Evidence map›Paper›PMID 32514926›Full record

ReviewEnvironmental science and pollution research international2020

The effects of silver nanoparticles on the microbial nitrogen cycle: a review of the known risks.

Conor Francis McGee

Abstract readReview
PubMed Publisher
In one paragraph

Review in Environmental science and pollution research international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

9 citing papers in PubMed, 47 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Conor Francis McGeeDepartment of Agriculture, Food and the Marine, Cellbridge, Co. Kildare, Ireland. conorfmcgee@gmail.com.ORCID http://orcid.org/0000-0002-7683-1623
Department of Agriculture Food and the Marine · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The nitrogen cycle is an integral biogeochemical function for maintaining healthy environments. Nitrogen is a key nutrient that must be continuously replenished through recycling mechanisms to sustain ecosystems, disruption to which can result in compromised ecosystem functioning. Certain stages in the microbial conversion of nitrogen compounds are performed by a limited range of micro-organisms making these key functional species in ecosystems. The growing industrial use of silver nanoparticles (AgNPs) potentially poses significant risks for microbial nitrogen cycling species. AgNPs possess potent antimicrobial properties and are expected to reach a range of natural environments through several routes of exposure. Certain functional nitrogen cycling microbes have been shown to be highly susceptible to AgNP toxicity. The current literature indicates that AgNPs can negatively affect certain nitrogen fixing, nitrifying and denitrifying microbes in vitro. In vivo studies investigating the effect of AgNPs on nitrogen cycling microbial communities and nitrogen transformation rates in soil, sediment and sludge environments have also indicated disruption of these functional processes. This review provides a comprehensive description of the current state of knowledge regarding the toxicity of AgNPs to nitrogen cycling communities. The aim of the review is to highlight the most susceptible stages in the nitrogen cycle and the implications for the affected ecosystems.

Indexed as

Metal NanoparticlesNitrogen CycleSewageSilverSoilSewageSilverSoilAgNPEcotoxicologyMicrobial ecologyNitrogen cycleSilver

Identifiers

PMID32514926
OpenAlexW3033632383

What OpenQuestion holds

Textmetadata
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.