ArticleiScience2025
Rapid and sensitive antimicrobial susceptibility testing of biofilm-forming bacteria using scalable paper-based organic transistors.
Article in iScience, 2025. 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.
- Point of care antimicrobial susceptibility testing.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026Review
- Label-free phenotypic antimicrobial susceptibility testing on microfluidic platforms: a review of advances and translation.Mikrochimica acta · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A scalable, cost-effective paper-based organic field-effect transistor platform has been developed for rapid antimicrobial susceptibility testing (AST) of biofilm-forming pathogens. Traditional AST methods are costly, labor-intensive, and slow, with a lack of standardized biofilm models. This system directly tracks protons generated by biofilms, which serve as key indicators of bacterial metabolism under antibiotic exposure. A proton-sensitive PEDOT:PSS channel is employed, where metabolic proton activity de-dopes the transistor, reducing conductivity. The engineered paper substrate facilitates rapid, high-quality biofilm formation, improving assay reliability. The platform was validated on three clinically significant pathogens against frontline antibiotics, providing real-time, quantitative antibiotic efficacy profiles. Integrated with a microcontroller and machine learning algorithm, results are displayed on a liquid crystal display (LCD), classifying antibiotic concentration relative to the minimum inhibitory concentration with over 85% accuracy. This clinically translatable system offers a high-throughput, point-of-care solution for efficient infection management and antibiotic stewardship.
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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.