ArticleProceedings of the National Academy of Sciences of the United States of America2008
Perturbational profiling of nanomaterial biologic activity.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 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
76 citing papers in PubMed.
- Review on Predictive Models and Integration Strategies for Holistic Impact Assessment of Chemicals and Materials.Environmental science & technology · 2026Review
- Recent Advances in Machine Learning Models for Predicting Toxicity of Inorganic Nanoparticles.Chem & bio engineering · 2025Review
- Chemical screens for particle-induced macrophage death identifies kinase inhibitors of phagocytosis as targets for toxicity.Journal of nanobiotechnology · 2024Article
- Biomarkers of nanomaterials hazard from multi-layer data.Nature communications · 2022Article
- NanoTox: Development of a ParsimoniousACS omega · 2021Article
- Electrodynamic assisted self-assembled fibrous hydrogel microcapsules: a novel 3DRSC advances · 2021Article
- Multiparametric Profiling of Engineered Nanomaterials: Unmasking the Surface Coating Effect.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Article
- Measuring the Stability of Supramolecular Complexes in the Proximity of Single-Walled Carbon Nanotubes.ChemistryOpen · 2020Article
- QSAR without borders.Chemical Society reviews · 2020Review
- Big Data and Artificial Intelligence Modeling for Drug Discovery.Annual review of pharmacology and toxicology · 2020Review
- Nano-(Q)SAR for Cytotoxicity Prediction of Engineered Nanomaterials.Molecules (Basel, Switzerland) · 2019Review
- Closing the 'phenotype gap' in precision medicine: improving what we measure to understand complex disease mechanisms.Mammalian genome : official journal of the International Mammalian Genome Society · 2019Review
- Multiple linear regression applied to predicting droplet size of complex perfluorocarbon nanoemulsions for biomedical applications.Pharmaceutical development and technology · 2019Article
- Computational models for the assessment of manufactured nanomaterials: Development of model reporting standards and mapping of the model landscape.Computational toxicology (Amsterdam, Netherlands) · 2019Article
- The Right Stuff: On the Future of Nanotoxicology.Frontiers in toxicology · 2019Article
- Toxicity Classification of Oxide Nanomaterials: Effects of Data Gap Filling and PChem Score-based Screening Approaches.Scientific reports · 2018Article
- Comparison of conventional and advanced in vitro models in the toxicity testing of nanoparticles.Artificial cells, nanomedicine, and biotechnology · 2018Review
- Predicting Nano-Bio Interactions by Integrating Nanoparticle Libraries and Quantitative Nanostructure Activity Relationship Modeling.ACS nano · 2017Article
- A Review of Recent Advances towards the Development of (Quantitative) Structure-Activity Relationships for Metallic Nanomaterials.Materials (Basel, Switzerland) · 2017Review
- Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials.International journal of molecular sciences · 2017Review
16 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Our understanding of the biologic effects (including toxicity) of nanomaterials is incomplete. In vivo animal studies remain the gold standard; however, widespread testing remains impractical, and the development of in vitro assays that correlate with in vivo activity has proven challenging. Here, we demonstrate the feasibility of analyzing in vitro nanomaterial activity in a generalizable, systematic fashion. We assessed nanoparticle effects in a multidimensional manner, using multiple cell types and multiple assays that reflect different aspects of cellular physiology. Hierarchical clustering of these data identifies nanomaterials with similar patterns of biologic activity across a broad sampling of cellular contexts, as opposed to extrapolating from results of a single in vitro assay. We show that this approach yields robust and detailed structure-activity relationships. Furthermore, a subset of nanoparticles were tested in mice, and nanoparticles with similar activity profiles in vitro exert similar effects on monocyte number in vivo. These data suggest a strategy of multidimensional characterization of nanomaterials in vitro that can inform the design of novel nanomaterials and guide studies of in vivo activity.
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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.