Evidence map›Paper›PMID 31489337›Full record

ArticleMolecular therapy. Methods & clinical development2019

Integration of Fluorescence Detection and Image-Based Automated Counting Increases Speed, Sensitivity, and Robustness of Plaque Assays.

Allyson L Masci, Emily B Menesale, Wei-Chiang Chen, Carl Co, Xiaohui Lu, Svetlana Bergelson

Open access · goldAbstract read
In one paragraph

Article in Molecular therapy. Methods & clinical development, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

10 citing papers in PubMed, 21 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

6 authors at 1 institution in 1 country.

Allyson L MasciBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Emily B MenesaleBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Wei-Chiang ChenBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Carl CoBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Xiaohui LuBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Svetlana BergelsonBioassay and Gene Therapy, Analytical Development, Biogen, Cambridge, MA, USA.
Biogen (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plaque assays are used to measure the infectious titer of viral samples. These assays are multi-day and low-throughput and may be subject to analyst variability from biased or subjective manual plaque counting. Typically, on day 1, cells are adhered to plates overnight. On day 2, cells are infected with virus. After 3 additional days, plaques are fixed, stained with a horseradish peroxidase (HRP)-conjugated antibody and a HRP substrate, and counted by eye. Manual-based visual counting of plaques is time-consuming and laborious and may be subject to variability between analysts. Also, the assay must proceed for several days to allow the plaques to increase to sufficiently large sizes for manual identification. Here, we integrate fluorescent detection and automated plaque counting to increase the sensitivity and speed of the assay. First, we stain plaques with a fluorescent-labeled antibody. Second, we implement a plate-based cell imager to perform non-biased, non-subjective plaque counting. The integration of these two technologies decreases the assay length by 40%, from 5 days to 3 days, because plaque size, plaque signal to noise, and manual visualization are no longer limiting. This optimized plaque assay is sensitive, fast, and robust and expands the throughput and usage of this method for measuring plaque formation.

Indexed as

assay robustnessautomated countingfluorescent detectiongene therapyimage-based countingplaque assay

Identifiers

PMID31489337
PMCPMC6717064
OpenAlexW2966586524

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.