Evidence map›Paper›PMID 25874592›Full record

ArticleMicrobial biotechnology2015

A preliminary and qualitative study of resource ratio theory to nitrifying lab-scale bioreactors.

Micol Bellucci, Irina D Ofiţeru, Luciano Beneduce, David W Graham, Ian M Head, Thomas P Curtis

Abstract read
In one paragraph

Article in Microbial biotechnology, 2015. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Micol BellucciSchool of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK; Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università di Foggia, via Napoli 25, Foggia, 71122, Italy.
Irina D Ofiţeru
Luciano Beneduce
David W Graham
Ian M Head
Thomas P Curtis

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incorporation of microbial diversity in design would ideally require predictive theory that would relate operational parameters to the numbers and distribution of taxa. Resource ratio-theory (RRT) might be one such theory. Based on Monod kinetics, it explains diversity in function of resource-ratio and richness. However, to be usable in biological engineered system, the growth parameters of all the bacteria under consideration and the resource supply and diffusion parameters for all the relevant nutrients should be determined. This is challenging, but plausible, at least for low diversity groups with simple resource requirements like the ammonia oxidizing bacteria (AOB). One of the major successes of RRT was its ability to explain the 'paradox of enrichment' which states that diversity first increases and then decreases with resource richness. Here, we demonstrate that this pattern can be seen in lab-scale-activated sludge reactors and parallel simulations that incorporate the principles of RRT in a floc-based system. High and low ammonia and oxygen were supplied to continuous flow bioreactors with resource conditions correlating with the composition and diversity of resident AOB communities based on AOB 16S rDNA clone libraries. Neither the experimental work nor the simulations are definitive proof for the application of RRT in this context. However, it is sufficient evidence that such approach might work and justify a more rigorous investigation.

Indexed as

BiodiversityNitrificationAmmoniaBacteriaBioreactorsCluster AnalysisComputer SimulationCulture MediaDNA, RibosomalModels, BiologicalMolecular Sequence DataOxygenPhylogenyRNA, Ribosomal, 16SSequence Analysis, DNASewageAmmoniaCulture MediaDNA, RibosomalOxygenRNA, Ribosomal, 16SSewage

Identifiers

PMID25874592
PMCPMC4408191

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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.