ArticleNature communications2022
Microwave assisted antibacterial action of Garcinia nanoparticles on Gram-negative bacteria.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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.
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Who cites it
30 citing papers in PubMed, 154 citations in OpenAlex.
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Corrections and comments
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Authors and funding
12 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to the existence of the outer membrane barrier, most antibacterial agents cannot penetrate Gram-negative bacteria and are ineffective. Here, we report a general method for narrow-spectrum antibacterial Garcinia nanoparticles that can only be effective to kill Gram-positive bacteria, to effectively eliminate Gram-negative bacteria by creating transient nanopores in bacterial outer membrane to induce drug entry under microwaves assistance. In vitro, under 15 min of microwaves irradiation, the antibacterial efficiency of Garcinia nanoparticles against Escherichia coli can be enhanced from 6.73% to 99.48%. In vivo, MV-assisted GNs can effectively cure mice with bacterial pneumonia. The combination of molecular dynamics simulation and experimental results reveal that the robust anti-E. coli effectiveness of Garcinia nanoparticles is attributed to the synergy of Garcinia nanoparticles and microwaves. This work presents a strategy for effectively treating both Gram-negative and Gram-positive bacteria co-infected pneumonia using herbal medicine nanoparticles with MV assistance as an exogenous antibacterial auxiliary.
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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.