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Record W2093713096 · doi:10.1159/000134642

Analysis of human sperm karyotypes in testicular cancer patients before and after chemotherapy

2008· article· en· W2093713096 on OpenAlexaff
Renée H. Martin, Scott Ernst, Leona Barclay, Edmund Ko, Nicholas Summers

Bibliographic record

VenueCytogenetics and Cell Genetics · 2008
Typearticle
Languageen
FieldMedicine
TopicTesticular diseases and treatments
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsSpermBiologyTesticular cancerKaryotypeAneuploidyBleomycinEtoposideChemotherapyFluorescence in situ hybridizationCancerCisplatinAndrologyPathologyChromosomeMedicineGenetics

Abstract

fetched live from OpenAlex

Sperm karyotype analysis was performed on testicular cancer patients before and after treatment with BEP (bleomycin, etoposide, and cisplatin). A total of 788 sperm chromosome complements was studied, 236 before chemotherapy (CT) and 552 post-CT. There was no significant difference in the total frequency of sperm chromosomal abnormalities pre-CT (10.2%) compared to post-CT (10.7%). Similarly, there were no significant differences in the frequencies of numerical abnormalities (2.5% pre-CT vs. 2.4% post-CT) or structural abnormalities (6.4% pre-CT vs. 7.4% post-CT). The percentage of X-bearing sperm was also not significantly different before (46.3%) and after CT (50.1%). The results in cancer patients were not significantly different from those in control donors. This study corroborates results from our previous analysis of these same men using multicolor fluorescence in situ hybridization for assessment of aneuploidy for chromosomes 1, 12, X, Y, and XY. Together, these two studies suggest that the sperm of men receiving BEP chemotherapy are not at increased risk of chromosomal abnormalities two or more years after treatment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.253
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations28
Published2008
Admission routes1
Has abstractyes

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