Suppression of Human T-Cell Responses to β-Cells by Activation of B7-H4 Pathway
Bibliographic record
Abstract
B7-H4, a recently described member of the B7 family of cosignal molecules, is thought to be involved in the regulation of cellular and humoral immune responses through receptors on activated T and B cells. Human islet cells express positive B7-H4 mRNA in RT-PCR assays, but not B7-H4 protein on cell surface in flow cytometric analyses. To investigate the regulatory effects of activation of the B7-H4 pathway on the function of activated T cells of patients with type 1 diabetes (T1D), we have used our in vitro human experimental system, including human beta-cell antigen-specific T-cell clones and human beta-cell lines CM and HP62, as well as primary islet cells. B7-H4.Ig protein was purified from the culture supernatant of 293T cells transfected by a B7-H4.Ig plasmid (pMIgV, containing a human B7-H4 cDNA and a mouse IgG2a Fc cDNA). Our preliminary studies showed that immobilized fusion protein human B7-H4.Ig (coated with 5 microg/ml for 2 h at 37 degrees C), but not control Ig, clearly inhibited the proliferation of activated CD4+ and CD8+ T cells of patients induced by anti-CD3 antibody in CFSE assays. B7-H4.Ig also arrested cell cycle progression of T cells in G0/G1 phase and induced T-cell apoptosis as measured by BrdU-7-AAD flow cytometric analysis. To determine the cytoprotective effects of B7-H4, we developed transfectants of human beta-cell lines CM and HP62 and islet cells transfected with the B7-H4.Ig plasmid, using empty vector transfectants as controls. The results demonstrate that cell-associated B7-H4.Ig expressed on human beta-cells clearly inhibits the cytotoxicity of the T-cell clones to targeted human beta-cells in 51Cr release cytotoxicity assays. Activation of the B7-H4 pathway may represent a novel immunotherapeutic approach to inhibit T-cell responses for the prevention of beta-cell destruction in T1D.
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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".