Growth Regulation of Nervous System Tumours: Models for Assessment of Angiogenesis in Brain Tumours
Bibliographic record
Abstract
The metabolic demand of rapidly proliferating tumour cells is reliant on an adequate blood supply that allows the continual delivery of oxygen, nutrients and growth factors. The growth and progression of tumours is significantly reduced in the absence of neovascularization and often increased abnormal neoangiogenesis correlates with the increased malignancy and poor prognosis in many tumours. By far, the most studied and understood mechanism of blood vessel formation is via angiogenesis, a process that initiates the sprouting and elongation of existing vessels into the tumour. However, more recent concepts suggest that in large tumours, the process of vasculogenesis, whereby bone marrow derived progenitor cells (BMDPCs) are recruited to the tumour and differentiate into ECs and other vascular cell types, is a more important mechanism of generating de novo vessels.The mechanisms underlying both processes are poorly understood and the redundancy between signalling pathways involved leads to complications in elucidating the control mechanisms involved. Using various experimental techniques to investigate the processes of tumour neovascularization is an evolving field, one which in this chapter we try to summarize and provide an overview of both the traditional and more novel experimental techniques used to study angiogenesis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".