ReviewBiotechnology reports (Amsterdam, Netherlands)2025
Bacteriophage-based biosensors technology: Materials, fabrications, efficiencies and shortcomings.
Review in Biotechnology reports (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Article
- Artificial Intelligence in Bacteriophage Science: A Comprehensive Narrative Review of Applications, Challenges, and Translational Opportunities.Antibiotics (Basel, Switzerland) · 2026Review
- Evolving Approaches to Bacterial Identification: A Review of Classical and Modern Techniques.International journal of molecular sciences · 2026Review
- Bacteriophage BCP01 and Its Endolysin as Tools for Biocontrol and Rapid Detection ofJournal of microbiology and biotechnology · 2026Article
- Carbohydrate-based biosensors for enhanced pathogen detection.Analytical and bioanalytical chemistry · 2026Review
- Polypyrrole functionalized (TiRSC advances · 2025Article
- Electrochemical (Bio)Sensors for Toxins, Foodborne Pathogens, Pesticides, and Antibiotics Detection: Recent Advances and Challenges in Food Analysis.Biosensors · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ongoing research in biosensor technologies has led to advanced functional materials for healthcare diagnostics, and bacteriophages (phages), demonstrating exceptional utility due to their high specificity, accuracy, rapid, label-free, and wireless detection capabilities with minimal false-positive results. Phage-based-pathogen-detecting biosensors (PBPDBs) include surface plasmon resonance (SPR) biosensors, magnetoelastic (ME), electrochemical, and quartz crystal microbalance (QCM) biosensors. Commonly used substrates for PBPDBs are gold, silicon, glass, carbon-based materials, magnetic particles, and quantum dots. These substrates are chemically and physically modified to optimize phage orientation on sensor surfaces, enhancing bacterial capture. To address typical stability and issues encountered in traditional biosensor applications, phage particles and genetically modified phages are utilized to improve biosensor stability and increase detection efficacy while reducing assay time. Genetic modification in phages facilitated by CRISPR/Cas9 enables the tailoring of phages to target specific bacterial strains. This approach helps overcome the inherent specificity of phages and enables the detection of multiple pathogens in a single assay. Multiple pathogens can be detected through a single phage-based assay. This manuscript elucidates the fabrication methodologies and detection efficiencies of PBPDBs providing valuable insights into the development of practical, precise, and efficient biosensors for pathogen detection. Summary: PBPDBs are emerging diagnostic tools for the detection of bacterial pathogens.
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.