Behavioral improvement in a primate Parkinson's model is associated with multiple homeostatic effects of human neural stem cells
Bibliographic record
Abstract
Stem cells have been widely assumed to be capable of replacing lost or damaged cells in a number of diseases, including Parkinson's disease (PD), in which neurons of the substantia nigra (SN) die and fail to provide the neurotransmitter, dopamine (DA), to the striatum. We report that undifferentiated human neural stem cells (hNSCs) implanted into 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated Parkinsonian primates survived, migrated, and had a functional impact as assessed quantitatively by behavioral improvement in this DA-deficit model, in which Parkinsonian signs directly correlate to reduced DA levels. A small number of hNSC progeny differentiated into tyrosine hydroxylase (TH) and/or dopamine transporter (DAT) immunopositive cells, suggesting that the microenvironment within and around the lesioned adult host SN still permits development of a DA phenotype by responsive progenitor cells. A much larger number of hNSC-derived cells that did not express neuronal or DA markers was found arrayed along the persisting nigrostriatal path, juxtaposed with host cells. These hNSCs, which express DA-protective factors, were therefore well positioned to influence host TH+ cells and mediate other homeostatic adjustments, as reflected in a return to baseline endogenous neuronal number-to-size ratios, preservation of extant host nigrostriatal circuitry, and a normalizing effect on alpha-synuclein aggregation. We propose that multiple modes of reciprocal interaction between exogenous hNSCs and the pathological host milieu underlie the functional improvement observed in this model of PD.
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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) | 0.001 | 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".