Determination of gelatinase A using a modified indirect hemagglutination assay in human prostate cancer screening and assessment of its correlation with prostate‐specific antigen parameters
Bibliographic record
Abstract
BACKGROUND: Prostate cancer is the most common malignancy affecting men and is a major cause of cancer death. There are increasing data on novel tumor markers, such as gelatinase A, which play a key role in tissue invasion and metastasis. OBJECTIVES: We designed a study to evaluate total gelatinase A content using a simple and applicable Indirect hemagglutination (IHA) test in harmony with gelatinase A activity in serum samples as compared with prostate-specifc antigen (PSA) parameters. METHODS: In this study, we analysed the circulating form of gelatinase A (MMP-2) in patients suffering from either benign prostate hyperplasia (n=54) or prostate cancer (n=26) versus normal individuals as control (n=26). The gelatinolytic activity was determined by zymography and total MMP-2 content was measured by a novel IHA method. Total PSA and free PSA were quantified using a standard ELISA technique. RESULTS: Correlation of densitometric analysis of gelatinase A activity and IHA titer is significant at the 0.01 level (P<0.01, rho=0.916). Correlation of PSA and IHA titer is significant at the 0.01 level (P<0.01, rho=0.746). Correlation of free PSA and IHA titer is significant at the 0.01 level (P<0.01, rho=0.749). Borderline of IHA titer in patients with prostate cancer was 512+/-1 tube titer, in benign prostate hyperplasia patients was 128+/-1 tube titer and the titer in normal individuals was 8+/-1 tube titer. CONCLUSIONS: These results demonstrate that assessment of gelatinase A might be a promising procedure for monitoring and screening patients with prostate cancer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".