Endogenous Expression of B7-H4 Improves Long-term Murine Islet Allograft Survival
Bibliographic record
Abstract
BACKGROUND: Allograft rejection is one of the main obstacles for islet transplantation. B7-H4 plays a key role in maintaining T-cell homeostasis by reducing T-cell proliferation and cytokine production. In this study, we investigated whether the endogenous expression of B7-H4 in β cells from B7-H4 transgenic mice enhances islet allograft survival. METHODS: B7-H4 transgenic C57BL/6 (B6) mice (RIP.B7-H4) were developed by inserting the entire B7-H4 open reading frame under the rat insulin promoter (RIP). B7-H4 protein expression was examined by flow cytometric analysis and immunohistochemical staining. Islet allograft survival was investigated in streptozotocin-induced diabetic recipient BALB/c (H-2d) mice transplanted with 400 islets from RIP.B7-H4 (H-2b) mice under the kidney capsule. The recipient control group received islets from wild-type B6 donors. RESULTS: B7-H4 protein was significantly up-regulated in isolated islets from RIP.B7-H4 compared with wild-type B6 mice (56%±23% vs. 3%±1.2%). B7-H4 was coexpressed with insulin, but not glucagon, suggesting that B7-H4 is expressed in a β-cell-specific manner. Recipient BALB/c mice transplanted with RIP.B7-H4 islets established euglycemia for 42.3±18.4 days (mean±SD; n=9) compared with controls at 23.1±7.8 days (mean±SD; n=12; P<0.004, log-rank test). CONCLUSIONS: The endogenous expression of B7-H4 in donor β cells from transgenic mice prolongs islet allograft survival, confirming the negative role of B7-H4 in regulating alloreactive T-cell responses.
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) | 0.001 | 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 | 0.001 |
| 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".