The immune system in Parkinson's disease: what we know so far
Bibliographic record
Abstract
Parkinson's disease is characterized neuropathologically by the degeneration of dopaminergic neurons in the ventral midbrain, the accumulation of α-synuclein (α-syn) aggregates in neurons and chronic neuroinflammation. In the past two decades, in vitro, ex vivo and in vivo studies have consistently shown the involvement of inflammatory responses mediated by microglia and astrocytes, which may be elicited by pathological α-syn or signals from affected neurons and other cell types, and are directly linked to neurodegeneration and disease development. Apart from the prominent immune alterations seen in the CNS, including the infiltration of T cells into the brain, more recent studies have demonstrated important changes in the peripheral immune profile within both the innate and adaptive compartments, particularly involving monocytes, CD4+ and CD8+ T cells. This review aims to integrate the consolidated understanding of immune-related processes underlying the pathogenesis of Parkinson's disease, focusing on both central and peripheral immune cells, neuron-glia crosstalk as well as the central-peripheral immune interaction during the development of Parkinson's disease. Our analysis seeks to provide a comprehensive view of the emerging knowledge of the mechanisms of immunity in Parkinson's disease and the implications of this for better understanding the overall pathogenesis of this disease.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".