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Forward subtractive libraries containing genes transactivated by dexamethasone in ataxia-telangiectasia lymphoblastoid cells

Overview of attention for article published in Molecular and Cellular Biochemistry, March 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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Title
Forward subtractive libraries containing genes transactivated by dexamethasone in ataxia-telangiectasia lymphoblastoid cells
Published in
Molecular and Cellular Biochemistry, March 2014
DOI 10.1007/s11010-014-2013-7
Pubmed ID
Authors

Sara Biagiotti, Michele Menotta, Elisa Giacomini, Lucia Radici, Marzia Bianchi, Cristina Bozzao, Luciana Chessa, Mauro Magnani

Abstract

Ataxia telangiectasia (A-T) is a rare autosomal recessive disorder caused by biallelic mutations in the Ataxia Telangiectasia-mutated gene. A-T shows a complex phenotype ranging from early-onset progressive neurodegeneration to immunodeficiencies, high incidence of infections, and tumors. Unfortunately, no therapy is up to now available for treating this condition. Recently, the short term treatment of ataxia-telangiectasia patients with glucocorticoids was shown to improve their neurological symptoms and possibly reverse cerebellar atrophy. Thus, corticosteroids represent an attractive approach for the treatment of this neurodegenerative disease. However, the molecular mechanism involved in glucocorticoid action in A-T is yet unknown. The aim of our work is to construct cDNA libraries containing those genes which are transactivated by the glucocorticoid analogue, dexamethasone, in A-T human cells. For this purpose, suppression subtractive hybridization has been performed on ATM-null lymphoblastoid cell transcriptome extracted following drug administration. Annotation of whole genes contained in the libraries has been obtained by coupling subtractive hybridization with microarray analysis. Positive transcripts have been validated by quantitative PCR. Through in silico analyses, identified genes have been classified on the basis of the pathway in which they are involved, being able to address signaling required for dexamethasone action. Most of the induced transcripts are involved in metabolic processes and regulation of cellular processes. Our results can help to unravel the mechanism of glucocorticoid action in the reversion of A-T phenotype. Moreover, the induction of a specific region of the ATM transcript has been identified as putative biomarker predictive of dexamethasone efficacy on ataxic patients.

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Mendeley readers

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The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 21%
Researcher 3 16%
Student > Master 2 11%
Professor 1 5%
Other 1 5%
Other 2 11%
Unknown 6 32%
Readers by discipline Count As %
Medicine and Dentistry 4 21%
Biochemistry, Genetics and Molecular Biology 2 11%
Mathematics 1 5%
Agricultural and Biological Sciences 1 5%
Psychology 1 5%
Other 3 16%
Unknown 7 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 14 April 2020.
All research outputs
#4,505,602
of 22,751,628 outputs
Outputs from Molecular and Cellular Biochemistry
#178
of 2,292 outputs
Outputs of similar age
#44,728
of 220,996 outputs
Outputs of similar age from Molecular and Cellular Biochemistry
#2
of 23 outputs
Altmetric has tracked 22,751,628 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,292 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done particularly well, scoring higher than 92% 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 220,996 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.