TECHNICAL FACTORS AND IMMUNOSUPRESSION LEVELS FOR THE SUCCESS OF CLINICAL MYOBLAST TRANSPLANTATION.
Bibliographic record
Abstract
P679 Aims: Our previous pre-clinical (cynomolgus monkey) and clinical studies demonstrated that myoblast transplantation can be successful if multiple close parallel injections (MCPI) of cells are performed, and if FK506 is used for immunosuppression. We progressed here in defining technical and immunosuppression parameters that may be useful in planning successful clinical myoblast transplantation. Methods: Adult Macaca fascicularis monkeys were used as hosts of myoblast allotransplantation. Myoblasts derived from skeletal muscles were proliferated in vitro, labeled with a retroviral vector containing the LacZ gene, and injected by MCPI in limb muscles. We tested different needle sizes, inter-injection distances and numbers of cells by injection. Monkeys were immunosuppressed with FK506 at high (mean blood levels between 50 to 70 μg/L) and mild (mean blood levels between 10 and 30 μg/L) dosages. Results: MCPI with 18G-needles produced generally a better success than using 22G- and 27G-needles at an inter-injection distance of 2 mm, the success of each single injection being proportional to the tissular damage produced by each needle trajectory. However, 18G needles produced more bleeding during transplantation, muscle regeneration was not complete after 1 month, and some fibrosis was observed at 2 months. An inter-injection distance of 2 mm did not produce more than 15% of β-Gal+ fibers using 22G or 27G needles. The percentages increased to 30 to 45% when the inter-injection distance was 1 mm, but at least 100,000 myoblasts cells were needed by cm of single-injection trajectory (10,000 myoblasts by cm of individual injection led to only 5-15% of β-Gal+ myofibers). Increasing to 1x106 myoblasts per cm of single-injection trajectory has sometimes increased success. Conclusions: Needles of 22G to 27G sizes should be the choice for myoblast transplantation by MCPI, using an inter-injection distance of 1 mm. The number of cells to be delivered by cm of single-injection trajectory should be of at least 100,000. An FK506 monotherapy with blood levels similar to those attained in humans did not prevent a slow delayed acute rejection of the β-Gal+ myofibers, and higher dosages were needed for prevent it. Pre-clinical studies combining FK506 with other immunosuppressants and studies on immunological tolerance in the context of myoblast transplantation seem of importance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".