposited in GEO dataset to demonstrate that SERPING1 mRNA is modulated in CD14(+) monocytes from HIV-1-infected individuals. In addition, data were validated on monocytes isolated from seronegative healthy volunteers, treated with IFNs. Our analysis shows that SERPING1 mRNA is overexpressed in monocytes from HIV-1+ patients and the expression levels correlate positively with viral load and negatively with the CD4(+) T-cell count. Of note, anti-retroviral therapy is able to reduce the levels of SERPING1 mRNA, ex vivo. In addition, we found that 30% of the SERPING1 genes network is upregulated in monocytes from HIV-1+ patients. Noteworthy, the expression levels of IFITM1-an antiviral molecule belonging to the genes network-correlate positively with SERPING1 expression. Interestingly, the monocytes treatment with IFN-gamma, IFN-beta and IFN-alpha significantly upregulates the SERPING1 mRNA expression levels. From the outcome of our investigation, it is possible to conclude that SERPING1 and its network serve as important components of the innate immune system to restrict HIV-1 infection.

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Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 14%
Researcher 3 14%
Student > Ph. D. Student 3 14%
Other 1 5%
Librarian 1 5%
Other 3 14%
Unknown 7 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 29%
Medicine and Dentistry 2 10%
Agricultural and Biological Sciences 2 10%
Arts and Humanities 1 5%
Veterinary Science and Veterinary Medicine 1 5%
Other 0 0%
Unknown 9 43%