ArticleNanoscale advances2019
Read-across predictions of nanoparticle hazard endpoints: a mathematical optimization approach.
Article in Nanoscale advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation.Computational and structural biotechnology journal · 2024Article
- The DaNa projects: public communication of (nano)material safety data-from conspiracy theories to study quality.Frontiers in toxicology · 2024Article
- Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment.Nanomaterials (Basel, Switzerland) · 2020Review
- NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools forComputational and structural biotechnology journal · 2020Review
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
No grant is acknowledged in the PubMed record.
Abstract
In the present study, a novel read-across methodology for the prediction of toxicity related end-points of engineered nanomaterials (ENMs) is developed. The proposed method lies in the interface between the two main read-across approaches, namely the analogue and the grouping methods, and can employ a single criterion or multiple criteria for defining similarities among ENMs. The main advantage of the proposed method is that there is no need of defining a prior read-across hypothesis. Based on the formulation and the solution of a mathematical optimization problem, the method searches over a space of alternative hypotheses, and determines the one providing the most accurate read-across predictions. The procedure is automated and only two parameters are user-defined: the balance between the level of predictive accuracy and the number of predicted samples, and the similarity criteria, which define the neighbors of a target ENM.
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.