ArticleEnvironmental science. Nano2018
Biodissolution and Cellular Response to MoO3 Nanoribbons and a New Framework for Early Hazard Screening for 2D Materials.
Article in Environmental science. Nano, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Synthesis and characterization of tungsten disulfide-graphene oxide nanocomposite.BMC chemistry · 2026Article
- The State of the Art and Challenges of In Vitro Methods for Human Hazard Assessment of Nanomaterials in the Context of Safe-by-Design.Nanomaterials (Basel, Switzerland) · 2023Review
- Biotransformations and cytotoxicity of eleven graphene and inorganic two-dimensional nanomaterials using simulated digestions coupled with a triculture in vitro model of the human gastrointestinal epithelium.Environmental science. Nano · 2021Article
- Degradation Behavior, Biocompatibility, Electrochemical Performance, and Circularity Potential of Transient Batteries.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Review
- Manganese dioxide nanosheets induce mitochondrial toxicity in fish gill epithelial cells.Nanotoxicology · 2021Article
- The preparation temperature influences the physicochemical nature and activity of nanoceria.Beilstein journal of nanotechnology · 2021Article
- A Method to Assess the Relevance of Nanomaterial Dissolution During Reactivity Testing.Materials (Basel, Switzerland) · 2020Article
- Chemical and Colloidal Dynamics of MnOSmall (Weinheim an der Bergstrasse, Germany) · 2020Article
- Predicting dissolution and transformation of inhaled nanoparticles in the lung using abiotic flow cells: The case of barium sulfate.Scientific reports · 2020Article
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.
Funding
Abstract
Two-dimensional (2D) materials are a broad class of synthetic ultra-thin sheet-like solids whose rapid pace of development motivates systematic study of their biological effects and safe design. A challenge for this effort is the large number of new materials and their chemical diversity. Recent work suggests that many 2D materials will be thermodynamically unstable and thus non-persistent in biological environments. Such information could inform and accelerate safety assessment, but experimental data to confirm the thermodynamic predictions is lacking. Here we propose a framework for early hazard screening of nanosheet materials based on biodissolution studies in reactive media, specially chosen for each material to match chemically feasible degradation pathways. Simple dissolution and in vitro tests allow grouping of nanosheet materials into four classes: A, potentially biopersistent; B: slowly degradable (>24-48 hours); C, biosoluble with potentially hazardous degradation products; and D, biosoluble with low-hazard degradation products. The proposed framework is demonstrated through an experimental case study on MoO
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.