Role of the metastasis‐promoting protein osteopontin in the tumour microenvironment
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
Osteopontin (OPN) is a secreted protein present in bodily fluids and tissues. It is subject to multiple post-translational modifications, including phosphorylation, glycosylation, proteolytic cleavage and crosslinking by transglutamination. Binding of OPN to integrin and CD44 receptors regulates signalling cascades that affect processes such as adhesion, migration, invasion, chemotaxis and cell survival. A variety of cells and tissues express OPN, including bone, vasculature, kidney, inflammatory cells and numerous secretory epithelia. Normal physiological roles include regulation of immune functions, vascular remodelling, wound repair and developmental processes. OPN also is expressed in many cancers, and elevated levels in patients' tumour tissue and blood are associated with poor prognosis. Tumour growth is regulated by interactions between tumour cells and their tissue microenvironment. Within a tumour mass, OPN can be expressed by both tumour cells and cellular components of the tumour microenvironment, and both tumour and normal cells may have receptors able to bind to OPN. OPN can also be found as a component of the extracellular matrix. The functional roles of OPN in a tumour are thus complex, with OPN secreted by both tumour cells and cells in the tumour microenvironment, both of which can in turn respond to OPN. Much remains to be learned about the cross-talk between normal and tumour cells within a tumour, and the role of multiple forms of OPN in these interactions. Understanding OPN-mediated interactions within a tumour will be important for the development of therapeutic strategies to target OPN.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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