Angiogenesis Signaling in Retinoblastoma: Prognostic and Therapeutic Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Angiogenesis is a critical player in tumor metastasis that is involved in the pathophysiology of the pediatric ocular cancer retinoblastoma (RB). This review summarizes evidence linking angiogenesis to RB prognostication, response to treatment, and therapy. Vascular endothelial growth factor (VEGF), a major proangiogenic growth factor, has potential as a biomarker of therapy response in RB treatment. High VEGF correlates with poor chemotherapy response, subsequent local invasion, and lower patient survival. VEGF levels are also strongly correlated with choroidal invasion, poor differentiation, and an overall negative disease prognosis for RB patients. In contrast, decreasing VEGF levels can predict vitreous seed regression after intravitreal chemotherapy. Further investigation is needed to determine the accuracy and clinical value of using aqueous humor liquid biopsies to assess VEGF levels to predict prognosis or therapy response. Antiangiogenic agents, including approved drugs and experimental compounds, have shown potential in RB models and may become potential therapeutics, adjuvants to current chemotherapies, or treatments for chemotherapy complications, although there is limited evidence that antiangiogenic monotherapy may be sufficient for RB. Overall, future research aimed at integrating angiogenesis markers and therapies with existing RB strategies holds promise for improving patient outcomes and personalizing treatment approaches.
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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 | 0.000 | 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) | 0.000 | 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 it