Electromagnetic field in human sperm cryopreservation improves fertilizing potential of thawed sperm through physicochemical modification of water molecules in freezing medium
Bibliographic record
Abstract
Physicochemical properties of water molecules as the main compositions of the freezing media can be affected by the electromagnetic fled. The purpose of this study was to apply extremely low repetition rate electromagnetic fields (ELEFs) to change the molecular network of water molecules existing in freezing media used for human sperm cryopreservation. First, different time periods and pulsed electromagnetic fields were used to evaluate the physiochemical properties of water. The lowest rate of cluster size, surface tension, viscosity, and density was observed for water samples exposed to 1000 Hz ELEF for 60 min (P < 0.05) that could be results in small ice crystal formation. Therefore, this treatment was selected for further evaluations in human sperm freezing because there was minimal probability of amorphous ice crystallization in this group. To assess fertilizing potential, human semen samples were subjected to ELEF (1000 Hz) water-made freezing medium and cryopreserved. The highest percentage of total motility, progressive motility, viability, membrane integrity, mitochondrial membrane potential, DNA integrity, and TAC were obtained in frozen ELEF as compared to other groups. The percentage of viable spermatozoa (Annexin V-/PI-) in frozen ELEF was significantly higher than in frozen control. The level of ROS was significantly lower in frozen ELEF when compared to frozen control. It can be concluded that the modification of physicochemical properties of water existing in cryopreservation media by ELEF is a suitable strategy to improve the outcome of cryopreservation.
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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 | 0.000 |
| 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) | 0.001 | 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".