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p53: key conductor of all anti-acne therapies

Overview of attention for article published in Journal of Translational Medicine, September 2017
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2 tweeters
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1 Redditor

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53 Mendeley
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Title
p53: key conductor of all anti-acne therapies
Published in
Journal of Translational Medicine, September 2017
DOI 10.1186/s12967-017-1297-2
Pubmed ID
Authors

Bodo C. Melnik

Abstract

This review based on translational research predicts that the transcription factor p53 is the key effector of all anti-acne therapies. All-trans retinoic acid (ATRA) and isotretinoin (13-cis retinoic acid) enhance p53 expression. Tetracyclines and macrolides via inhibiting p450 enzymes attenuate ATRA degradation, thereby increase p53. Benzoyl peroxide and hydrogen peroxide elicit oxidative stress, which upregulates p53. Azelaic acid leads to mitochondrial damage associated with increased release of reactive oxygen species inducing p53. p53 inhibits the expression of androgen receptor and IGF-1 receptor, and induces the expression of IGF binding protein 3. p53 induces FoxO1, FoxO3, p21 and sestrin 1, sestrin 2, and tumour necrosis factor-related apoptosis-inducing ligand (TRAIL), the key inducer of isotretinoin-mediated sebocyte apoptosis explaining isotretinoin's sebum-suppressive effect. Anti-androgens attenuate the expression of miRNA-125b, a key negative regulator of p53. It can thus be concluded that all anti-acne therapies have a common mode of action, i.e., upregulation of the guardian of the genome p53. Immortalized p53-inactivated sebocyte cultures are unfortunate models for studying acne pathogenesis and treatment.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 15%
Student > Ph. D. Student 7 13%
Other 5 9%
Student > Master 5 9%
Researcher 5 9%
Other 7 13%
Unknown 16 30%
Readers by discipline Count As %
Medicine and Dentistry 17 32%
Biochemistry, Genetics and Molecular Biology 7 13%
Immunology and Microbiology 3 6%
Engineering 2 4%
Nursing and Health Professions 1 2%
Other 5 9%
Unknown 18 34%

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 05 June 2019.
All research outputs
#12,481,071
of 20,189,078 outputs
Outputs from Journal of Translational Medicine
#1,574
of 3,526 outputs
Outputs of similar age
#154,961
of 291,499 outputs
Outputs of similar age from Journal of Translational Medicine
#2
of 2 outputs
Altmetric has tracked 20,189,078 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,526 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.8. This one has gotten more attention than average, scoring higher than 50% 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 291,499 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 2 others from the same source and published within six weeks on either side of this one.