ArticleMethods in molecular biology (Clifton, N.J.)2021
Determining Shiga Toxin-Producing Escherichia coli Interactions with Human Intestinal Epithelium in a Microaerobic Vertical Diffusion Chamber.
Article in Methods in molecular biology (Clifton, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed.
- EnterohemorrhagicInternational journal of molecular sciences · 2022Review
- Development of a novel human intestinal model to elucidate the effect of anaerobic commensals on Escherichia coli infection.Disease models & mechanisms · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The environment in the human intestine is low in oxygen. This affects virulence gene expression of enteropathogens including Shiga toxin-producing E. coli (STEC) and enables mucosal colonization by oxygen-sensitive commensal bacteria. To simulate the oxygen-restricted milieu at the intestinal epithelium, we have developed a vertical diffusion chamber model (VDC) which allows infection of polarized human intestinal epithelia under microaerobic conditions. In this chapter, we present a detailed protocol for performing STEC infections in the VDC system and subsequent analysis of STEC pathogenesis.
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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.