Disruption of Telomere–Telomere Interactions Associated with DNA Damage in Human Spermatozoa
Bibliographic record
Abstract
Telomeres play a fundamental role in the organization of the sperm nucleus resulting in the looped chromosome configuration and non-random positioning of chromosomes. Telomeres localize in the nuclear periphery and interact dynamically by forming dimers and tetramers. The purpose of this study was to evaluate the relationship of telomere interactions to DNA damage, a factor known to adversely influence male fertility. Telomeres were localized by fluorescence in situ hybridization (FISH) using human chromosome pan-telomeric probe in ten samples with low and ten samples with high sperm DNA damage. The samples with a low DNA fragmentation index (DFI) had a mean number of telomere signals of 21.7±1.9 compared to a mean of 26.5±3.4 signals in the samples with a high DFI (p<.005). The percentage of cells with a typical telomere distribution of ≤23 telomere-telomere dimers was observed in 70.8%±15.6 samples with a low DFI compared to 44.2%±22.4 in samples with a high DFI (p<.05). These results suggest that sperm DNA damage is associated with disruption of the normal telomere-telomere interactions leading to possible loss of the looped chromosome configuration. Improperly packed and organized sperm chromatin might have a high probability of disrupting the extremely structured sequence of sperm chromosome deposition, activation, and processing by the oocyte at the time of fertilization. These results might provide additional information on the nature of sperm DNA damage and the role of such damage on fertilization and development of the zygote.
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 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".