ReviewNpj imaging2025
New insights into radiolabelled siderophores for molecular imaging of bacterial infections.
Review in Npj imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
This perspective article aims to provide an update on current trends in the research of radiolabelled siderophores for molecular imaging of bacterial infections. It begins by explaining the importance of developing novel diagnostic tools for infections and addresses the limitations of contemporary methods, including molecular imaging. The discussion then shifts to compounds currently being studied for nuclear imaging, with a focus on radiolabelled siderophores and recent advances in their development. It also provides the latest insights into the structures of siderophores, their utilisation by bacteria and their role in bacterial metabolism, as well as potential for labelling with various radioisotopes. Additionally, it presents the use of radiolabelled siderophores, both naturally occurring and artificial siderophore derivates, for imaging of various bacterial infections.
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.