Spermatogenic and sperm quality differences in an experimental model of metabolic syndrome and hypogonadal hypogonadism
Bibliographic record
Abstract
The synergistic effect of the co-morbidities that comprise metabolic syndrome (MetS) is increasingly being recognised as an important contributor in the pathology of a broad spectrum of seemingly disparate conditions. However, in terms of male reproductive function, beyond erectile dysfunction, little is known about the influence of this cohort (collectively or separately) on spermatogenesis and sperm quality. The aims of this study were to assess the reproductive tract of a MetS animal model for detrimental changes, to determine whether a group of compounds (advanced glycation end products and their receptor) known to cause cell dysfunction and DNA damage was present and assess whether hypogonadotropic hypogonadism was the main contributing factor for the changes seen. Animals fed a high-fat diet were found to have significantly increased cholesterol, triglycerides, blood glucose, mean arterial pressure and visceral fat levels. Although serum testosterone was decreased, no changes were seen in either testicular or epididymal histology. Immunolocalisation of N(ε)-carboxymethyl-lysine and the receptor for advanced glycation end products was found in the testes, epididymides and sperm of the two treated groups of animals; however, ELISA did not show any difference in protein levels. Similarly, assessment of sperm nuclear DNA (nDNA) fragmentation by acridine orange test did not find significant differences in nDNA integrity. We conclude that the minimal effect on spermatogenesis and sperm quality seen in our model is probably due to the moderate increase of blood glucose rather than the hypogonadism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".