Effect of L-carnosine on frozen ram-semen quality evaluated by CASA and flow-cytometry
Bibliographic record
Abstract
Context Successful freezing of ram semen has not yet reached the desired levels. The main reason for this situation could be due to the fact that the spermatozoa of this species have a lipid composition different from that of other species. Aims The objective of the study was to evaluate the effect of different concentrations of L-carnosine added to the extender on ram semen after being frozen and thawed. Methods Semen was collected from six Akkaraman rams twice a week for a period of 3 weeks. Pooling was performed at each time. The semen were reconstituted with a pre-prepared tris + egg yolk solution and different amounts of L-carnosine to form experimental groups (Group 1: 1 mM, Group 2: 5 mM, Group 3: 10 mM, Group 4: 20 mM, Group 5: control) and were drawn into 0.25 mL mini straws. Subsequently, the samples were subjected to freezing by using an automated freezing device. Following the freezing process, the straws were placed in containers containing liquid nitrogen and thawed after 24 h. Key results After thawing, it was found that the samples containing 5 mM L-carnosine had superior results in all analyses. This concentration exhibited significantly higher percentages of progressive, total, and rapid sperm motility, live spermatozoa, high mitochondrial membrane potential rate, and higher GSH-Px concentrations. In addition, it was determined that 5 mM L-carnosine group protected the membrane integrity and significantly decreased the rate of abnormal spermatozoa, acrosomal damage rate, low mitochondrial membrane potential and apoptotic cell rate. Conclusions As a result, It was determined that adding 5 mM of L-carnosine to the semen extender during the freezing of ram samples would be beneficial for successful freezing. Implications The addition of 5 mM L-carnosine to ram-semen extenders ensures the freezability of the semen of this species; thus, this protocol could be used to perform artificial insemination with frozen ram semen.
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.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 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".