Selection of high-quality sperm with thousands of parallel channels
Bibliographic record
Abstract
Sperm selection is essential for successful fertilization and embryo development. Current clinical sperm selection methods are labor-intensive and lack the selectivity required to isolate high-quality sperm. Microfluidic sperm selection approaches have shown promise but present a trade-off between the quality and quantity of selected sperm - clinicians demand both. The structure of the female reproductive tract helps to isolate a sufficient quantity of high-quality sperm for fertilization with densely folded epithelium that provides a multitude of longitudinally oriented pathways that guide sperm toward the fertilization site. Here, a three-dimensionally structured sperm selection device is presented that levers this highly parallelized in vivo mechanism for in vitro sperm selection. The device is inserted in a test tube atop 1 mL of raw semen and provides 6500 channels that isolate ∼100 000 high-DNA-integrity sperm for assisted reproduction. In side-by-side clinical testing, the developed approach outperforms the best current clinical methods by improving the DNA integrity of the selected sperm subpopulation up to 95%. Also, the device streamlines clinical workflow, reducing the time required for sperm preparation 3-fold. This single-tube, single-step sperm preparation approach promises to improve both the economics and outcomes of assisted reproduction practices, especially in cases with significant male-factors.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".