The effects of <scp><i>AQP4</i></scp> rs162009 on <scp>resting‐state</scp> brain activity in Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: We previously identified a significant association between Aquaporin-4 (AQP4) and Parkinson's disease (PD). OBJECTIVES: To identify whether AQP4 single-nucleotide polymorphism (SNP) rs162009 affects regional brain activity and clinical phenotypes of PD. METHODS: Low-frequency fluctuation amplitude (ALFF) was used to evaluate spontaneous brain activity, regional homogeneity (ReHo) was used to evaluate the pace of activity of adjacent voxel regions, and degree centrality (DC) was used to describe the functional connection strength between a voxel and the whole brain. Disease severity and PD stage were assessed with the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale and Hoehn and Yahr scales, and the Montreal Cognitive Assessment (MoCA) was used to assess the participants' cognitive function. RESULTS: In patients with PD, AQP4 SNP rs162009 was associated with a significant higher ALFF in the right caudate head and the left occipital gyrus, a significant lower ReHo in the right inferior frontal gyrus, a different DC in the right frontal gyrus, the left calcarine, and the right inferior temporal gyrus. A significant positive correlation between ALFF in the right caudate head and MoCA in rs162009_A carriers was found. A significant negative correlation between the DC at the left calcarine and MDS-UPDRS and MDS-UPDRS III in rs162009_A noncarriers was found. CONCLUSIONS: Our study further revealed the effect of AQP4 SNP rs162009 on brain activity in PD, indicating that AQP4 may play an important role in PD neuropathophysiology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".