Scrreening for microdeletions in human Y chromosome‐AZF candidate genes and male infertility
Bibliographic record
Abstract
About 30% of couple infertilities are of male origin, some of them caused by genetic abnormalities of the Y chromosome. Deletions in AZF region can cause severe spermatogenic defects ranging from non-obstructive azoospermia to oligospermia. The intracytoplasmatic sperm injection technique (ICSI) is rapidly becoming a versatile procedure for human assisted reproduction in case of male infertility. The use of ICSI allows Y chromosome defects to be passed from father. The goal of our study is to evaluate the frequency of microdeletions in the long arm of Y chromosome, within the AZF regions, in these cases of infertilities, using molecular genetics techniques. Thirty infertile men with azoospermia or oligozoospermia, determined by spermogram, were studied after exclusion of patients with endocrine or obstructive causes of infertility. Peripheral blood DNA was extracted from each patient, then amplified by multiplex PCR with STS genomic markers from the Y chromosome AZF zones. Each case was checked by multiplex PCR through coamplification with the SRY marker. Three men with microdeletions of the long arm of the Y chromosome were diagnosed among the 30 patients, corresponding to a proportion of 10%. The relatively high proportion of microdeletions found in our population suggest the need for strict patient selection to avoid unnecessary screening for long arm Y chromosome microdeletions. The molecular diagnostics was performed according to the current European Academy of Andrology laboratory guidelines for molecular diagnosis of Y chromosomal microdeletions.
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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 | 0.000 |
| 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".