Evidence map›Paper›PMID 20456527›Full record

ArticleJournal of applied microbiology2010

Detection limit of negative staining electron microscopy for the diagnosis of bioterrorism-related micro-organisms.

M Laue, N Bannert

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of applied microbiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.8field-weighted citation impact, top 17% 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, 56 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.

M LaueCentre for Biological Safety 4, Robert Koch Institute, Berlin, Germany. michael.laue@med.uni-rostock.de
N Bannert
Robert Koch Institute · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo determine the detection limit of diagnostic negative staining electron microscopy for the diagnosis of pathogens that could be used for bioterrorism. METHODS AND

resultsSuspensions of vaccinia poxvirus and endospores of Bacillus subtilis were used at defined concentrations as a model for poxviruses and spores of anthrax (Bacillus anthracis), both of which are pathogens that could be used for bioterrorist attacks. Negative staining electron microscopy was performed directly or after sedimentation of these suspensions on to the sample supports using airfuge ultracentrifugation. For both virus and spores, the detection limit using direct adsorption of a 10-μl sample volume onto the sample support was 10(6) particles per ml. Using airfuge ultracentrifugation with a sample volume of 80 μl, the detection limit could be reduced to 10(5) particles per ml for spores and to 5 × 10(4) particles per ml for poxviruses. The influence on particle detection of incubation time, washing and adsorption procedures was investigated.

conclusionsThe reproducibility and sensitivity of the method were acceptable, particularly considering the small sample volume and low particle number applied onto the sample support. SIGNIFICANCE AND IMPACT OF THE STUDY: Diagnostic negative staining electron microscopy is used for the diagnosis of pathogens in emergency situations because it allows a rapid examination of all particulate matter down to the nanometre scale. This study provides precise detection limit for the method, an important factor for the validation and improvement of the technique.

Indexed as

BioterrorismBacillus subtilisLimit of DetectionMicroscopy, ElectronNegative StainingPoxviridaeSpores, BacterialVirion

Identifiers

PMID20456527
PMCPMC7197746
OpenAlexW1486365184

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.