ArticleACS applied materials & interfaces2018
Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices.
Article in ACS applied materials & interfaces, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 53 citations in OpenAlex.
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- Effect of DMPEI coating against biofilm formation on PVC catheter surface.World journal of microbiology & biotechnology · 2023Article
- A potential alternative to fungicides using actives-free (meth)acrylate polymers for protection of wheat crops from fungal attachment and infection.Green chemistry : an international journal and green chemistry resource : GC · 2023Article
- Applied machine learning as a driver for polymeric biomaterials design.Nature communications · 2023Review
- Introduction of Materials Genome Technology and Its Applications in the Field of Biomedical Materials.Materials (Basel, Switzerland) · 2023Review
- Discovery of a polymer resistant to bacterial biofilm, swarming, and encrustation.Science advances · 2023Article
- Antimicrobial Properties of Plant Fibers.Molecules (Basel, Switzerland) · 2022Review
- Machine learning approaches for biomolecular, biophysical, and biomaterials research.Biophysics reviews · 2022Review
- Biocompatible Materials in Otorhinolaryngology and Their Antibacterial Properties.International journal of molecular sciences · 2022Review
- High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology.Chemical reviews · 2021Review
- In Vitro Evaluation of Polihexanide, Octenidine and NaClO/HClO-Based Antiseptics against Biofilm Formed by Wound Pathogens.Membranes · 2021Article
- Precision Design of Antimicrobial Surfaces.Frontiers in medical technology · 2021Article
- Single-Cell Tracking on Polymer Microarrays Reveals the Impact of Surface Chemistry onACS applied bio materials · 2020Article
- Hyperosmotic Infusion and Oxidized Surfaces Are Essential for Biofilm Formation ofFrontiers in microbiology · 2020Article
- Ethylene Glycol Dicyclopentenyl (Meth)Acrylate Homo and Block Copolymers via Nitroxide Mediated Polymerization.Materials (Basel, Switzerland) · 2019Article
- Biofilm formation - what we can learn from recent developments.Journal of internal medicine · 2018Article
- Sparse QSAR modelling methods for therapeutic and regenerative medicine.Journal of computer-aided molecular design · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 3 countries.
Funding
Abstract
Bacterial infections in healthcare settings are a frequent accompaniment to both routine procedures such as catheterization and surgical site interventions. Their impact is becoming even more marked as the numbers of medical devices that are used to manage chronic health conditions and improve quality of life increases. The resistance of pathogens to multiple antibiotics is also increasing, adding an additional layer of complexity to the problems of employing safe and effective medical procedures. One approach to reducing the rate of infections associated with implanted and indwelling medical devices is the use of polymers that resist the formation of bacterial biofilms. To significantly accelerate the discovery of such materials, we show how state of the art machine learning methods can generate quantitative predictions for the attachment of multiple pathogens to a large library of polymers in a single model for the first time. Such models facilitate design of polymers with very low pathogen attachment across different bacterial species that will be candidate materials for implantable or indwelling medical devices such as urinary catheters, cochlear implants, and pacemakers.
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.