Differential response of sensory and motor axons in nerve allografts after withdrawal of immunosuppressive therapy
Bibliographic record
Abstract
OBJECT: Rejection of nerve allografts and loss of regenerated host axons after withdrawal of immunosuppressive therapy poses an ongoing challenge in peripheral nerve repair. The present report is of a blinded prospective controlled study in which an established rat model of nerve allotransplantation is used to examine the effect of fiber type on survival and degeneration of nerve allografts after discontinuation of immunosuppression. The authors hypothesized that sensory axons will selectively resist a rejection response, whereas motor axons will degenerate. METHODS: Four-centimeter nerve segments from ACI rats were grafted into peroneal and sural (mixed) or saphenous (sensory) nerve gaps in Lewis rats. In some rats, L4-6 dorsal root ganglia were ablated before grafting, creating pure motor sural and peroneal nerves. All rats received 12 weeks of immunosuppressive therapy to support nerve regeneration into allografts. Immunosuppression with cyclosporin was then withdrawn. At planned death (12-18 weeks postsurgery), graft tissue was subjected to histomorphometric analysis for evaluation of axon survival and loss. Graft rejection led to loss of all axons in approximately 60% of the allograft segments. The mixed nerve group was most prone to complete rejection, with significantly lowered axon counts at Weeks 16 and 18 compared with the Week 12 baseline. Axons from the sensory nerve were least likely to degenerate. The pure motor nerve group axons demonstrated intermediate sensitivity, with a selective loss of larger axons at Week 16 and a significant decrease in axon counts from the Week 12 baseline at Week 18. CONCLUSIONS: Whereas the majority of axons are lost after withdrawal of immunosuppressive therapy from nerve allografts, there is a selective survival of axons from cutaneous sensory nerves and smaller-diameter motor fibers. The biological and molecular mechanisms that make some axons impervious to injury remain to be determined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".