ArticleJournal of toxicology2014
Modeling in vitro cellular responses to silver nanoparticles.
Article in Journal of toxicology, 2014. 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.
- Influence of Physicochemical Characteristics and Stability of Gold and Silver Nanoparticles on Biological Effects and Translocation across an Intestinal Barrier-A Case Study from In Vitro to In Silico.Nanomaterials (Basel, Switzerland) · 2021Article
- New Relevant Descriptor of Linear QNAR Models for Toxicity Assessment of Silver Nanoparticles.Nanomaterials (Basel, Switzerland) · 2020Article
- Physiologically based mathematical models of nanomaterials for regulatory toxicology: A review.Computational toxicology (Amsterdam, Netherlands) · 2019Review
- The small airway epithelium as a target for the adverse pulmonary effects of silver nanoparticle inhalation.Nanotoxicology · 2018Article
- Advancing the Understanding of Environmental Transformations, Bioavailability and Effects of Nanomaterials, an International US Environmental Protection Agency-UK Environmental Nanoscience Initiative Joint Program.Journal of environmental protection · 2018Article
- The virtual cell based assay: Current status and future perspectives.Toxicology in vitro : an international journal published in association with BIBRA · 2017Article
- Pulmonary effects of inhalation of spark-generated silver nanoparticles in Brown-Norway and Sprague-Dawley rats.Respiratory research · 2016Article
- ModelingNanomaterials (Basel, Switzerland) · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Engineered nanoparticles (NPs) have been widely demonstrated to induce toxic effects to various cell types. In vitro cell exposure systems have high potential for reliable, high throughput screening of nanoparticle toxicity, allowing focusing on particular pathways while excluding unwanted effects due to other cells or tissue dosimetry. The work presented here involves a detailed biologically based computational model of cellular interactions with NPs; it utilizes measurements performed in human cell culture systems in vitro, to develop a mechanistic mathematical model that can support analysis and prediction of in vivo effects of NPs. The model considers basic cellular mechanisms including proliferation, apoptosis, and production of cytokines in response to NPs. This new model is implemented for macrophages and parameterized using in vitro measurements of changes in cellular viability and mRNA levels of cytokines: TNF, IL-1b, IL-6, IL-8, and IL-10. The model includes in vitro cellular dosimetry due to nanoparticle transport and transformation. Furthermore, the model developed here optimizes the essential cellular parameters based on in vitro measurements, and provides a "stepping stone" for the development of more advanced in vivo models that will incorporate additional cellular and NP interactions.
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.