Evidence map›Paper›PMID 35205164›Full record

ArticleBiology2022

A Computational Model of Bacterial Population Dynamics in Gastrointestinal

Janina K Geißert, Erwin Bohn, Reihaneh Mostolizadeh, Andreas Dräger, Ingo B Autenrieth, Sina Beier, Oliver Deusch, Alina Renz, Martin Eichner, Monika S Schütz

Open access · goldAbstract read
In one paragraph

Article in Biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 34% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

10 authors at 3 institutions in 1 country.

Janina K GeißertInstitute for Medical Microbiology and Hygiene, University Hospital Tübingen, Elfriede-Aulhorn-Str. 6, 72076 Tübingen, Germany.ORCID 0000-0003-1937-7054
Erwin BohnInstitute for Medical Microbiology and Hygiene, University Hospital Tübingen, Elfriede-Aulhorn-Str. 6, 72076 Tübingen, Germany.
Reihaneh MostolizadehComputational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Sand 14, 72076 Tübingen, Germany.ORCID 0000-0003-2479-6851
Andreas DrägerComputational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Sand 14, 72076 Tübingen, Germany.ORCID 0000-0002-1240-5553
Ingo B AutenriethInstitute for Medical Microbiology and Hygiene, University Hospital Tübingen, Elfriede-Aulhorn-Str. 6, 72076 Tübingen, Germany.
Sina BeierDepartment of Computer Science, University of Tübingen, Sand 14, 72076 Tübingen, Germany.
Oliver DeuschCEMET GmbH, Eisenbahnstr. 63, 72072 Tübingen, Germany.
Alina RenzComputational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Sand 14, 72076 Tübingen, Germany.ORCID 0000-0003-3851-9978
Martin EichnerEpimos GmbH, Frühlingstraße 2, 97653 Bischofsheim in der Rhön, Germany.
Monika S SchützInstitute for Medical Microbiology and Hygiene, University Hospital Tübingen, Elfriede-Aulhorn-Str. 6, 72076 Tübingen, Germany.ORCID 0000-0002-4086-7800
German Center for Infection Research · DEUniversity of Tübingen · DEInstitute of Medical Microbiology and Hygiene · DE

Funding

Deutsche Forschungsgemeinschaft AU 102/16-1Deutsche Forschungsgemeinschaft EXC 2124-390838134Federal Ministry of Education and Research 031 A535AGerman Center for Infection Research 8020708703
6 · The paper itself

Abstract

The complex interplay of a pathogen with its virulence and fitness factors, the host's immune response, and the endogenous microbiome determine the course and outcome of gastrointestinal infection. The expansion of a pathogen within the gastrointestinal tract implies an increased risk of developing severe systemic infections, especially in dysbiotic or immunocompromised individuals. We developed a mechanistic computational model that calculates and simulates such scenarios, based on an ordinary differential equation system, to explain the bacterial population dynamics during gastrointestinal infection. For implementing the model and estimating its parameters, oral mouse infection experiments with the enteropathogen,

Indexed as

computational modelinggastrointestinal infectioninfectionordinary differential equationsparameter estimationpopulation dynamicssystems biologyYersinia enterocolitica

Identifiers

PMID35205164
PMCPMC8869254
OpenAlexW4213380937

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.