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Optimization of the production and characterization of milk clotting enzymes by Bacillus subtilis natto

Overview of attention for article published in SpringerPlus, January 2013
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  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

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Title
Optimization of the production and characterization of milk clotting enzymes by Bacillus subtilis natto
Published in
SpringerPlus, January 2013
DOI 10.1186/2193-1801-2-33
Pubmed ID
Authors

Fang-Chen Wu, Chen-Wei Chang, Ing-Lung Shih

Abstract

Suitable medium for production of milk clotting enzyme (MCE) by Bacillus subtilis (natto) Takahashi in submerged liquid-state fermentation was screened, the nutrient factors affecting MCE production was optimized by response surface methodology. The MCE production by B. subtilis (natto) Takahashi was increased significantly by 428% in the optimal medium developed. The MCE was filtered and concentrated by ultrafiltration. The retentate after tandem filtration carried out with the combined membranes of MWCO 50kDa and 5 kDa showed two major bands between 25kDa and 30kDa on SDS-PAGE, and the MCA and MCA/PA improved significantly in comparison with those in the initial broth. The crude enzyme thus obtained showed MCA and MCA/PA ratio of 48,000 SU/g and 6,400, which are commensurate with those (MCA 26,667 SU/g and MCA/PA 6,667) of the commercial rennet. It had optimal pH and temperature at pH 6 and 60°C, and showed excellent pH and thermal stability.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 3%
Chile 1 3%
India 1 3%
Germany 1 3%
Unknown 36 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 20%
Student > Ph. D. Student 6 15%
Student > Bachelor 6 15%
Researcher 5 13%
Professor > Associate Professor 3 8%
Other 5 13%
Unknown 7 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 30%
Chemistry 6 15%
Biochemistry, Genetics and Molecular Biology 6 15%
Engineering 2 5%
Materials Science 2 5%
Other 5 13%
Unknown 7 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 April 2021.
All research outputs
#17,677,535
of 22,694,633 outputs
Outputs from SpringerPlus
#1,202
of 1,852 outputs
Outputs of similar age
#210,769
of 282,272 outputs
Outputs of similar age from SpringerPlus
#43
of 102 outputs
Altmetric has tracked 22,694,633 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 32nd percentile – i.e., 32% of its peers scored the same or lower than it.
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 282,272 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.