The adverse outcome pathway (<scp>AOP</scp>) for chemical binding to tubulin in oocytes leading to aneuploid offspring
Bibliographic record
Abstract
The Organisation for Economic Co-operation and Development (OECD) has launched the Adverse Outcome Pathway (AOP) Programme to advance knowledge of pathways of toxicity and improve the use of mechanistic information in risk assessment. An AOP links a molecular initiating event (MIE) to an adverse outcome (AO) through intermediate key events (KE). Here, we present the scientific evidence in support of an AOP whereby chemicals that bind to tubulin cause microtubule depolymerization resulting in spindle disorganization followed by altered chromosome alignment and segregation and the generation of aneuploidy in female germ cells, ultimately leading to aneuploidy in the offspring. Aneuploidy, an abnormal number of chromosomes that is not an exact multiple of the haploid number, is a well-known cause of human disease and represents a major cause of infertility, pregnancy failure, and serious genetic disorders in the offspring. Among chemicals that induce aneuploidy in female germ cells, a large majority impairs microtubule dynamics and spindle function. Colchicine, a prototypical chemical that binds to tubulin and causes microtubule depolymerization, is used here to illustrate the AOP. This AOP is specific to female germ cells exposed during the periovulation period. Although the majority of the data come from rodent studies, the available evidence suggests that the MIE and KEs are conserved across species and would occur in human oocytes. The development of AOPs related to mutagenicity in germ cells is expected to aid the identification of potential hazards to germ cell genomic integrity and support regulatory efforts to protect population health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".