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Characterization of siderophores from Escherichia coli strains through genome mining tools: an antiSMASH study

Overview of attention for article published in AMB Express, June 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)

Mentioned by

twitter
3 tweeters

Readers on

mendeley
7 Mendeley
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Title
Characterization of siderophores from Escherichia coli strains through genome mining tools: an antiSMASH study
Published in
AMB Express, June 2022
DOI 10.1186/s13568-022-01421-x
Pubmed ID
Authors

Levent Cavas, Ibrahim Kirkiz

Abstract

Although urinary tract infections (UTIs) affect many people, they are usually a disease observed in women. UTIs happen when exogenous and endogenous bacteria enter the urinary tract and colonize there. Cystitis and pyelonephritis occur when bacteria infect the bladder and the kidneys, respectively. UTIs become much serious if the bacteria causing the infection are antibiotic resistant. Since the pathogenic microorganisms have been adopted to current antibiotics via genetic variations, UTIs have become an even more severe health problem. Therefore, there is a great need for the discovery of novel antibiotics. Genome mining of nonpathogenic and pathogenic Escherichia coli strains for investigating secondary metabolites were conducted by the antiSMASH analysis. When the resulting secondary metabolites were examined, it was found that some of the siderophores are effective in UTIs. In conclusion, since the siderophore production in E. coli is directly related to UTIs, these molecules can be a good target for development of future pharmaceutical approaches and compounds. Siderophores can also be used in industrial studies due to their higher chelating affinity for iron.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 43%
Unspecified 1 14%
Student > Master 1 14%
Unknown 2 29%
Readers by discipline Count As %
Unspecified 1 14%
Agricultural and Biological Sciences 1 14%
Immunology and Microbiology 1 14%
Energy 1 14%
Engineering 1 14%
Other 0 0%
Unknown 2 29%

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 21 June 2022.
All research outputs
#13,494,900
of 22,060,496 outputs
Outputs from AMB Express
#277
of 1,211 outputs
Outputs of similar age
#161,362
of 343,304 outputs
Outputs of similar age from AMB Express
#1
of 1 outputs
Altmetric has tracked 22,060,496 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,211 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done well, scoring higher than 76% 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 343,304 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them