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A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures

Overview of attention for article published in Microbial Cell Factories, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#42 of 1,802)
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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1 news outlet
twitter
2 X users
patent
3 patents

Citations

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38 Dimensions

Readers on

mendeley
148 Mendeley
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Title
A novel process-based model of microbial growth: self-inhibition in Saccharomyces cerevisiae aerobic fed-batch cultures
Published in
Microbial Cell Factories, July 2015
DOI 10.1186/s12934-015-0295-4
Pubmed ID
Authors

Stefano Mazzoleni, Carmine Landi, Fabrizio Cartenì, Elisabetta de Alteriis, Francesco Giannino, Lucia Paciello, Palma Parascandola

Abstract

Microbial population dynamics in bioreactors depend on both nutrients availability and changes in the growth environment. Research is still ongoing on the optimization of bioreactor yields focusing on the increase of the maximum achievable cell density. A new process-based model is proposed to describe the aerobic growth of Saccharomyces cerevisiae cultured on glucose as carbon and energy source. The model considers the main metabolic routes of glucose assimilation (fermentation to ethanol and respiration) and the occurrence of inhibition due to the accumulation of both ethanol and other self-produced toxic compounds in the medium. Model simulations reproduced data from classic and new experiments of yeast growth in batch and fed-batch cultures. Model and experimental results showed that the growth decline observed in prolonged fed-batch cultures had to be ascribed to self-produced inhibitory compounds other than ethanol. The presented results clarify the dynamics of microbial growth under different feeding conditions and highlight the relevance of the negative feedback by self-produced inhibitory compounds on the maximum cell densities achieved in a bioreactor.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users 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 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 <1%
Sweden 1 <1%
India 1 <1%
Mexico 1 <1%
Denmark 1 <1%
China 1 <1%
Spain 1 <1%
Unknown 141 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 18%
Student > Bachelor 27 18%
Researcher 22 15%
Student > Master 16 11%
Student > Doctoral Student 7 5%
Other 16 11%
Unknown 33 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 26%
Biochemistry, Genetics and Molecular Biology 26 18%
Chemical Engineering 18 12%
Chemistry 9 6%
Engineering 8 5%
Other 12 8%
Unknown 37 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 10 January 2024.
All research outputs
#1,746,519
of 25,139,853 outputs
Outputs from Microbial Cell Factories
#42
of 1,802 outputs
Outputs of similar age
#21,826
of 268,886 outputs
Outputs of similar age from Microbial Cell Factories
#2
of 32 outputs
Altmetric has tracked 25,139,853 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,802 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 268,886 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 32 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 96% of its contemporaries.