The immunoregulatory mechanisms of carcinoma for its survival and development
Bibliographic record
Abstract
The immune system in patients detects and eliminates tumor cells, but tumors still progress persistently. The mechanisms by which tumor cells survive under the pressure of immune surveillance are not fully understood. This review is to present the evidence from clinical studies, showing a significant correlation of clinicopathological features of carcinoma with: (1) the loss of classical human leukocyte antigen class I, (2) the up-regulation of non-classical human leukocyte antigen class I, pro-apoptotic Fas ligand and receptor-binding cancer antigen expressed on SiSo cells I, and (3) the formation of immunosuppressive microenvironment by up-regulation of transforming growth factor-beta, Galectin-1, inhibitory ligand B7s, indoleamine 2,3-dioxygenase and arginase, as well as by recruitment of tumor-induced myeloid-derived suppressor cells and regulatory T cells. All of these factors may together protect carcinoma cells from the immune-cytotoxicity.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".