Laboratory handling of epididymal and testicular spermatozoa: What can be done to improve sperm injections outcome
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Spermatozoa from azoospermic males can be retrieved from either the epididymis or the testis, depending on the type of azoospermia, using different surgical methods such as percutaneous epididymal sperm aspiration (PESA), testicular sperm aspiration (TESA), testicular sperm extraction (TESE), and microsurgical testicular sperm extraction (micro- TESE). After collecting the epididymal fluid or testicular tissue, laboratory techniques are used to remove contaminants, cellular debris, noxious microorganisms, and red blood cells. Processed spermatozoa may be used for intracytoplasmic sperm injection or eventually be cryopreserved. However, spermatozoa collected from either the epididymis or the testis are often compromised and more fragile than ejaculated ones. Therefore, sperm processing techniques should be used with great caution to avoid jeopardizing the sperm fertilizing potential in treatment cycles. In this review, we describe the current methods for processing surgically-retrieved specimens, either fresh or frozen- thawed, and provide the tips and pitfalls for facilitating the handling of such specimens. In addition, we present the available laboratory tools to aid in the identification of viable immotile spermatozoa to be used in conjunction with assisted reproductive techniques. Review of the literature was carried out using PubMed and Science Direct search engines.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it