Absence of sperm RNA elements correlates with idiopathic male infertility
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
Semen parameters are typically used to diagnose male infertility and specify clinical interventions. In idiopathic infertile couples, an unknown male factor could be the cause of infertility even when the semen parameters are normal. Next-generation sequencing of spermatozoal RNAs can provide an objective measure of the paternal contribution and may help guide the care of these couples. We assessed spermatozoal RNAs from 96 couples presenting with idiopathic infertility and identified the final reproductive outcome and sperm RNA elements (SREs) reflective of fecundity status. The absence of required SREs reduced the probability of achieving live birth by timed intercourse or intrauterine insemination from 73 to 27%. However, the absence of these same SREs does not appear to be critical when using assisted reproductive technologies such as in vitro fertilization with or without intracytoplasmic sperm injection. About 30% of the idiopathic infertile couples presented an incomplete set of required SREs, suggesting a male component as the cause of their infertility. Conversely, analysis of couples that failed to achieve a live birth despite presenting with a complete set of SREs suggested that a female factor may have been involved, and this was confirmed by their diagnosis. The data in this study suggest that SRE analysis has the potential to predict the individual success rate of different fertility treatments and reduce the time to achieve live birth.
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.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 it