ReviewFrontiers in medical technology2020
Spectroscopic and Microscopic Approaches for Investigating the Dynamic Interactions of Anti-microbial Peptides With Membranes and Cells.
Review in Frontiers in medical technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed, 1 citations in OpenAlex.
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1 author at 1 institution in 1 country.
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Abstract
The emergence of microbes resistant to conventional antibiotics is a burgeoning threat to humanity with significant impacts on the health of people and on the health system itself. Antimicrobial peptides (AMPs) hold promise as potential future alternatives to conventional drugs because they form an integral part of the defense systems of other species in the animal, plant, and fungal kingdoms. To aid the design of the next generation of AMPs optimized for human use, we must first understand the mechanism of action of existing AMPs with their targets, ideally in the context of the complex landscape of the living (microbial) cell. Advances in lasers, optics, detectors, fluid dynamics and various probes has enabled the experimentalist to measure the kinetics of molecule-membrane, molecule-molecule, and molecule-cell interactions with increasing spatial and temporal resolution. The purpose of this review is to highlight studies into these dynamic interactions with a view to improving our understanding of AMP mechanisms.
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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.