Evidence map›Paper›PMID 21042885›Full record

ArticleMolecular biotechnology2011

Improvement of HRV quantification using cRNA-based standards for real time RT-PCR.

Maria Elena Terlizzi, Massimiliano Bergallo, Sara Astegiano, Francesca Sidoti, Stefano Gambarino, Paolo Solidoro, Cristina Costa, Rossana Cavallo

Open access · greenAbstract read
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In one paragraph

Article in Molecular biotechnology, 2011. 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
0.6field-weighted citation impact, top 33% 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, 8 citations in OpenAlex.

  1. Article
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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

8 authors at 1 institution in 1 country.

Maria Elena TerlizziVirology Unit, University Hospital San Giovanni Battista di Torino, Via Santena 9, 10126 Turin, Italy. mariaelena.terlizzi@unito.it
Massimiliano Bergallo
Sara Astegiano
Francesca Sidoti
Stefano Gambarino
Paolo Solidoro
Cristina Costa
Rossana Cavallo
Azienda Ospedaliero Universitaria San Giovanni Battista · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real Time RT-PCR developed in recent years represents an useful tool in the diagnosis of RNA viruses. In order to accurately quantify and normalize a RNA target, efficiency of reverse-transcription must be considered. In this study, a cRNA-standard-based quantitative Real Time RT-PCR have been developed for HRV quantification on bronchoalveolar lavage (BAL) specimens. Results has been compared to a quantitative plasmid standard-based Real Time RT-PCR previously developed by us. Large amount of pHRV was linearized and purified. Blunt ends were generated and cRNA production was carried out. Dilutions of cRNA were generated and dynamic range, intra- and inter-test variability, sensitivity, and limit of detection were evaluated. Sixty-seven BAL, previously resulted positive to our plasmid standard-based method, were evaluated using cRNA-standard quantification. cRNA curve showed a broad dynamic range with a good intra- and inter-test variability, with an average of 3.23 threshold cycles more in comparison to plasmid standard-based curve. In terms of specimen quantification, a difference of 1.07 log was found, showing a significant underrate using plasmid standard-based quantification. The method for cRNA-standard construction seems more suitable for quantification of RNA viruses, in order to normalize the quantification in reverse-transcription.

Indexed as

Reverse Transcriptase Polymerase Chain ReactionRhinovirusRNA, ComplementaryRNA, Complementary

Identifiers

PMID21042885
OpenAlexW2022279639

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.