Interaction between tumor microenvironment, autophagy, and epithelial-mesenchymal transition in tumor progression
Bibliographic record
Abstract
Tumor microenvironment (TME) is the ecosystem surrounding a tumor to influence tumor cells' growth, metastasis and immunological battlefield, in which the tumor systems fight against the body system. TME has been considered as the essential link between the tumorigenesis and development of neoplasm. Both nutrients intake and tumor progression to malignancy require the participation of components in TME. Epithelial-mesenchymal transition (EMT) is a key step in the metastasis of tumor cells. Cells that lost polarity and acquired migration ability are prone to metastasize. Autophagy is an important self-protective mechanism in tumor cells and a necessity for the tumor cells to respond to harmful stress. Protective autophagy benefits tumor cells while abnormal autophagy leads to cell injury or death. EMT and autophagy are directly regulated by TME. To date, there are numerous studies on TME, autophagy and EMT separately, but few on their complex interrelationships. This review aims to comprehensively analyze the existing mechanisms and convincing evidence so far to seek novel therapeutic strategies and research directions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".