Evidence map›Paper›PMID 32695215›Full record

ArticleComputational and mathematical methods in medicine2020

Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems.

Mathias S Weyland, Pauline Thumser-Henner, Katarzyna J Nytko, Carla Rohrer Bley, Simone Ulzega, Alke Petri-Fink, Marco Lattuada, Rudolf M Füchslin, Stephan Scheidegger

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. The Use of Survival Dose-Rate Dependencies as Theoretical Discrimination Criteria forDose-response : a publication of International Hormesis Society
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mathias S WeylandZurich University of Applied Sciences Winterthur, Switzerland.ORCID https://orcid.org/0000-0001-6389-0029
Pauline Thumser-HennerDivision of Radiation Oncology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Katarzyna J NytkoDivision of Radiation Oncology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Carla Rohrer BleyDivision of Radiation Oncology, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Simone UlzegaZurich University of Applied Sciences Winterthur, Switzerland.
Alke Petri-FinkBioNanomaterials Group, Adolphe Merkle Institute, University of Fribourg, Fribourg, Switzerland.
Marco LattuadaDepartment of Chemistry, University of Fribourg, Fribourg, Switzerland.
Rudolf M FüchslinZurich University of Applied Sciences Winterthur, Switzerland.
Stephan ScheideggerZurich University of Applied Sciences Winterthur, Switzerland.ORCID https://orcid.org/0000-0002-2622-2918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to "syntactic" models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model but also in a far more challenging calibration. Model calibration is attempted from clonogenic assay data (doses of 0-6 Gy) and from time-resolved comet assay data obtained within 6 h after irradiation with 6 Gy. It is demonstrated that either of those two sources of information alone is insufficient for successful model calibration, and that both sources of information combined in a holistic approach are necessary to find viable model parameters. Approximate Bayesian computation (ABC) with simulated annealing is used for parameter search, revealing two aspects that are beneficial to resolving the calibration problem: (1) assessing posterior parameter distributions instead of point-estimates and (2) combining calibration runs from different assays by joining posterior distributions instead of running a single calibration run with a combined, computationally very expensive objective function.

Indexed as

Cell SurvivalDNA DamageModels, BiologicalAnimalsBayes TheoremCell Line, TumorComet AssayComputational BiologyDNA RepairDogsHumansMathematical ConceptsMonte Carlo MethodNeoplasmsRadiotherapy Planning, Computer-AssistedSystems Biology

Identifiers

PMID32695215
PMCPMC7361897

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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.