TREATMENT WITH ANTI-CD154 ANTIBODY AND DONOR-SPECIFIC TRANSFUSION PREVENTS ACUTE REJECTION OF MYOBLAST TRANSPLANTATION1
Bibliographic record
Abstract
BACKGROUND: Achieving immunological tolerance to transplanted myoblasts would reduce the adverse effects associated with the sustained immunosuppression required for this experimental therapeutic approach in Duchenne muscular dystrophic patients. METHODS: Mdx mice were transplanted with fully allogeneic BALB/c myoblasts in the tibialis anterior muscles. Seven days before transplantation (-7), host mice received 107 total donor spleen cells i.v. (donor-specific transfusion, DST) with 500 microg of anti-CD154 mAb i.p. on days -7, -4, 0, +4. RESULTS: Results showed a high level of dystrophin expression in 83, 60, and 20% of the mice 1, 3, and 6 months, respectively, after transplantation of myoblasts. No antibodies against the donor cells were produced up to 3 months after transplantation. However, abundant activated cytotoxic cells were present in muscles still expressing high percentage of dystrophin positive fibers. CONCLUSIONS: In conclusion, the DST + anti-CD154 mAb treatments effectively prolonged myoblast survival, but this treatment could not develop tolerance to complete allogeneic myoblast transplantation.
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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".