Reduced xenograft rejection in rat striatum after pretransplant photodynamic therapy of murine neural xenografts
Bibliographic record
Abstract
OBJECT: The goal of this study was to develop a method of reducing neural xenograft rejection by pretreating the graft with photodynamic therapy (PDT). METHODS: Xenograft cell suspensions were prepared from fetal mouse mesencephalon, after which they were incubated for 30 minutes with various concentrations of a photosensitizer, verteporfin for injection, and light exposure. The xenograft cell suspensions were injected into the dopamine-depleted striata of 40 hemiparkinsonian rats assigned to different treatment groups. Four weeks after transplantation, xenograft function (determined by methamphetamine-induced rotation) and survival (determined by immunohistochemical staining for murine neurons) were compared. Group 1 animals (xenografts pretreated with 25 ng/ml verteporfin) and Group 3 animals (no verteporfin pretreatment, but daily administration of cyclosporin A) had significantly better xenograft survival and function compared with control animals (no pretreatment with verteporfin). Group 2 animals (xenografts pretreated with 250 ng/ml verteporfin) had no significant improvement. CONCLUSIONS: This work demonstrates improved neural xenograft survival and function when using pretransplant PDT of the graft in a rodent model. The potential benefits of this new therapy are its convenience (one pretransplant treatment) and its compatibility with host immunosuppression.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".