Mast cells as targets for immunotherapy of solid tumors
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
Mast cells have historically been studied mainly in the context of allergic disease. In recent years, we have come to understand the critical importance of mast cells in tissue remodeling events and their role as sentinel cells in the induction and development of effective immune responses to infection. Studies of the role of mast cells in tumor immunity are more limited. The pro-tumorigenic role of mast cells has been widely reported. However, mast cell infiltration predicts improved prognosis in some cancers, suggesting that their prognostic value may be dependent on other variables. Such factors may include the nature of local mast cell subsets and the various activation stimuli present within the tumor microenvironment. Experimental models have highlighted the importance of mast cells in orchestrating the anti-tumor events that follow immunotherapies that target innate immunity. Mast cells are long-lived tissue resident cells that are abundant around many solid tumors and are radiation resistant making them unique candidates for combined treatment modalities. This review will examine some of the key roles of mast cells in tumor immunity, with a focus on potential immunotherapeutic interventions that harness the sentinel role of mast cells.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it