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Record W3194941548 · doi:10.1080/09553002.2021.1969466

Expert consultation is vital for adverse outcome pathway development: a case example of cardiovascular effects of ionizing radiation

2021· article· en· W3194941548 on OpenAlexaff
Vinita Chauhan, Nobuyuki Hamada, Virginie Monceau, Téni G. Ebrahimian, Nadine Adam, Ruth C. Wilkins, Soji Sebastian, Zarana S. Patel, Janice L. Huff, Cristoforo Simonetto, Toshiyasu Iwasaki, Jan Christian Kaiser, Sisko Salomaa, Simone Moertl, Omid Azimzadeh

Bibliographic record

VenueInternational Journal of Radiation Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsCanadian Nuclear LaboratoriesHealth Canada
FundersHuman Exploration and Operations Mission DirectorateNational Aeronautics and Space Administration
KeywordsAdverse Outcome PathwayIonizing radiationAdverse effectMedicineIntensive care medicineMedical physicsToxicologyRisk analysis (engineering)PharmacologyBiologyIrradiationComputational biologyPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: The circulatory system distributes nutrients, signaling molecules, and immune cells to vital organs and soft tissues. Epidemiological, animal, and in vitro cellular mechanistic studies have highlighted that exposure to ionizing radiation (IR) can induce molecular changes in cellular and subcellular milieus leading to long-term health impacts, particularly on the circulatory system. Although the mechanisms for the pathologies are not fully elucidated, endothelial dysfunction is proven to be a critical event via radiation-induced oxidative stress mediators. To delineate connectivities of events specifically to cardiovascular disease (CVD) initiation and progression, the adverse outcome pathway (AOP) approach was used with consultation from field experts. AOPs are a means to organize information around a disease of interest to a regulatory question. An AOP begins with a molecular initiating event and ends in an adverse outcome via sequential linkages of key event relationships that are supported by evidence in the form of the modified Bradford-Hill criteria. Detailed guidelines on building AOPs are provided by the Organisation for Economic Cooperation and Development (OECD) AOP program. Here, we report on the questions and discussions needed to develop an AOP for CVD resulting from IR exposure. A recent workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations brought together experts from the OECD to present the AOP approach and tools with examples from the toxicology field. As part of this workshop, four working groups were formed to discuss the identification of adverse outcomes relevant to radiation exposures and development of potential AOPs, one of which was focused on IR-induced cardiovascular effects. Each working group comprised subject matter experts and radiation researchers interested in the specific disease area and included an AOP coach. CONCLUSION: The CVD working group identified the critical questions of interest for AOP development, including the exposure scenario that would inform the evidence, the mechanisms of toxicity, the initiating event, intermediate key events/relationships, and the type of data currently available. This commentary describes the four-day discussion of the CVD working group, its outcomes, and demonstrates how collaboration and expert consultation is vital to informing AOP construction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.003
Scholarly communication0.0030.003
Open science0.0020.005
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.313
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations30
Published2021
Admission routes1
Has abstractyes

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