ArticleMaterials horizons2023
Antimicrobial polymer-siRNA polyplexes as a dual-mode platform for the treatment of wound biofilm infections.
Article in Materials horizons, 2023. 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
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
2 citing papers in PubMed.
- Cellular therapeutics and immunotherapies in wound healing - on the pulse of time?Military Medical Research · 2024Review
- Biofilm formation: mechanistic insights and therapeutic targets.Molecular biomedicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Treatment of wound biofilm infections faces challenges from both pathogens and uncontrolled host immune response. Treating both issues through a single vector would provide enhanced wound healing. Here, we report the use of a potent cationic antimicrobial polymer to generate siRNA polyplexes for dual-mode treatment of wound biofilms
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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.