Evidence map›Paper›PMID 37112978›Full record

ArticleViruses2023

Evaluating Novel Quantification Methods for Infectious Baculoviruses.

Keven Lothert, Elena Bagrin, Michael W Wolff

Abstract read
In one paragraph

Article in Viruses, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

3 authors.

Keven LothertInstitute of Bioprocess Engineering and Pharmaceutical Technology, Department Life Science Engineering, University of Applied Sciences Mittelhessen (THM), 35390 Giessen, Germany.ORCID 0000-0002-8930-9834
Elena BagrinInstitute of Bioprocess Engineering and Pharmaceutical Technology, Department Life Science Engineering, University of Applied Sciences Mittelhessen (THM), 35390 Giessen, Germany.
Michael W WolffInstitute of Bioprocess Engineering and Pharmaceutical Technology, Department Life Science Engineering, University of Applied Sciences Mittelhessen (THM), 35390 Giessen, Germany.ORCID 0000-0001-7443-3122

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate and rapid quantification of (infectious) virus titers is of paramount importance in the manufacture of viral vectors and vaccines. Reliable quantification data allow efficient process development at a laboratory scale and thorough process monitoring in later production. However, current gold standard applications, such as endpoint dilution assays, are cumbersome and do not provide true process analytical monitoring. Accordingly, flow cytometry and quantitative polymerase chain reaction have attracted increasing interest in recent years, offering various advantages for rapid quantification. Here, we compared different approaches for the assessment of infectious viruses, using a model baculovirus. Firstly, infectivity was estimated by the quantification of viral nucleic acids in infected cells, and secondly, different flow cytometric approaches were investigated regarding analysis times and calibration ranges. The flow cytometry technique included a quantification based on post-infection fluorophore expression and labeling of a viral surface protein using fluorescent antibodies. Additionally, the possibility of viral (m)RNA labeling in infected cells was investigated as a proof of concept. The results confirmed that infectivity assessment based on qPCR is not trivial and requires sophisticated method optimization, whereas staining of viral surface proteins is a fast and feasible approach for enveloped viruses. Finally, labeling of viral (m)RNA in infected cells appears to be a promising opportunity but will require further research.

Indexed as

BaculoviridaeGenetic VectorsRNARNAflow cytometrygp64 proteininfectivity titernative baculovirusprocess monitoringquantitative polymerase chain reactionviral RNAvirus quantification

Identifiers

PMID37112978
PMCPMC10141099

What OpenQuestion holds

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Registered trials

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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.