Accumulation of Seminolipid in Sertoli Cells Is Associated with Increased Levels of Reactive Oxygen Species and Male Subfertility: Studies in Aging Arsa Null Male Mice
Bibliographic record
Abstract
Seminolipid (also known as sulfogalactosylglycerolipid-SGG), present selectively in male germ cells, plays important roles in spermatogenesis and sperm–egg interaction. The proper degradation of SGG in apoptotic germ cells is also as important. Sertoli cells first phagocytose apoptotic germ cells, then Sertoli lysosomal arylsulfatase A (ARSA) desulfates SGG, the first step of SGG degradation. We have reported that aging male Arsa−/− mice become subfertile with SGG accumulation in Sertoli cell lysosomes, typical of a lysosomal storage disorder (LSD). Since reactive oxygen species (ROS) levels are increased in other glycolipid-accumulated LSDs, we quantified ROS in Arsa−/− Sertoli cells. Our analyses indicated increases in superoxide and H2O2 in Arsa−/− Sertoli cells with elevated apoptosis rates, relative to WT counterparts. Excess H2O2 from Arsa−/− Sertoli cells could travel into testicular germ cells (TGCs) to induce ROS production. Our results indeed indicated higher superoxide levels in Arsa−/− TGCs, compared with WT TGCs. Increased ROS levels in Arsa−/− Sertoli cells and TGCs likely caused the decrease in spermatogenesis and increased the abnormal sperm population in aging Arsa−/− mice, including the 50% decrease in sperm SGG with egg binding ability. In summary, our study indicated that increased ROS production was the mechanism through which subfertility manifested following SGG accumulation in Sertoli cells.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".