ReviewBiodegradation2026
Microalgae-based removal and biodegradation of antibiotics: mechanisms, synergistic consortia, and engineering prospects.
Review in Biodegradation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Antibiotic pollution in aquatic environments drives the spread of resistance genes and threatens ecosystem health. Microalgae offer a dual-function platform that both senses antibiotic stress and actively removes these contaminants. This review synthesizes current knowledge on microalgae-based antibiotic removal and biotransformation, emphasizing the integration of biosorption, enzyme-mediated transformation-primarily via cytochrome P450 and nitroreductase-and co‑metabolic processes. We highlight the phycosphere as a dynamic interface where symbiotic bacteria enhance algal survival and pollutant removal, while also modulating the enrichment and dissemination of resistance genes. Algal-bacterial granular sludge systems illustrate the practical potential of this synergy, achieving efficient antibiotic removal and suppression of resistance propagation. Emerging tools such as immobilization, synthetic biology, and machine learning show potential to further improve system robustness and may facilitate precision process control, although their scalability and long-term performance remain to be validated. By linking fundamental mechanisms with engineering strategies, this review provides a framework for developing sustainable, low-carbon bioremediation technologies aligned with global antimicrobial resistance action plans.
Indexed as
Identifiers
42891879What 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.