Cannabinoid Receptor 1 Influences Chromatin Remodeling in Mouse Spermatids by Affecting Content of Transition Protein 2 mRNA and Histone Displacement
Bibliographic record
Abstract
Marijuana smokers and animals treated with Δ9-tetrahydrocannabinol, the principal component of marijuana, show alterations of sperm morphology suggesting a role for cannabinoids in sperm differentiation and/or maturation. Because the cannabinoid receptor 1 (CNR1) activation appears to play a pivotal role in spermiogenesis, the developmental stage where DNA is remodeled, we hypothesized that CNR1 receptors might also influence chromatin quality in sperm. We used Cnr1 null mutant (Cnr1-/-) mice to study the possible role of endocannabinoids on sperm chromatin during spermiogenesis. We demonstrated that CNR1 activation regulated chromatin remodeling of spermatids by either increasing Tnp2 levels or enhancing histone displacement. Comparative analysis of wild-type, Cnr1+/-, and Cnr1-/- animals suggested the possible occurrence of haploinsufficiency for Tnp2 turnover control by CNR1, whereas histone displacement was disrupted to a lesser extent. Furthermore, flow cytometry analysis demonstrated that the genetic loss of Cnr1 decreased sperm chromatin quality and was associated with sperm DNA fragmentation. This damage increased during epididymal transit, from caput to cauda. Collectively, our results show that the expression/activity of CNR1 controls the physiological alterations of DNA packaging during spermiogenesis and epididymal transit. Given the deleterious effects of sperm DNA damage on male fertility, we suggest that the reproductive function of marijuana users may also be impaired by deregulation of the endogenous endocannabinoid system.
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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) | 0.002 | 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".