Evidence map›Paper›PMID 25243370›Full record

ArticleViruses2014

A filtration based technique for simultaneous SEM and TEM sample preparation for the rapid detection of pathogens.

Daniel R Beniac, Christine G Siemens, Christine J Wright, Tim F Booth

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2014. 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
0.9field-weighted citation impact, top 23% 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, 32 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

4 authors at 2 institutions in 1 country.

Daniel R BeniacViral Diseases Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3P6, Canada. daniel.beniac@phac-aspc.gc.ca.
Christine G SiemensViral Diseases Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3P6, Canada. christine.siemens@phac-aspc.gc.ca.
Christine J WrightViral Diseases Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3P6, Canada. christine.j.wright@phac-aspc.gc.ca.
Tim F BoothViral Diseases Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB R3E 3P6, Canada. tim.booth@phac-aspc.gc.ca.
Public Health Agency of Canada · CAUniversity of Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diagnostic electron microscopy for infectious diseases has the advantage that "everything" in the specimen can be observed, without a priori knowledge of the likely identity of the microorganisms present in the sample. The classical specimen preparation method used employs a droplet of sample, which allows particles to adsorb to a support film, and is subsequently negative stained. This "grid on drop" procedure has a sensitivity range of approximately 106 viruses per mL if no enrichment procedures are used. In the current investigation we present a novel use of filtration that allows us to detect viruses at concentrations as low as 102 viruses per mL. We present here methods based on filtration, in which total virus, and not virus concentration, is the limiting factor for detection. We show that filtration is more sensitive than conventional negative staining and can detect as few as 5 × 103 particles per sample.

Indexed as

AnimalsBacteriophagesCell LineChlorocebus aethiopsCricetinaeFiltrationLeptospiraMicroscopy, Electron, ScanningMicroscopy, Electron, TransmissionVero CellsViruses

Identifiers

PMID25243370
PMCPMC4189033
OpenAlexW1974771539

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.