INTERLEUKIN-10 LEVELS IN SEMINAL PLASMA: IMPLICATIONS FOR CHRONIC PROSTATITIS-CHRONIC PELVIC PAIN SYNDROME
Bibliographic record
Abstract
PURPOSE: Chronic prostatitis-chronic pelvic pain syndrome is a disease of unknown pathogenesis. We investigated whether the chronic inflammation and pain experienced by patients may be caused by an imbalance of proinflammatory versus anti-inflammatory cytokines within the prostate, namely interleukin (IL)-8, interferon-gamma and IL-2 versus IL-10. We measured these inflammatory cytokines in seminal plasma as a reflection of the prostate environment. MATERIALS AND METHODS: We measured levels of IL-8, interferon-gamma, IL-2 and IL-10 in the seminal plasma of 31 patients with chronic prostatitis-chronic pelvic pain syndrome and 14 controls using enzyme-linked immunosorbent assay. Results were correlated with health related quality of life, as measured by the Multidimensional Pain Inventory, McGill pain questionnaire and International Prostate Symptom Score. RESULTS: The cytokines analyzed were detectable in the seminal plasma of patients with chronic prostatitis-chronic pelvic pain syndrome and controls. Interferon-gamma, IL-2 and IL-10 levels were statistically greater in patients. Furthermore, IL-10 levels correlated directly with measures of life interference (r = 0.52, p <0.01) and pain severity (r = 0.53, p <0 0.01), and inversely with spousal support (r = -0.39, p <0.04). CONCLUSIONS: Our study suggests that IL-10 may have a role in the pain symptoms experienced by patients with chronic prostatitis-chronic pelvic pain syndrome.
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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 | 0.002 |
| 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".