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Record W2137341907 · doi:10.1093/humrep/del190

Analysis of non-crossover bivalents in pachytene cells from 10 normal men

2006· article· en· W2137341907 on OpenAlexaff
Fei Sun

Bibliographic record

VenueHuman Reproduction · 2006
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsCrossoverGeneticsBiologyAndrologyMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Bivalents with no recombination foci (possible achiasmates) are unable to orient properly on the metaphase plate or to segregate chromosomes to daughter cells. Non-crossover bivalents are known to cause meiotic arrest in various organisms. METHODS: Individual non-crossover bivalents were identified in 886 pachytene cells (19 492 bivalents) from testicular biopsies of 10 normal men. Fluorescence staining combined with centromere-specific multicolour fluorescence in situ hybridization (cenM-FISH) was used to identify mismatch repair gene mutation of human mutL homologue 1 (MLH1) recombination foci along each bivalent synaptonemal complex (SC). RESULTS: A total of 60 autosomal non-crossovers (SCs without an MLH1 focus) were found, and of these, chromosomes 21 (2.1%) and 22 (1.7%) had a significantly higher proportion than chromosomes 11, 12, 19 (each 0.1%), 13 (0.2%), 14 (0.6%), 16 (0.5%) and 15, 17, 18, 20 (each 0.3%) (P < 0.05). Sex chromosome univalents had a frequency of 27%, higher than that observed in any autosomal bivalent (P < 0.0001). CONCLUSIONS: These results suggest that G-group chromosomes and sex chromosomes are most susceptible to having no recombination foci and thus would be more susceptible to non-disjunction during spermatogenesis. This is consistent with previous observations from sperm karyotyping and FISH analysis, which demonstrate that chromosomes 21 and 22 and the sex chromosomes have a significantly increased frequency of aneuploidy compared with other autosomes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.279
Teacher spread0.264 · 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 teacher head, not a consensus.

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
Published2006
Admission routes1
Has abstractyes

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