ArticleScientific reports2020
An in-silico study of cancer cell survival and spatial distribution within a 3D microenvironment.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 25 citations in OpenAlex.
- Next-generation osteosarcoma models for precision medicine.Communications biology · 2026Review
- Development and validation of a computational tool to predict treatment outcomes in cells from high-grade serous ovarian cancer patients.Bioengineering & translational medicine · 2025Article
- Article
- A comparative analysis of 2D and 3D experimental data for the identification of the parameters of computational models.Scientific reports · 2023Article
- J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.BMC bioinformatics · 2022Article
- Design of a custom-made device for real-time optical measurement of differential mineral concentrations in three-dimensional scaffolds for bone tissue engineering.Royal Society open science · 2022Article
- Review
- Perfusion Flow Enhances Viability and Migratory Phenotype in 3D-Cultured Breast Cancer Cells.Annals of biomedical engineering · 2021Article
- PML Differentially Regulates Growth and Invasion in Brain Cancer.International journal of molecular sciences · 2021Article
- Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics.Frontiers in oncology · 2021Review
- In Vitro/Ex Vivo Models for the Study of Ischemia Reperfusion Injury during Kidney Perfusion.International journal of molecular sciences · 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
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
3D cell cultures are in-vitro models representing a significant improvement with respect to traditional monolayers. Their diffusion and applicability, however, are hampered by the complexity of 3D systems, that add new physical variables for experimental analyses. In order to account for these additional features and improve the study of 3D cultures, we here present SALSA (ScAffoLd SimulAtor), a general purpose computational tool that can simulate the behavior of a population of cells cultured in a 3D scaffold. This software allows for the complete customization of both the polymeric template structure and the cell population behavior and characteristics. In the following the technical description of SALSA will be presented, together with its validation and an example of how it could be used to optimize the experimental analysis of two breast cancer cell lines cultured in collagen scaffolds. This work contributes to the growing field of integrated in-silico/in-vitro analysis of biological systems, which have great potential for the study of complex cell population behaviours and could lead to improve and facilitate the effectiveness and diffusion of 3D cell culture models.
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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.