Persistence in graft of Foxp3,TGFβ and IL-10 is hallmark of successful retransplantation of grafts after primary transplantation under cover of CD200 expression (126.21)
Bibliographic record
Abstract
Abstract We showed that overexpression of CD200, a molecule of the immunoglobulin supergene family, increases graft survival and suppresses inflammation/acquired immunity after binding to its receptors (CD200Rs). Skin/cardiac allograft survival is increased in transgenic mice over-expressing CD200 under control of a doxycycline-inducible promoter, (CD200tg), or following transplantation of CD200tg grafts to control mice, along with increased intra-graft expression of mRNAs implicated in Treg differentiation, including TGFβ, IL-10 and Foxp3. We have investigated whether C57BL/6 CD200tg grafts taken from control BALB/c mice at 14 days post transplantation can be successfully re-grafted into secondary control BALB/c mice, and whether such animals show perturbation of specific alloimmunity, and/or changes in graft gene expression in comparison to mice receiving control C57BL/6 grafts. Control grafts taken from mice at d14 and re-transplanted to control BALB/c mice were rejected rapidly, and with mice developing the expected CTL response in splenocytes detected by lysis of EL4 tumor targets in 4-hour 51Cr-release assays. In contrast, CD200tg grafts survived on secondary transfer to control BALB/c mice, with specific suppression of the cytotoxicitv response to EL4 targets. In these secondary recipients only, persistently high expression of Foxp3, IL-10 and TGFβ gene expression was seen. We conclude that expression of these latter genes is crucial for adoptive transfer of tolerance.
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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 | 0.001 |
| 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".