Evidence map›Paper›PMID 29308273›Full record

ArticleRoyal Society open science2017

Bacterial bioluminescence onset and quenching: a dynamical model for a

Domenico Delle Side, Vincenzo Nassisi, Cecilia Pennetta, Pietro Alifano, Marco Di Salvo, Adelfia Talà, Aleksei Chechkin, Flavio Seno, Antonio Trovato

Open access · goldAbstract read
In one paragraph

Article in Royal Society open science, 2017. 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
0.7field-weighted citation impact, top 30% 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, 10 citations in OpenAlex.

  1. Article
  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

9 authors at 2 institutions in 3 countries.

Domenico Delle SideDipartimento di Matematica e Fisica 'Ennio De Giorgi', Università del Salento, Lecce, Italy.
Vincenzo NassisiDipartimento di Matematica e Fisica 'Ennio De Giorgi', Università del Salento, Lecce, Italy.
Cecilia PennettaDipartimento di Matematica e Fisica 'Ennio De Giorgi', Università del Salento, Lecce, Italy.
Pietro AlifanoDipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, Lecce, Italy.
Marco Di SalvoDipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, Lecce, Italy.
Adelfia TalàDipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, Lecce, Italy.
Aleksei ChechkinAkhiezer Institute for Theoretical Physics, Kharkov Institute of Physics and Technology, Kharkov 61108, Ukraine.
Flavio SenoDipartimento di Fisica e Astronomia 'Galileo Galilei', Università di Padova, Padova, Italy.
Antonio TrovatoDipartimento di Fisica e Astronomia 'Galileo Galilei', Università di Padova, Padova, Italy.ORCID 0000-0002-1596-9477
University of Salento · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present an effective dynamical model for the onset of bacterial bioluminescence, one of the most studied quorum sensing-mediated traits. Our model is built upon simple equations that describe the growth of the bacterial colony, the production and accumulation of autoinducer signal molecules, their sensing within bacterial cells, and the ensuing quorum activation mechanism that triggers bioluminescent emission. The model is directly tested to quantitatively reproduce the experimental distributions of photon emission times, previously measured for bacterial colonies of

Indexed as

bioluminescencebiophysical modelGompertz growth functionHarveyi cladeoxygen quenchingquorum sensing

Identifiers

PMID29308273
PMCPMC5750040
OpenAlexW2775439073

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.