The p75<sup>NTR</sup> neurotrophin receptor is a tumor suppressor in human and murine retinoblastoma development
Bibliographic record
Abstract
The transition from the benign retinal tumor retinoma to its malignant counterpart retinoblastoma is accompanied by the loss of expression of the p75(NTR) neurotrophin receptor. This change in expression is mimicked in the TAg-RB murine model of retinoblastoma, where early tumors retain expression of p75(NTR) and advanced tumors lack it. We sought to determine the functional effect on tumor development of absence of p75(NTR) from the onset of TAg-RB tumor initiation. TAg-RB mice were crossed with either p75(NTR) exon 3 (E3KO) or exon 4 knockout (E4KO) mice to produce TAg-RB offspring that lacked one or both normal p75(NTR) alleles. The average tumor area per eye as a percentage of retinal area was measured. TAg-RB/E3KO (TAg-RB(E3KO)) and heterozygous mice showed no significant difference in tumor area compared to the TAg-RB control mice at any time point studied. However, TAg-RB/E4KO (TAg-RB(E4KO)) and heterozygous mice displayed a significantly larger tumor area than the TAg-RB control mice. Furthermore, adenoviral-mediated expression of p75(NTR) in a p75(NTR)-deficient human retinoblastoma cell line resulted in increased apoptosis. Our results confirm that p75(NTR) suppresses progression of both human and TAg-RB murine retinoblastoma, and holds promise as a target for future therapy of the 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 | 0.000 | 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) | 0.001 | 0.001 |
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".