A case example of a radiation-relevant adverse outcome pathway to lung cancer
Bibliographic record
Abstract
BACKGROUND: Adverse outcome pathways (AOPs) describe how a measurable sequence of key events, beginning from a molecular initiator, can lead to an adverse outcome of relevance to risk assessment. An AOP is modular by design, comprised of four main components: (1) a Molecular Initiating Event (MIE), (2) Key Events (KEs), (3) Key Event Relationships (KERs) and (4) an Adverse Outcome (AO). PURPOSE: Here, we illustrate the utility of the AOP concept through a case example in the field of ionizing radiation, using the Organisation for Economic Cooperation and Development (OECD) Users' Handbook. This AOP defines a classic targeted response to a radiation insult with an AO of lung cancer that is relevant to radon gas exposure. MATERIALS AND METHODS: To build this AOP, over 500 papers were reviewed and categorized based on the modified Bradford-Hill Criteria. Data-rich key events from the MIE, to several measurable KEs and KERs related to DNA damage response/repair were identified. RESULTS: The components for this AOP begin with direct deposition of energy as the MIE. Energy deposited into a cell can lead to multiple ionization events to targets such as DNA. This energy can damage DNA leading to double-strand breaks (DSBs) (KE1), this will initiate repair activation (KE2) in higher eukaryotes through mechanisms that are quick and efficient, but error-prone. If DSBs occur in regions of the DNA transcribing critical genes, then mutations (KE3) generated through faulty repair may alter the function of these genes or may cause chromosomal aberrations (KE4). This can impact cellular pathways such as cell growth, cell cycling and then cellular proliferation (KE5). This will form hyperplasia in lung cells, leading eventually to lung cancer (AO) induction and metastasis. The weight of evidence for the KERs was built using biological plausibility, incidence concordance, dose-response, time-response and essentiality studies. The uncertainties and inconsistencies surrounding this AOP are centered on dose-response relationships associated with dose, dose-rates and radiation quality. CONCLUSION: Overall, the AOP framework provided an effective means to organize the scientific knowledge surrounding the KERs and identify those with strong dose-response relationships and those with inconsistencies. This case study is an example of how the AOP methodology can be applied to sources of radiation to help support areas of risk assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".