ArticleMethods in molecular biology (Clifton, N.J.)2014
Assessing Pseudomonas virulence using host cells.
Article in Methods in molecular biology (Clifton, N.J.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- TheVirulence · 2026Article
- Article
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- Neural network based integration of assays to assess pathogenic potential.Scientific reports · 2023Article
- Current concepts on Pseudomonas aeruginosa interaction with human airway epithelium.PLoS pathogens · 2023Review
- Phage-resistantFrontiers in microbiology · 2022Article
- NtrBC Selectively Regulates Host-Pathogen Interactions, Virulence, and Ciprofloxacin Susceptibility ofFrontiers in cellular and infection microbiology · 2021Article
- Topological analysis of type 3 secretion translocons in native membranes.Methods in enzymology · 2021Article
- Magnetite Nanoparticles Functionalized with RNases against Intracellular Infection ofPharmaceutics · 2020Article
- Stenotrophomonas maltophilia Encodes a VirB/VirD4 Type IV Secretion System That Modulates Apoptosis in Human Cells and Promotes Competition against Heterologous Bacteria, Including Pseudomonas aeruginosa.Infection and immunity · 2019Article
- Association of biofilm formation and cytotoxic potential with multidrug resistance in clinical isolates ofEXCLI journal · 2019Article
- CLIQ-BID: A method to quantify bacteria-induced damage to eukaryotic cells by automated live-imaging of bright nuclei.Scientific reports · 2018Article
- Effect of Different Antibiotic Chemotherapies onFrontiers in microbiology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
While human or animal models are often considered the gold standard experimental system for defining virulence factors, cell culture-based infection models have proven useful for identifying important virulence factors and for examining the interactions between pathogens and the epithelial barrier. The first step in infections for most mucosal pathogens involves binding (adhesion) to the epithelial cells that line the mucosa. Successful pathogens can then penetrate the barrier by (1) inducing their uptake (i.e., "entry" or "invasion") into epithelial cells, (2) crossing the barrier by inducing epithelial cell death, and/or (3) penetrating between cells. This chapter describes growth conditions to form polarized cultures, either two-dimensional monolayers or three-dimensional cysts, of various immortalized epithelial cell lines. It describes assays to measure key early interactions between P. aeruginosa and host cells, including binding, invasion, and cytotoxicity. Many virulence factors defined by these criteria have been shown to be important for pathogenesis of P. aeruginosa infections in animals or humans. These methods are also applicable to other pathogens.
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Registered trials
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.