A cloaked human stem-cell-derived neural graft capable of functional integration and immune evasion in rodent models
Bibliographic record
Abstract
Human pluripotent stem cell (hPSC)-derived therapies are a realistic possibility for numerous disorders, including Parkinson's disease. While generating replacement neurons is achievable, immunosuppressive drug challenges, to prevent rejection, remain. Here we adopted a hPSC line (termed H1-FS-8IM), engineered to overexpress 8 immunomodulatory transgenes, to enable transplant immune evasion. In co-cultures, H1-FS-8IM PSC-derived midbrain neurons evaded rejection by T lymphocytes, natural killer cells, macrophages, and dendritic cells. In humanized mice, allogeneic H1-FS-8IM neural grafts evaded rejection, while control hPSC-derived neural grafts evoked activation of human immune cells, elevated inflammatory cytokines in blood and cerebrospinal fluid, and caused spleen and lymph node enlargement. H1-FS-8IM neural grafts retained functionality, reversing motor deficits in Parkinsonian rats. Additional incorporation of a suicide gene into the H1-FS-8IM hPSC line enabled proliferative cell elimination within grafts. Findings demonstrate feasibility of generating a population-wide applicable, safe, off-the-shelf cell product, suitable for treating diseases for which cell-based therapies are a viable option.
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 | 0.000 | 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 | 0.000 |
| 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".