ReviewEnvironment & health (Washington, D.C.)2024
Predicting Bioaccumulation of Nanomaterials: Modeling Approaches with Challenges.
Review in Environment & health (Washington, D.C.), 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
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
6 citing papers in PubMed.
- A Triadic Framework for Context-Dependent Nanotoxicology through the Lens of Biotransformation.Environment & health (Washington, D.C.) · 2026Article
- Washable Face Masks: An Emerging Source of Metal and Nanoparticle Contamination in Aquatic Environments.Environment & health (Washington, D.C.) · 2026Article
- Machine learning-enhanced nano-QSAR and multiscale modeling for predictive nanomedicine: applications in herbal therapeutics and neglected tropical diseases.Discover nano · 2026Review
- Review
- Fabrication and Characterization of a Stretchable Sodium Alginate Hydrogel Patch Combined with Silicon Nitride and Metalized Halloysite Nanotubes to Develop a Chronic Wound Healing Treatment.International journal of molecular sciences · 2025Article
- Prospects of nanotechnology and natural products for cancer and immunotherapy.Beilstein journal of nanotechnology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the bioaccumulation of nanomaterials (NMs) by organisms is essential in evaluating their potential ecotoxicity. However, the experimental determination of bioaccumulation is substantially challenging, which spawned the development of prediction approaches via establishing models for various NMs. Conventional modeling approaches, such as the biotic ligand model (BLM), partition coefficients, accumulation factor models, and quantitative structure-activity relationship (QSAR) models, were initially used in the application of NMs, aiming to provide a reliable quantitative dose in a resource-saving way. These methods, which are based on the uptake patterns of substances, probably lead to deviated results due to the different uptake behaviors of NMs. In this study, currently developed models to evaluate the bioaccumulation of NMs are critically reviewed, with their feasibilities and limitations being analyzed. In addition, the recently developed machine learning amended models have taken great efforts in realizing biological behaviors of NMs in organisms by providing
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.