PI3K polymorphism in patients with sporadic Parkinson’s disease
Bibliographic record
Abstract
Parkinson's disease (PD) is a common irreversible neurodegenerative disease associated with cognitive impairment. To investigate the serum level of phosphatidylinositol-3-kinase (PI3K) and the distribution of the genotypes and alleles of 3 PI3K single-nucleotide polymorphisms (RS37,30,087, RS37,30,088, and RS37,30,089) in PD patients with different clinical characteristics. A total of 54 PD patients and 50 healthy individuals were recruited. The serum PI3K level was measured using the enzyme-linked immunosorbent assay. The severity of PD was assessed using the modified Hoehn-Yahr scale. The cognitive function of PD patients was evaluated using the Mini-Mental State Examination scale and the Montreal Cognitive Assessment. The distribution of the alleles and genotypes of PI3K single-nucleotide polymorphisms (SNPs) was calculated using the Hardy-Weinberg equilibrium. PD patients showed a significantly higher serum level of PI3K compared to healthy individuals. Increased serum PI3K level was observed in PD patients with more severe disease, longer disease duration, and impaired cognitive function. Additionally, no significant differences were observed in the distributions of the genotypes and alleles of 3 PI3K SNPs between PD patients with normal cognitive function and those with cognitive impairment. PD patients with different levels of disease severity, disease duration, and cognitive function had significantly different serum levels of PI3K. However, the PI3K SNPs in patients with normal cognitive function were not significantly different from those in patients with cognitive impairment. These findings contribute to a better understanding of the roles of PI3K and SNPs of the PI3K gene in 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".