ReviewNanomedicine (London, England)2025
Nanomaterials for bacterial enrichment and detection in healthcare.
Review in Nanomedicine (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
6 authors.
Funding
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Abstract
Bacterial infections in the blood (sepsis) have been recognized as a leading cause of mortality in the clinical field due to limitations in the detection of bacteria at low concentration and their resistance to antibiotics by excessive misuse. Some of the common symptoms are fever, chills, rapid heartbeat, difficulty breathing, confusion, and changes in mental status with occasionally pale, clammy, and mottled skin. Early diagnosis and identification are the keys to a successful treatment for sepsis patients. Researchers have developed nanoparticles to enrich bacterial populations followed by detection and applied them to conventional methods such as phenotypic and molecular diagnostics to enhance different detectors' responses toward pathogens. This short review systematically overviews steps that are followed in clinical labs for bacterial detection, identification, and their drawbacks. In this context, we discuss the role that nanoparticles can play in overcoming the limits of traditional microbiology methods in terms of turnaround times (TATs) and accuracy. We believe that this short review will provide up-to-date information about the applications of nanoparticles in the enrichment, separation, and identification of bacterial infection in the clinical field and, therefore, a way of rapid treatment.
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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.