腎細胞癌患者における血清可溶性インターロイキン2受容体値 : 手術前後の変化についての検討
Bibliographic record
Abstract
This study was carried out in order to find out whether soluble interleukin II receptor (sIL-2R) levels were useful as a treatment biomarker in patients with renal cell carcinoma (RCC). The subjects consisted of 17 patients with RCC who had been scheduled for radical or partial nephrectomy. Serum levels of sIL-2R were measured before surgery and 1 and 3 months after surgery. We also analyzed the relationship of preoperative sIL-2R to pathologic TNM-stage, grading and presumptive tumor volume. The mean value of pre-operative sIL-2R in patients with RCC was 496.5 U/ml as compared with 302.7 U/ml in the control group (p = 0.056). Pre-operative sIL-2R values were 411.1 U/ml in stage I (n = 6), 481.4 U/ml in stage III (n = 11) and 1, 330 U/ml in stage IV (n = 1). There was no significant difference between stage I and stage III. As compared with pathologic grading, pre-operative sIL-2R levels in patients with grade 2 were significantly higher than those with grade 1 (609.8 U/ml versus 288.7 U/ml, p = 0.016). There existed a significant correlation between preoperative sIL-2R and presumptive tumor volume (r = 0.61, p = 0.008). Three months after surgery, sIL-2R values were significantly higher than before surgery. Serum sIL-2R levels seemed to bear some relationship to the extent of disease in patients with RCC. Values of sIL-2R were significantly higher after than before surgery at least for a three-month postoperative period, suggesting a response to trauma of surgery. Further long term studies were required to clarify if sIL-2R could predict the progression of disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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; both teacher heads agree on what is shown here.
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".