ArticleBiosensors2024
Real-Time On-Site Monitoring of Viruses in Wastewater Using Nanotrap
Article in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed.
- Direct quantification of waterborne viruses via high-temperature and high-pressure treatment: a simplified nucleic acid extraction-free approach.Scientific reports · 2026Article
- Remotely Controlled Continuous Surveillance of Viral RNA in Wastewater Using a LoRa Network.IEEE internet of things journal · 2026Article
- Machine learning comparison for biomarker level estimation in wastewater dynamics monitoring.Scientific reports · 2025Article
- Thermally Responsive Alkane Partitions and a Magnetofluidic Assay for Point-of-Sample Detection of Viruses in Wastewater.Biosensors · 2025Article
- Review
- Enhanced Recovery and Detection of Highly Infectious Animal Disease Viruses by Virus Capture Using NanotrapViruses · 2024Article
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
Wastewater-based epidemiology (WBE) is an effective and efficient tool for the early detection of infectious disease outbreaks in a community. However, currently available methods are laborious, costly, and time-consuming due to the low concentration of viruses and the presence of matrix chemicals in wastewater that may interfere with molecular analyses. In the present study, we designed a highly sensitive "Quick Poop (wastewater with fecal waste) Sensor" (termed, QPsor) using a joint approach of Nanotrap microbiome particles and RICCA (RNA Isothermal Co-Assisted and Coupled Amplification). Using QPsor, the WBE study showed a strong correlation with standard PEG concentrations and the qPCR technique. Using a closed format for a paper-based lateral flow assay, we were able to demonstrate the potential of our assay as a real-time, point-of-care test by detecting the heat-inactivated SARS-CoV-2 virus in wastewater at concentrations of 100 copies/mL and within one hour. As a proof-of-concept demonstration, we analyzed the presence of viral RNA of the SARS-CoV-2 virus and PMMoV in raw wastewater samples from wastewater treatment plants on-site and within 60 min. The results show that the QPsor method can be an effective tool for disease outbreak detection by combining an AI-enabled case detection model with real-time on-site viral RNA extraction and amplification, especially in the absence of intensive clinical laboratory facilities. The lab-free, lab-quality test capabilities of QPsor for viral prevalence and transmission in the community can contribute to the efficient management of pandemic situations.
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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.