Role of Regulatory T Cells (Treg) and the Treg Effector Molecule Fibrinogen-like Protein 2 in Alloimmunity and Autoimmunity
Bibliographic record
Abstract
CD4(+)CD25(+)Foxp3(+) regulatory T cells (Treg) are critical to the maintenance of immune tolerance. Treg are known to utilize a number of molecular pathways to control immune responses and maintain immune homeostasis. Fibrinogen-like protein 2 (FGL2) has been identified by a number of investigators as an important immunosuppressive effector of Treg, which exerts its immunoregulatory activity by binding to inhibitory FcγRIIB receptors expressed on antigen-presenting cells including dendritic cells, endothelial cells, and B cells. More recently, it has been suggested that FGL2 accounts for the immunosuppressive activity of a highly suppressive subset of Treg that express T cell immunoreceptor with Ig and ITIM domains (TIGIT). Here we discuss the important role of Treg and FGL2 in preventing alloimmune and autoimmune disease. The FGL2-FcγRIIB pathway is also known to be utilized by viruses and tumor cells to evade immune surveillance. Moving forward, therapies based on modulation of the FGL2-FcγRIIB pathway hold promise for the treatment of a wide variety of conditions ranging from autoimmunity to cancer.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".