Bibliographic record
Abstract
PURPOSE OF REVIEW: Tissue factor is increasingly viewed as an integral part of the vicious circle that links the vascular system with cancer progression at multiple systemic, cellular and molecular levels. RECENT FINDINGS: The emerging tenet in this area is that oncogenic events/pathways driving the malignant process also stimulate the expression of tissue factor by cancer cells and promote the release of tissue factor-containing microvesicles into the circulation. The combined effects of these changes likely contribute to cancer coagulopathy, cessation of tumour dormancy, aggressive growth, angiogenesis and metastasis, notably through a combination of procoagulant and signalling effects set in motion by tissue factor. As certain tumour-associated host cell types (inflammatory cells, endothelium) may also express tissue factor their contribution is plausible, though poorly understood. Interestingly, tissue factor could be 'shared' between various subsets of cancer and host cells due to intercellular transfer of tissue factor-containing microvesicles. It has recently been proposed that tissue factor may influence the interactions between tumour initiating (stem) cells and their growth or prometastatic niches. SUMMARY: Whereas targeting tissue factor in cancer is appealing, the prospects in this regard will depend on the identification of disease specific indications, active agents and their safe regimens.
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.
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 | 0.000 | 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 | 0.001 | 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".