Evidence map›Paper›PMID 35800243›Full record

ArticleHeliyon2022

Dynamics and growth rate implications of ribosomes and mRNAs interaction in

Tin Phan, Changhan He, Irakli Loladze, Clay Prater, Jim Elser, Yang Kuang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Review
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

6 authors.

Tin PhanSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, USA.
Changhan HeSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, USA.
Irakli LoladzeBryan Medical Center, Bryan College of Health Sciences, Lincoln, NE 68506, USA.
Clay PraterDepartment of Integrative Biology, Oklahoma State University, Stillwater, OK 74078, USA.
Jim ElserFlathead Lake Bio Station, University of Montana, Polson, MT 59860, USA.
Yang KuangSchool of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ 85287, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how cells grow and adapt under various nutrient conditions is pivotal in the study of biological stoichiometry. Recent studies provide empirical evidence that cells use multiple strategies to maintain an optimal protein production rate under different nutrient conditions. Mathematical models can provide a solid theoretical foundation that can explain experimental observations and generate testable hypotheses to further our understanding of the growth process. In this study, we generalize a modeling framework that centers on the translation process and study its asymptotic behaviors to validate algebraic manipulations involving the steady states. Using experimental results on the growth of

Indexed as

Cell growthGrowth rate hypothesisInactive ribosomesMathematical analysisModel formulationModel validationTranslation dynamics

Identifiers

PMID35800243
PMCPMC9254350

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.