ArticleWater research2022
Performance of NIST SRM® 2917 with 13 recreational water quality monitoring qPCR assays.
Article in Water research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Have genetic targets for faecal pollution diagnostics and source tracking revolutionized water quality analysis yet?FEMS microbiology reviews · 2023Pooled it
- Environmental investigation of a hepatitis A outbreak associated with spring water consumption in an Anabaptist community: Kentucky, 2018-2019.Journal of water and health · 2026Article
- Quantitative fecal pollution assessment with bacterial, viral, and molecular methods in small stream tributaries.The Science of the total environment · 2024Article
- Quantitative fecal source characterization of urban municipal storm sewer system outfall 'wet' and 'dry' weather discharges.Water research · 2024Article
- Occurrence of recreational water quality monitoring general fecal indicator bacteria and fecal source identification genetic markers in gray seal scat.The Science of the total environment · 2024Article
- A fecal score approximation model for analysis of real-time quantitative PCR fecal source identification measurements.Water research · 2024Article
- An overview of molecular markers for identification of non-human fecal pollution sources.Frontiers in microbiology · 2023Review
- Genetic fecal source identification in urban streams impacted by municipal separate storm sewer system discharges.PloS one · 2023Article
- Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917.Water research · 2022Article
- Design of Water Quality Monitoring System in Shaanxi Section of Weihe River Basin Based on the Internet of Things.Computational intelligence and neuroscience · 2022Article
- Fecal indicators and antibiotic resistance genes exhibit diurnal trends in the Chattahoochee River: Implications for water quality monitoring.Frontiers in microbiology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R
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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.