Checkpoint blockade in solid tumors and B-cell malignancies, with special consideration of the role of CD200
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
In the ontogeny of a normal immune response, a series of checkpoints must be overcome to ensure that unwanted and/or harmful self-directed activation responses are avoided. Many of the molecules now known to be active in this overseeing of the evolving immune activation cascade, contributing inhibitory signals to dampen an overexuberant response, belong to the immunoglobulin supergene family. These include members of the CD28/CTLA-4:B7.1/B7.2 receptor/ligand family, PD-1 and PDL-1, CD200 and CD200R, and the more recently described V-domain immunoglobulin suppressor of T-cell activation and its ligand (VSIG-3/IGSF11). Unfortunately, from the point of view of improving immunotargeting of cancer cells, triggering these checkpoint inhibitory signaling pathways, so necessary to maintain self-tolerance, simultaneously acts to prevent effective tumor immunity. The recent development of reagents, predominantly antibodies, to act as checkpoint blockade agents, has had a dramatic effect on human cancer treatment, with a marked reported success for anti-CTLA-4 and PD-1 in particular in clinical trials. This review provides a general overview of the data now available showing the promise of such treatments to our cancer armamentarium and elaborates in depth on the potential promise of what can be regarded as an underappreciated target molecule for checkpoint blockade in chronic lymphocytic leukemia and solid tumors, CD200.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it