Diagnostic Utility of Nestin Expression in Pediatric Tumors in the Region of the Kidney
Bibliographic record
Abstract
Nestin is an intermediate filament that was first identified in neuroepithelial stem cells. During embryogenesis, nestin is expressed in a number of cell types, including neural crest cells and developing myocytes. We have recently shown that nestin is expressed in human podocytes and nephrogenic blastema. We sought to determine the utility of nestin expression in distinguishing pediatric tumors in the region of the kidney. Cases studied included Wilms tumor (n=24), nephroblastomatosis (n=6), renal cell carcinoma (n=19), renal clear cell sarcoma (n=9), mesoblastic nephroma (n=9), neuroblastoma (n=11), malignant rhabdoid tumor (n=8 including 2 renal), Ewing sarcoma (n=16 including 1 renal, 7 soft tissue, and 8 bone), intra-abdominal desmoplastic small round cell tumor (n=5), and rhabdomyosarcoma (n=8, all extrarenal). Nestin expression was assessed semiquantitatively by immunohistochemistry and then scored as positive or negative. All cases of Wilms tumor, mesoblastic nephroma, rhabdomyosarcoma, neuroblastoma, malignant rhabdoid tumor, and desmoplastic small round cell tumor were nestin-positive. In Wilms tumor and nephroblastomatosis, nestin was expressed in blastema and glomeruloid structures, but not tubules. In neuroblastoma, positive staining was detected regardless of degree of differentiation. The majority of Ewing sarcoma and renal cell carcinoma were negative. Expression in clear cell sarcoma was variable with 5 cases negative and 4 cases positive. Thus, nestin is a highly sensitive, but nonspecific, marker of Wilms tumor in the context of tumors that may occur in or around the kidney. Nestin reactivity may be useful in differentiating Wilms tumor from Ewing sarcoma, renal cell carcinoma, or nestin-negative clear cell sarcoma.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".