Bibliographic record
Abstract
Dopaminergic neurons of the substantia nigra are particularly vulnerable to oxidative and inflammatory attack. Such processes may play a crucial role in the etiology of Parkinson disease (PD). Since glia are the main generators of these processes, the possibility that PD may be caused by glial dysfunction needs to be considered. This review concentrates on glial reactions in PD. Reactive astrocytes and reactive microglia are abundant in the substantia nigra (SN) of PD cases indicating a robust inflammatory state. Glia normally serve neuroprotective roles but, given adverse stimulation, they may contribute to damaging chronic inflammation. Microglia, the phagocytes of brain, may be the main contributors since they can produce large numbers of superoxide anions and other neurotoxins. Their toxicity towards dopaminergic neurons has been demonstrated in tissue culture and various animal models of PD. The MPTP and alpha-synuclein models are of particular interest. Years after exposure to MPTP, inflammation has been observed in the SN. This has established that an acute insult to the SN can result in a sustained local inflammation. The alpha-synuclein model indicates that an endogenous protein can induce inflammation, and, when overexpressed, can lead to autosomal dominant PD. Less is known about the role of astrocytes than microglia, but they are known to secrete both inflammatory and anti-inflammatory molecules and may play a role in modulating microglial activity. Oligodendrocytes do not seem to play a role in promoting inflammation although, like neurons, they may be damaged by inflammatory processes. Further research concerning glial reactions in PD may lead to disease-modifying therapeutic approaches.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".