Evidence map›Paper›PMID 36518164›Full record

ArticleCurrent research in microbial sciences2022

Modeling the elemental stoichiometry and silicon accumulation in diatoms.

Gabrielle Armin, Keisuke Inomura

Open access · goldAbstract read
In one paragraph

Article in Current research in microbial sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 47% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Gabrielle ArminGraduate School of Oceanography, University of Rhode Island, Narragansett, RI , United States.
Keisuke InomuraGraduate School of Oceanography, University of Rhode Island, Narragansett, RI , United States.
University of Rhode Island · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diatoms are important microorganisms involved in global primary production, nutrient cycling, and carbon sequestration. A unique feature of diatoms is their silica frustules, which impact sinking speed, defense against predators and viruses, and growth cycling. Thus, frustules are inherently linked to their role in ecosystems and biogeochemical cycles. However, constraints on cellular silicon levels remain unclear and few existing models resolve diatom elemental stoichiometry to specifically include variable silicon levels. Here, we use a coarse-grained model of the diatom, Thalassiosira pseudonana, compared with laboratory results to illustrate the relationship of silicon uptake with elemental stoichiometry of other nutrients. The model-data comparison suggests the balance between growth rate and silicon uptake constrains the amount of cellular silicon. Additionally, it expresses relationships between silicon, nitrogen, phosphorus, and carbon to changing growth rates in nitrogen-limited and phosphorus-limited regimes. First, our model-data comparison suggests Si uptake hits a maximum cellular quota at low growth rates and below this maximum there is independent Si uptake. In each nutrient regime, Si:N, Si:P, and Si:C decrease exponentially with growth rate when Si is below the maximum limit. This is explained by independent Si uptake and increased loss of Si to new cells. These results provide predictions of diatom stoichiometry and allocation, which can be used in ecosystem models to differentiate phytoplankton types to better represent diatoms' contribution to global biogeochemical cycles and ecosystems.

Indexed as

BiosynthesisMacromoleculesMetabolismNutrientsPhytoplanktonProteinsQuantitative modelSilicaSilicon

Identifiers

PMID36518164
PMCPMC9743000
OpenAlexW4296517085

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.