Using mouse models to investigate the biological and physiological consequences of defects in the Fanconi anaemia/breast cancer DNA repair signalling pathway
Bibliographic record
Abstract
Fanconi anaemia (FA) is a rare, predominantly autosomal recessive syndrome (with one X-linked form) that results in congenital defects, abnormal haematopoiesis and a greatly increased risk of solid tumours in humans. Mutations in at least 14 different genes have been shown to cause FA, and several of these genes, including FANCJ/BRIP1, FANCD1/BRCA2 and FANCN/PALB2, also predispose to breast cancer in heterozygote carriers. The FA genes code for proteins that act in complexes to coordinate the repair of damaged DNA, and thus the FA repair network is intimately linked with hereditary breast cancer. Much remains to be learnt about the functions and interactions of the FA proteins and one experimental approach involves the generation of mice that are deficient in various FA genes. Mouse models for FANCN/PALB2 have recently been generated, including one reported in a recent issue of The Journal of Pathology. Given the pivotal role of the PALB2 protein, which interacts with both BRCA1 and BRCA2, these mice provide valuable insights into the FA phenotype and mechanisms of tumourigenesis caused by disruption of the FA protein network.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".