Modulation of T cell function by CD271
Bibliographic record
Abstract
Abstract Co-signaling molecules are essential modulators of the immune system. These molecules belong to the immunoglobulin and tumor necrosis factor receptor superfamilies (IgSF and TNFRSF, respectively). Despite intensive study of these protein families, the functions and binding partners for many IgSF and TNFRSF members remain largely unknown. In particular, CD271 (NGFR and TNFRSF16) is expressed on neural crest-derived cells, several immunomodulatory cell types, as well as on diverse cancers cells, and our data attribute new immunoregulatory properties to CD271 that may play a role in both cancer evasion and autoimmune disease. Indeed, in vitro stimulation of mouse and human T cells in the presence of recombinant CD271-Fc protein inhibits T cell activation, proliferation and cytokine production. Additionally, we co-cultured antigen-specific mouse T cells with artificial antigen presenting cells overexpressing CD271 and observed a partial inhibition of T cell proliferation in the presence of CD271. Further, although the proportion and activation state of immune cells are similar in adult CD271 knockout (KO) and control mice at steady-state, our preliminary data suggest that CD271 KO mice have a more severe phenotype in autoimmune models as compared to control animals. Together, these results demonstrate that CD271 modulates T cell function and may inform therapeutic approaches in autoimmunity and cancer.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".