Sperm capacitation and transcripts levels are altered by in vitro THC exposure
Bibliographic record
Abstract
BACKGROUND: Delta-9-tetrahydrocannabinol (THC) is the primary phytocannabinoid responsible for the psychoactive properties of cannabis and is known to interact with the endocannabinoid system, which is functionally present in the male reproductive system. Since cannabis consumption is the highest among reproductive aged males, the current study aimed to further investigate the effects of THC exposure to phenotypical, physiological, and molecular parameters in sperm. Bull sperm of known fertility were used as a translational model for human sperm and subjected to in vitro treatment with physiologically relevant experimental doses of THC. Sperm parameters, capacitation, apoptosis, and transcript levels were evaluated following treatment. RESULTS: Motility, morphology, and viability of bovine sperm was unaltered from THC exposure. However, 0.32µM of THC caused an increased proportion of capacitating sperm (p < 0.05) compared to control and vehicle group sperm. Transcriptome analysis revealed that 39 genes were found to be differentially expressed by 0.032µM THC exposure, 196 genes were differentially expressed by 0.32µM THC exposure, and 33 genes were differentially expressed by 3.2µM THC. Secondary analysis reveals pathways involving development, nucleosomes, ribosomes and translation, and cellular metabolism to be significantly enriched. CONCLUSION: Phytocannabinoid exposure to sperm may adversely affect sperm function by stimulating premature capacitation. These findings also show for the first time that spermatozoal transcripts may be altered by THC exposure. These results add to previous research demonstrating the molecular effects of cannabinoids on sperm and warrant further research into the effects of cannabis on male fertility.
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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) | 0.003 | 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".