Impact of aging on the central and enteric nervous system in a Parkinson’s disease mouse model
Bibliographic record
Abstract
The etiopathogenesis of Parkinson's Disease (PD) remain poorly understood, particularly the roles of aging and the gut-brain axis. This study investigated the impact of aging on the development of PD hallmarks, including neurodegeneration and inflammation, in both the central (CNS) and enteric (ENS) nervous system of mice following exposure to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Young (2-4 months) and adult (7-12 months) mice were treated with either saline or MPTP (four intraperitoneal injections of 8 mg/kg at 2-hour intervals). Postmortem inflammatory and neuronal endpoints were compared in both the nigrostriatal pathway and the myenteric plexus. While age did not alter the MPTP-induced reduction in TH-positive cells in the striatum and substantia nigra pars compacta (SNpc), we observed a greater sensitivity of enteric DAergic neurons to MPTP neurotoxicity with age. Notably, MPTP treatment elicited a more prominent inflammatory response in the SNpc and the myenteric plexus in older animals, as assessed with Iba1 and GFAP immunofluorescence on brain sections. We also observed enteric and central inflammation, an increase in oxidative stress in the SNpc measured with Nrf2, and a loss of enteric DAergic neurons with aging, comparable to what is observed in young mice treated with MPTP. The enhanced vulnerability of the ENS is consistent with the observation that intestinal symptoms precede motor symptoms in PD, suggesting that immunosenescence in the gastrointestinal tract contributes to the early development and progression of PD.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".