ReviewCytometry. Part A : the journal of the International Society for Analytical Cytology2016
Contribution of high-content imaging technologies to the development of anti-infective drugs.
Review in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- High-throughput screening and meta-analysis for lead compounds in antimalarial drug discovery.Malaria journal · 2025Pooled it
- High-Content Screening for Cryptosporidium Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2026Article
- High-Content Imaging to Phenotype Antimicrobial Effects on Individual Bacteria at Scale.mSystems · 2021Article
- Technologies for High-Throughput Identification of Antibiotic Mechanism of Action.Antibiotics (Basel, Switzerland) · 2021Review
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Originally developed to study fundamental aspects of cellular biology, high-content imaging (HCI) was rapidly adapted to study host-pathogen interactions at the cellular level and adopted as a technology of choice to unravel disease biology. HCI platforms allow for the visualization and quantification of discrete phenotypes that cannot be captured using classical screening approaches. A key advantage of high-content screening technologies lies in the possibility to develop and interrogate physiologically significant, predictive ex vivo disease models that reproduce complex conditions relevant for infection. Here we review and discuss recent advances in HCI technologies and chemical biology approaches that are contributing to an increased understanding of the intricate host-pathogen interrelationship on the cellular level, and which will foster the development of novel therapeutic approaches for the treatment of human bacterial and protozoan infections. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC.
Indexed as
Identifiers
What OpenQuestion holds
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.