ArticleEnvironmental health perspectives1998
Molecular and genetic ecotoxicologic approaches to aquatic environmental bioreporting.
Article in Environmental health perspectives, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Differential gene expression of Australian Cricotopus draysoni (Diptera: Chironomidae) populations reveals seasonal association in detoxification gene regulation.Scientific reports · 2017Article
- Review
- The midgut epithelium of aquatic arthropods: a critical target organ in environmental toxicology.Environmental health perspectives · 2002Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Molecular and population genetic ecotoxicologic approaches are being developed for the utilization of arthropods as bioreporters of heavy metal mixtures in the environment. The explosion of knowledge in molecular biology, molecular genetics, and biotechnology provides an unparalleled opportunity to use arthropods as bioreporter organisms. Interspecific differences in aquatic arthropod populations have been previously demonstrated in response to heavy metal insult in the Arkansas River (AR) California Gulch Superfund site (CGSS). Population genetic analyses were conducted on the mayfly Baetis tricaudatus. Genetic polymorphisms were detected in polymerase chain reaction amplified 16S mitochondrial rDNA (a selectively neutral gene) of B tricaudatus using single-strand conformation polymorphism analysis. Genetic differences may have resulted from impediments to gene flow in the population caused by mortality arising from exposure to heavy metal mixture pollution. In laboratory studies a candidate metal-responsive mucinlike gene, which is metal and dose specific, has been identified in Chironomus tentans and other potential AR-CGSS bioreporter species. Population genetic analyses using the mucinlike gene may provide insight into the role of this selectable gene in determining the breeding structure of B. tricaudatus in the AR-CGSS and may provide mechanistic insight into determinants of aquatic arthropod response to heavy metal insult. Metal-responsive (MR) genes and regulatory sequences are being isolated, characterized, and assayed for differential gene expression in response to heavy metal mixture pollution in the AR-CGSS. Identified promoter sequences can then be engineered into previously developed MR constructs to provide sensitive in vitro assays for environmental bioreporting of heavy metal mixtures. The results of the population genetic studies are being entered into an AR geographic information system that contains substantial biological, chemical, and geophysical information. Integrated spatial, structural, and temporal analyses of these parameters will provide invaluable information concerning environmental determinants that restrict or promote gene flow in bioreporter populations.
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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.