Evidence map›Paper›PMID 28749991›Full record

ArticlePloS one2017

Nanofluidic digital PCR for the quantification of Norovirus for water quality assessment.

Silvia Monteiro, Ricardo Santos

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

14 citing papers in PubMed, 39 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

2 authors at 1 institution in 1 country.

Silvia MonteiroInstituto Superior Técnico, Laboratório Analises, Universidade Lisboa, Lisbon, Portugal.ORCID http://orcid.org/0000-0002-9943-0742
Ricardo SantosInstituto Superior Técnico, Laboratório Analises, Universidade Lisboa, Lisbon, Portugal.
Instituto Politécnico de Lisboa · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensitive detection of water- and foodborne enteric viruses is extremely relevant, especially due to the low concentrations in which they are found. Accurate and sensitive detection of Norovirus, the primary responsible for water- and foodborne outbreaks, is of particular importance. Quantification of Norovirus is commonly performed by quantitative RT-PCR (RT-qPCR). In recent years a new platform was developed, digital PCR, that quantifies without the need for a standard curve thus decreasing the errors associated with its utilization. The platform developed by LifeTechnologies, QuantStudio 3D Digital PCR is amongst the least studied digital platform and although it allows the direct detection of DNA targets it requires a two-step RT-PCR for the detection of RNA targets. In this work we developed a new protocol able to detect Norovirus using a one-step digital PCR reaction (RT-dPCR). The performance of the newly developed one-step digital PCR was compared to RT-qPCR for the detection of Norovirus genogroup I and genogroup II. The sensitivity of RT-dPCR was identical to that of RT-qPCR, and the quantitative data determined by both methods were not significantly different for most samples. This one-step absolute quantification approach is a useful tool to minimize the time spent currently using this particular platform to amplify viral RNA and to standardize quantification of enteric viruses in food and environmental samples. This study proved the usefulness of the newly developed RT-dPCR protocol for a sensitive and accurate detection of low-copy targets.

Indexed as

Water MicrobiologyWater QualityLimit of DetectionNanotechnologyNorovirusReal-Time Polymerase Chain ReactionRegression AnalysisRNA, ViralWastewaterRNA, ViralWastewater

Identifiers

PMID28749991
PMCPMC5531372
OpenAlexW2741737544

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.