Comparison of Chromosome Breakage in Non-Mosaic and Mosaic Patients with Fanconi Anemia, Relatives, and Patients with Other Inherited Bone Marrow Failure Syndromes
Bibliographic record
Abstract
Fanconi anemia (FA) is a rare inherited bone marrow failure syndrome (IBMFS). Affected individuals must be distinguished from relatives, patients with mosaicism must be identified, and patients with other IBMFS classified as non-FA. The diagnostic feature of FA is increased chromosomal breakage in blood lymphocytes cultured with diepoxybutane or mitomycin C. Here, we sought a method to uniquely identify patients with FA with mosaicism, using cells from participants in the National Cancer Institute IBMFS cohort. Lymphocytes were treated with diepoxybutane or mitomycin C, and metaphases scored for breaks and radials. Analyses included the percentage of cells with any aberration, breaks per cell, and breaks per aberrant cell. There were 26 patients with FA (4 mosaics), 46 FA relatives, and 62 patients with a non-FA IBMFS. By all analytic methods, patients with FA were abnormal compared with other groups. Those with FA mosaicism had more breakage than relatives or patients with non-FA IBMFS, but there was some individual overlap. The choices of clastogen are laboratory-dependent, but there was no method or analysis of lymphocytes that clearly distinguished all individuals mosaic for FA from relatives or patients with other IBMFS. Thus, genotyping remains the best method for providing absolute clarity.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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 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".