ReviewAnalytical and bioanalytical chemistry2018
Mass spectrometry-based proteomics for system-level characterization of biological responses to engineered nanomaterials.
Review in Analytical and bioanalytical chemistry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic Review of Multi-Omics Approaches to Investigate Toxicological Effects in Macrophages.International journal of molecular sciences · 2020Pooled it
- Mechanistic Insights into the Biological Effects of Engineered Nanomaterials: A Focus on Gold Nanoparticles.International journal of molecular sciences · 2023Review
- Proteomics unite traditional toxicological assessment methods to evaluate the toxicity of iron oxide nanoparticles.Frontiers in pharmacology · 2022Article
- Analysis of Nanotoxicity with Integrated Omics and Mechanobiology.Nanomaterials (Basel, Switzerland) · 2021Review
- Characterization of cellular oxidative stress response by stoichiometric redox proteomics.American journal of physiology. Cell physiology · 2021Review
- Integrated Redox Proteomic Analysis Highlights New Mechanisms of Sensitivity to Silver Nanoparticles.Molecular & cellular proteomics : MCP · 2021Article
- Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling.Journal of proteome research · 2020Article
- Redox toxicology of environmental chemicals causing oxidative stress.Redox biology · 2020Review
- Proteomic Analysis Identifies Markers of Exposure to Cadmium Sulphide Quantum Dots (CdS QDs).Nanomaterials (Basel, Switzerland) · 2020Article
- Article
- A proteome-wide assessment of the oxidative stress paradigm for metal and metal-oxide nanomaterials in human macrophages.NanoImpact · 2020Article
- An in-depth multi-omics analysis in RLE-6TN rat alveolar epithelial cells allows for nanomaterial categorization.Particle and fibre toxicology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The widespread use of engineered nanomaterials or nanotechnology makes the characterization of biological responses to nanomaterials an important area of research. The application of omics approaches, such as mass spectrometry-based proteomics, has revealed new insights into the cellular responses of exposure to nanomaterials, including how nanomaterials interact and alter cellular pathways. In addition, exposure to engineered nanomaterials often leads to the generation of reactive oxygen species and cellular oxidative stress, which implicates a redox-dependent regulation of cellular responses under such conditions. In this review, we discuss quantitative proteomics-based approaches, with an emphasis on redox proteomics, as a tool for system-level characterization of the biological responses induced by engineered nanomaterials. Graphical abstract ᅟ.
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.