Sperm aneuploidy frequencies analysed before and after chemotherapy in testicular cancer and Hodgkin's lymphoma patients
Bibliographic record
Abstract
BACKGROUND Multicolour fluorescent in situ hybridization was utilized to detect sperm aneuploidy for chromosomes 13, 21, X and Y in testicular cancer and Hodgkin's lymphoma chemotherapy patients. METHODS Aneuploidy was assessed before, and 6, 12 and/or 18-24 months after, the initiation of chemotherapy, and compared with age matched controls. 635 396 sperm were scored blindly with 5000 sperm/patient/chromosome/ time point, where sperm was available. (First two phrases have been reversed). RESULTS Comparing testicular cancer and Hodgkin's lymphoma patients to each other and with controls, cancer-specific differences were identified. Hodgkin's lymphoma patients, particularly, exhibited significantly increased aneuploidy frequencies for all chromosomes throughout treatment. At 6 months, all cancer patients showed significantly increased frequencies of XY disomy and nullisomy for chromosomes 13 and 21. In general, aneuploidy frequencies declined to pretreatment levels 18 months after treatment initiation, but increased aneuploidy frequencies persisted in some chromosomes for up to 24 months. CONCLUSIONS Because of elevated aneuploidy frequencies prior to and up to 24 months from the start of chemotherapy, patients should receive genetic counselling about the potentially increased risk of an aneuploid conceptus from sperm cryopreserved prior to chemotherapy, and for conceptions up to 2 years after the initiation of treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".