ReviewReproductive toxicology (Elmsford, N.Y.)2017
Applying evolutionary genetics to developmental toxicology and risk assessment.
Review in Reproductive toxicology (Elmsford, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 18 citations in OpenAlex.
- High-Throughput Toxicity Screening withEnvironmental science & technology · 2026Review
- Laboratory and physiological aspects of substitute metazoan models for in vivo pharmacotoxicological analysis.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Molecular Evolution of Aryl Hydrocarbon Receptor Signaling Pathway Genes.Journal of molecular evolution · 2023Article
- Toxicity by descent: A comparative approach for chemical hazard assessment.Environmental advances · 2022Article
- Xenobiotic metabolism and transport inJournal of toxicology and environmental health. Part B, Critical reviews · 2021Review
- Evolutionary concepts can benefit both fundamental research and applied research in toxicology (A comment on Brady et al. 2017).Evolutionary applications · 2019Article
- Proceedings of the 2017 annual meeting of the Fetal Alcohol Spectrum Disorders study group.Alcohol (Fayetteville, N.Y.) · 2018Article
- Evolutionary toxicology: Toward a unified understanding of life's response to toxic chemicals.Evolutionary applications · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 1 country.
Funding
Abstract
Evolutionary thinking continues to challenge our views on health and disease. Yet, there is a communication gap between evolutionary biologists and toxicologists in recognizing the connections among developmental pathways, high-throughput screening, and birth defects in humans. To increase our capability in identifying potential developmental toxicants in humans, we propose to apply evolutionary genetics to improve the experimental design and data interpretation with various in vitro and whole-organism models. We review five molecular systems of stress response and update 18 consensual cell-cell signaling pathways that are the hallmark for early development, organogenesis, and differentiation; and revisit the principles of teratology in light of recent advances in high-throughput screening, big data techniques, and systems toxicology. Multiscale systems modeling plays an integral role in the evolutionary approach to cross-species extrapolation. Phylogenetic analysis and comparative bioinformatics are both valuable tools in identifying and validating the molecular initiating events that account for adverse developmental outcomes in humans. The discordance of susceptibility between test species and humans (ontogeny) reflects their differences in evolutionary history (phylogeny). This synthesis not only can lead to novel applications in developmental toxicity and risk assessment, but also can pave the way for applying an evo-devo perspective to the study of developmental origins of health and disease.
Indexed as
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.