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
Modulation of T-cell immune functions by blocking key immune checkpoint protein interactions using monoclonal antibodies (mAbs) has been an innovative immunotherapeutic strategy. T-cells are regulated by different checkpoint proteins at the immunological synapse including the B7 ligands (B7-1 or CD80 and B7-2 or CD86), which is discussed in this review. These ligands are typically expressed on antigen presenting cells and interact with CD28 and cytotoxic T lymphocyte antigen-4 (CTLA-4) receptors on T-cells. Their interactions with CD28 trigger a costimulatory signal that potentiates T-cell activation, function and survival in response to cognate antigen. In addition, their interactions with CTLA-4 can also inhibit certain effector T-cell responses, particularly in response to sustained antigen stimulation. Through these mechanisms, the balance between T-cell activation and suppression is maintained, preventing the occurrence of immunopathology. Given their crucial roles in immune regulation, targeting B7 ligands has been an attractive strategy in cancer and autoimmunity. This review presents an overview of the essential roles of B7-1, highlighting the therapeutic benefits of modulating this protein in immunotherapy, and reviewing earlier and state-of-the-art efforts in developing anti-B7-1 inhibitors. Finally, we discuss the challenges facing the design of selective B7-1 inhibitors and present our perspectives for future developments.
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 | 0.017 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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