Impact of glucose and pyruvate on adenosine triphosphate production and sperm motility in goats
Bibliographic record
Abstract
OBJECTIVE: This study evaluates goat sperm motility in response to metabolic substrates and various inhibitors, aiming to assess the relative contribution of glycolysis and mitochondrial oxidation for sperm movement and adenosine triphosphate (ATP) production. METHODS: In the present study, two main metabolic substrates; 0 to 0.5 mM glucose and 0 to 30 mM pyruvate were used to evaluate their contribution to sperm movements of goats. Using a 3-chloro-1,2-propanediol (3-MCPD), a specific inhibitor for glycolysis, and carbonyl cyanide 3-chlorophenylhydrazone as an inhibitor for oxidative phosphorylation, cellular mechanisms into ATP-generating pathways in relation to sperm movements and ATP production were observed. Data were analysed using one-way analysis of variance for multiple comparisons. RESULTS: Sperm motility analysis showed that either glucose or pyruvate supported sperm movement during 0 to 30 min incubation. However, the supporting effects were abolished by the addition of a glycolysis inhibitor or mitochondrial uncoupler, concomitant with a significant decrease in ATP production. Although oxidative phosphorylation produces larger ATP concentrations than those from glycolysis, sperm progressivity in relation to these two metabolic pathways is comparable. CONCLUSION: Based on the present study, we suggest that goat sperm use glucose and pyruvate to generate cellular energy through glycolysis and mitochondrial respiration pathways to maintain sperm movement.
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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".