The Tree Shrew Model of Parkinson Disease: A Cost-Effective Alternative to Nonhuman Primate Models
Bibliographic record
Abstract
The surge in demand for experimental monkeys has led to a rapid increase in their costs. Consequently, there is a growing need for a cost-effective model of Parkinson disease (PD) that exhibits all core clinical and pathologic phenotypes. Evolutionarily, tree shrews (Tupaia belangeri) are closer to primates in comparison with rodents and could be an ideal species for modeling PD. To develop a tree shrew PD model, we used the 1-methyl-4-phenylpyridinium (MPP & thorn;), a metabolite derived from 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, to induce lesions in dopaminergic neurons of the unilateral substantia nigra. The induced tree shrew model consistently exhibited and maintained all classic clinical manifestations of PD for a 5-month period. The symptoms included bradykinesia, rest tremor, and postural instability, and -50% individuals showed apomorphine-induced rotations, a classic phenotype of unilateral PD models. All these are closely resembled the ones observed in PD monkeys. Meanwhile, this model was also sensitive to L-dopa treatment in a dose-dependent manner, which suggested that the motor deficits are dopamine dependent. Immunostaining showed a significant loss of dopaminergic neurons (-95%) in the lesioned substantia nigra, which is a crucial PD pathological marker. Moreover, a control group of nigral saline injection did not show any motor deficits and pathological changes. Cytomorphologic analysis revealed that the size of nigral dopaminergic neurons in tree shrews is much bigger than that of rodents and is close to that of macaques. The morphologic similarity may be an important structural basis for the manifestation of the highly similar phenotypes between monkey and tree shrew PD models. Collectively, in this study, we have successfully developed a PD model in a small animal species that faithfully recapitulated the classic clinical symptoms and key pathological indicators of PD monkeys, providing a novel and low-cost avenue for evaluation of PD treatments and underlying mechanisms. (c) 2024 THE AUTHORS. Published by Elsevier Inc. on behalf of the United States & Canadian Academy of Pathology. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".