Impact of sex on neuroimmune contributions to Parkinson’s disease
Bibliographic record
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Inflammation has been observed in both the idiopathic and familial forms of PD. Importantly, PD is reported more often in men than in women, men having at least 1.5- fold higher risk to develop PD than women. This review summarizes the impact of biological sex and sex hormones on the neuroimmune contributions to PD and its investigation in animal models of PD. Innate and peripheral immune systems participate in the brain neuroinflammation of PD patients and is reproduced in neurotoxin, genetic and α-synuclein based models of PD. Microglia and astrocytes are the main cells of the innate immune system in the central nervous system and are the first to react to restore homeostasis in the brain. Analysis of serum immunoprofiles in female and male control and PD patients show that a great proportion of these markers differ between males and females. The relationship between cerebrospinal fluid inflammatory markers and PD clinical characteristics or PD biomarkers shows sex differences. Conversely, in animal models of PD, sex differences in inflammation are well documented and the beneficial effects of endogenous and exogenous estrogenic modulation in inflammation have been reported. Targeting neuroinflammation in PD is an emerging therapeutic option but gonadal drugs have not yet been investigated in this respect, thus offering new opportunities for sex specific treatments.
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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) | 0.001 | 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) | 0.003 | 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".