Evidence map›Paper›PMID 16954262›Full record

ArticleJournal of clinical microbiology2006

Rapid and sensitive detection of single cryptosporidium oocysts from archived glass slides.

O Sunnotel, W J Snelling, L Xiao, K Moule, J E Moore, B Cherie Millar, J S G Dooley, C J Lowery

Abstract read
In one paragraph

Article in Journal of clinical microbiology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Prevalence ofElectronic physician · 2017
    Article
  3. Article
  4. Article
  5. Article
  6. Occurrence of Giardia and Cryptosporidium in Italian water supplies.Environmental monitoring and assessment · 2009
    Article
  7. Article
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.

O SunnotelDepartment of Biomedical Sciences, Centre for Molecular Biosciences, School of Biomedical Sciences, Faculty of Life and Health Sciences, University of Ulster, Cromore Road, Coleraine, Northern Ireland BT52 1SA.
W J Snelling
L Xiao
K Moule
J E Moore
B Cherie Millar
J S G Dooley
C J Lowery

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study we report on the development and application of a novel method for efficiently extracting and detecting single Cryptosporidium oocysts from archived glass slides. Laser capture microscopy was used to extract low numbers of oocysts from archived glass slides. Highly sensitive real-time PCR methods were then developed to enable the rapid detection and identification of Cryptosporidium oocysts from these samples. The method was applied to fecal smears stained with a variety of standard oocyst stains and water samples. This application, with samples derived from both public health and water service laboratories, highlighted the strong potential of this method to be used as a rapid high-throughput screening tool for the routine monitoring of Cryptosporidium and other medically important pathogens from clinical, veterinary, and environmental water samples. Importantly, the application of our protocol could be used to type Cryptosporidium and other pathogens from stored archived glass slides in public health and water service laboratories, providing vital epidemiological updates and helping to identify and trace pathogens and their routes of infection and ultimately improve their control.

Indexed as

AnimalsCryptosporidiumDNA, ProtozoanFecesGlassHumansMicroscopy, ConfocalMolecular Sequence DataOocystsPolymerase Chain ReactionSensitivity and SpecificityTime FactorsWater SupplyDNA, Protozoan

Identifiers

PMID16954262
PMCPMC1594691

What OpenQuestion holds

Textmetadata
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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.