Evidence map›Paper›PMID 33378939›Full record

ArticleMathematical biosciences and engineering : MBE2020

Mathematical modeling of population structure in bioreactors seeded with light-controllable microbial stem cells.

Dane Patey, Nikolai Mushnikov, Grant Bowman, Rongsong Liu

Open access · goldAbstract read
In one paragraph

Article in Mathematical biosciences and engineering : MBE, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 87% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Dane PateyDepartment of Mathematics and Statisitics, University of Wyoming, 1000 E. University, Laramie, WY 82071, USA.
Nikolai MushnikovDepartment of Molecular Biology, University of Wyoming, 1000 E. University, Laramie, WY 82071, USA.
Grant BowmanDepartment of Molecular Biology, University of Wyoming, 1000 E. University, Laramie, WY 82071, USA.
Rongsong LiuDepartment of Mathematics and Statisitics, University of Wyoming, 1000 E. University, Laramie, WY 82071, USA.
University of Wyoming · US

Funding

Bacterial Mechanisms for Establishing and Maintaining Cell PolarityR01GM118792 · NIGMS · UNIVERSITY OF WYOMING · PI BOWMAN, GRANT ROBERT · 2016 to 2019
$821k
NIGMS NIH HHS R01 GM118792
6 · The paper itself

Abstract

Industrial bioreactors use microbial organisms as living factories to produce a wide range of commercial products. For most applications, yields eventually become limited by the proliferation of "escape mutants" that acquire a growth advantage by losing the ability to make product. The goal of this work is to use mathematical models to determine whether this problem could be addressed in continuous flow bioreactors that include a "stem cell" population that multiplies rapidly and could be used to compete against the emergence of cheater mutants. In this system, external stimuli can be used to induce stem cell multiplication through symmetric cell division, or to limit stem cell multiplication and induce higher production through an asymmetric cell division that produces one stem cell and one new product-producing "factory cell". Our results show product yields from bioreactors with microbial stem cells can be increased by 18% to 127% over conventional methods, and sensitivity analysis shows that yields could be improved over a broad range of parameter space.

Indexed as

BioreactorsModels, TheoreticalCell DivisionCell ProliferationStem Cellscell divisionmathematical modelsmutantpopulation dynamics

Identifiers

PMID33378939
PMCPMC9714318
OpenAlexW3103809744

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.