Immunohistochemical staining of urokinase plasminogen activator-like and urokinase plasminogen activator receptor-like proteins in the urinary tract of healthy dogs
Bibliographic record
Abstract
OBJECTIVE: To determine distribution of urokinase plasminogen activator-like protein and urokinase plasminogen activator receptor-like protein in urinary tract tissues of healthy dogs. ANIMALS: 11 healthy dogs. PROCEDURES: Necropsy specimens from kidney, ureter, bladder, urethra, prostate, and testis were obtained from 4 sexually intact female dogs, 5 sexually intact males, and 2 castrated males; dogs ranged in age from juvenile to adult. Urokinase plasminogen activator-like protein and urokinase plasminogen activator receptor-like protein in tissue lysates from kidney, prostate, and testis were identified by use of SDS-PAGE, western blot analysis, and immunoprecipitation. Urokinase plasminogen activator-like protein and urokinase plasminogen activator receptor-like protein in kidney, ureter, urinary bladder, urethra, prostate, and testis were identified by use of immunohistochemical staining of tissue sections. RESULTS: Urokinase plasminogen activator-like protein and urokinase plasminogen activator receptor-like protein in the molecular-weight range published for urokinase and urokinase receptor (53 and 33 kd for urokinase and 60 to 65 kd for urokinase receptor) were identified. Distribution of the proteins identified by use of immunohistochemical staining was comparable with published information for humans and mice for the urinary tract. Staining of these proteins was detected in more tissue types than reported in healthy humans. CONCLUSIONS AND CLINICAL RELEVANCE: Urokinase plasminogen activator-like protein and urokinase plasminogen activator receptor-like protein were detected in the urinary tract of healthy dogs. This information is important for further evaluation of the functions of urokinase and urokinase receptor in the canine urinary tract and the pathophysiologic features of urinary tract disease.
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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) | 0.000 | 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".