Evidence map›Paper›PMID 22392139›Full record

ArticleParasitology research2012

Detection and characterization of Cryptosporidium cuniculus by real-time PCR.

Stephen J Hadfield, Rachel M Chalmers

Abstract read
PubMed Publisher
In one paragraph

Article in Parasitology research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 12% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. An Update on ZoonoticAnimals : an open access journal from MDPI · 2021
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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.

Stephen J HadfieldUK Cryptosporidium Reference Unit, Public Health Wales Microbiology, Singleton Hospital, Sketty, Swansea, SA2 8QA, United Kingdom.
Rachel M Chalmers
Public Health Wales · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cryptosporidium cuniculus was originally detected in rabbits and has been identified as an emerging human pathogen, but the occurrence, prevalence, and epidemiology in human and rabbit populations are poorly understood. As identification of C. cuniculus can be time-consuming and costly using existing molecular assays, a real-time polymerase chain reaction (PCR)-based method targeting specific markers for this species was developed. The assay is based on amplification of the C. cuniculus-specific 60-kDa glycoprotein (GP60) gene using two PCRs targeting subtype families Va and Vb. PCR product formation was monitored by SYBR Green I fluorescence measurement followed by post-amplification melt curve analysis; high resolution melt curve analysis was found to give increased sensitivity over standard melt curve analysis. The real-time PCR correctly identified all 41 C. cuniculus isolates (40 from humans, one from a rabbit) tested, with subtype family in agreement with GP60 gene sequencing. Specificity was demonstrated by lack of detection of nine other Cryptosporidium species and genotypes, including 88 isolates of the closely related species, Cryptosporidium hominis. The PCRs were performed in separate tubes to maximize the possibility of detecting mixed Va-Vb infections; however, none were detected. The potential for multiplexing the reactions was also demonstrated, furthering the utility of the assay for large-scale occurrence and prevalence studies.

Indexed as

AnimalsCryptosporidiosisCryptosporidiumDNA, ProtozoanNucleic Acid DenaturationRabbitsReal-Time Polymerase Chain ReactionReproducibility of ResultsSensitivity and SpecificityDNA, Protozoan

Identifiers

PMID22392139
OpenAlexW2055484162

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.