The utility of nanowater for ram semen cryopreservation
Bibliographic record
Abstract
Nanowater (NW; water declusterized in the low-temperature plasma reactor) has specific physicochemical properties that could increase semen viability after freezing and hence fertility after artificial insemination (AI) procedures. The main goal of this study was to evaluate ram semen quality after freezing in the media containing NW. Ejaculates from 10 rams were divided into two equal parts, diluted in a commercially available semen extender (Triladyl®; MiniTüb GmbH, Tiefenbach, Germany) prepared with deionized water (DW) or NW, and then frozen in liquid nitrogen. Semen samples were examined for sperm motility and morphology using the sperm class analyzer system and light microscopy. Cryo-scanning electron microscopy (cryo-SEM) was employed to determine the size of extracellular water crystals in frozen semen samples. Survival time at room temperature, aspartate aminotransferase (AspAT) and alkaline phosphatase (ALP) concentrations post-thawing as well as conception/lambing rates after laparoscopic intrauterine AI of 120 ewes were also determined. There were no significant differences between DW and NW groups in sperm progressive motility (26.4 ± 12.2 and 30.8 ± 12.4%) or survival time (266.6 ± 61.3 and 270.9 ± 76.7 min) after thawing and no differences in the percentages of spermatozoa with various morphological defects before or after freezing. There were, however, differences (P < 0.05) in AspAT (DW: 187.1 ± 160.4 vs. NW: 152.7 ± 118.3 U/l) and ALP concentrations (DW: 2198.3 ± 1810.5 vs. NW: 1612.1 ± 1144.8 U/l) in semen samples post-thawing. Extracellular water crystals were larger (P < 0.05) in ejaculates frozen in NW-containing media. Ultrasonographic examinations on day 40 post-AI revealed higher (P < 0.05) conception rates in ewes inseminated with NW (78.3%) compared with DW semen (58.3%), and the percentages of ewes that carried lambs to term were 73.3% and 45.0% in NW and DW groups, respectively (P < 0.01). In summary, the use of a semen extender prepared with NW was associated with a substantial improvement in the fertilizing ability of frozen-thawed ram semen and lamb productivity of inseminated ewes.
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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".