Neuroblastoma Interaction with the Tumour Microenvironment and Its Implications for Treatment and Disease Progression
Bibliographic record
Abstract
Neuroblastoma, a paediatric malignancy of the peripheral nervous system, displays a wide range of clinical outcomes, including regression to fatality despite extensive treatment. Neuroblastoma tumours display a complex interplay with their surrounding environment, known as the tumour microenvironment, which may affect disease progression and patient prognosis. This study aimed to dissect the ways in which neuroblastoma biology, treatment, prognosis, progression, and relapse are linked with the extracellular matrix, the dichotomous identities of neuroblastoma, various regulatory proteins and RNA, and extracellular vesicles within the backdrop of the tumour microenvironment. In addition, other aspects, such as immune cell infiltration, therapeutic options including monoclonal antibodies and small molecule inhibitors; and the ways in which these may affect disease progression and immunosuppression within the context of the neuroblastoma tumour microenvironment, are addressed. Such studies may shed light on useful therapeutic targets within the tumour microenvironment that may benefit groups of NB patients. Ultimately, a detailed understanding of these aspects will enable the neuroblastoma scientific community to improve treatment options, patient outcomes, and quality of life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".