Associations between brain‐derived neurotrophic factor and cognitive impairment in panic disorder
Bibliographic record
Abstract
INTRODUCTION: Our study was designed to examine the relationship between Brain-Derived Neurotrophic Factor (BDNF) genotypes (rs6265, Val66Met), BDNF plasma levels, and cognitive impairment in Chinese patients with panic disorder (PD). METHODS: Total 85 patients with PD and 91 healthy controls finally completed all assessments. The severity of panic symptoms and whole anxiety of PD was measured by Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and Hamilton Anxiety Scale (HAMA-14). Montreal Cognitive Assessment (MoCA) and some neurocognitive measures were conducted to evaluate the cognitive performance. All participants were detected for the plasma BDNF levels and BDNF Val66Met polymorphism before assessment and treatment. RESULTS: No significant differences were found in the BDNF allele frequencies and the BDNF genotype distributions between healthy controls and PD patients. BDNF Met/Met genotype was associated with lower BDNF plasma levels in PD patients, and PD patients with BDNF Met/Met genotype had the lower scores in the attention and speed of processing domains compared to those with Val/Val and Met/Val genotype (p's < .05). Among PD patients, the BDNF plasma levels showed moderate positive correlations with Stroop interference (r = .60, p < .001). Using the MoCA data, the BDNF plasma levels were correlated with delayed memory (r = .50, p < .001), verbal learning (r = .45, p < .001), and total scores of MoCA (r = .51, p < .001). CONCLUSIONS: The BDNF Met/Met genotype may be associated with lower BDNF plasma levels and cognitive impairments in PD patients.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".