Stress accelerates neural degeneration and exaggerates motor symptoms in a rat model of Parkinson's disease
Bibliographic record
Abstract
The causes of most cases of Parkinson's disease (PD) are still poorly understood. Here we show that chronic stress and elevated corticosterone levels exaggerate motor deficits and neurodegenerative events in a Parkinson's disease rat model. Animals were tested in skilled and non-skilled movement while being exposed to daily restraint stress or oral corticosterone treatment. Stress and corticosterone compromised normal motor function and exaggerated motor deficits caused by unilateral 6-hydroxydopamine lesion of the nigrostriatal bundle. Moreover, stress and corticosterone treatments diminished the ability to acquire compensatory strategies in limb use during skilled reaching and skilled walking. In contrast, lesion control animals were able to significantly improve in the ability of skilled limb use during the repeated test sessions. The exaggerated motor impairments in stress-treated animals were related to accelerated loss of midbrain dopamine-producing neurons during the first week postlesion. Correlation analysis revealed a significant connection between loss of tyrosine hydroxylase-positive cells and increase in Fluoro-Jade-positive cells only in stress- and corticosterone-treated animals. Furthermore, stress and elevated corticosterone levels caused greater permanent loss of midbrain neurons than found in non-treated lesion animals. These findings demonstrate that stress and elevated corticosterone levels can exaggerate nigral neuronal loss and motor symptoms in a rat analogue of PD. It is therefore possible that stress represents a key factor in the pathogenesis of human PD by impeding functional and structural compensation and exaggerating neurodegenerative processes.
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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) | 0.001 | 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".