Nucks1 gene polymorphism rs823114 is associated with the positive symptoms and neurocognitive function of patients with schizophrenia in parts of southern China
Bibliographic record
Abstract
Nuclear casein kinase and cyclin-dependent kinase substrate 1 (nucks1) are considered a potential susceptibility gene for certain neurological diseases, such as Parkinson's disease (PD). In our study, we genotyped three single nucleotide polymorphisms (SNPs) (rs4951261, rs823114 and rs951366) of the nucks1 gene in 774 schizophrenic patients and 819 healthy controls using the improved multiplex ligation detection reaction (imLDR) technique. Furthermore, we also studied the relationship between the above SNPs and the clinical psychiatric symptoms and neurocognitive function of the patients. Genotype distributions and allele frequencies of these SNPs showed no significant differences and were found between patients and healthy controls. However, in an analysis of the positive symptom score of rs823114 among male patients, we found that the score of the A/A genotype was lower than that of the G/A+G/G genotypes (P = 0.001, P(corr) = 0.003]. Additionally, we also found that among the female patients, G allele carriers with rs823114 had lower semantic fluency scores than subjects with the A/A genotype (P = 0.010, P(corr) = 0.030]. Our data show for the first time that rs823114 polymorphism of nucks1 may affect positive symptoms and neurocognitive function in patients with schizophrenia in parts of southern China.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".