The association between oral inflammatory load and semen and sperm functional analysis: A cross-sectional study
Bibliographic record
Abstract
Background. Studies have suggested a correlation between periodontitis and reduced male fertility. Inflammation has been described as the link between these ailments. Oral inflammatory load (OIL) can be measured through oral polymorphonuclear neutrophil (oPMN) count, which is associated with periodontal diseases. This cross-sectional study assessed the possible correlation between OIL and the functional parameters of sperm cells. Methods. In 229 volunteers, oral rinse and semen samples were assessed for oPMN, semen polymorphonuclears (sPMNs), sperm concentration, total sperm count, motility, morphology, and sperm DNA fragmentation index (SDFi). A multiple linear regression model was conducted to evaluate the relationships between oPMN and semen parameters. Results. The effect of elevated oPMN counts on total motility rate, progressive rate, and percentage of sperm cells with normal morphology was significant (P<0.001), with an inverse relationship, i.e., with every unit increase in oPMN count, the mentioned parameters would decline by 0.573, 0.367, and 0.407 units, respectively. oPMN counts also correlated positively with sPMN counts and SDFi (P<0.001), i.e., with every unit increase in the oPMN measures, sPMN counts would increase by 0.126 million/mL, with an 0.733% increase in SDFi. However, there was no significant association between oPMN counts and sperm concentration. Conclusion. OIL, as represented by oPMN counts, might affect male fertility as there is a positive correlation between the levels of these inflammatory cells and decreased sperm motility, abnormal morphological changes, increased sPMN counts, and increased SDFi.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".