BDNF gene polymorphisms and haplotypes in relation to cognitive performance in Polish healthy subjects
Bibliographic record
Abstract
The brain derived neurotrophic factor (BDNF) is a neurotrophin that plays an important role in the cell survival, axonal and dendritic growth, and synaptic plasticity. BDNF gene polymorphisms, 'functional Val66Met mainly, were shown to influence human brain structure and cognition. The aim of the study was to assess the relationship between twelve BDNF gene variants and their haplotypes and cognitive performance measured using the Wisconsin Card Sorting Test (WCST), the Trail Making Test (TMT), the Stroop Test which are to a large extent connected with prefrontal cortex activity. Our sample consisted of 460 healthy participants from Polish population. We detected possible association between five BDNF polymorphisms (rs11030101, rs10835210, rs2049046, rs2030324, rs2883187) and TMT_A. Additionally, one haplotype block made from eleven BDNF variants (rs2883187, rs1401635, rs2049046, rs2030324, rs11030101, rs10835210, rs1013402, rs1401635, rs1013402), as significant linkage disequilibrium appeared. We discovered possible relationships of CACCGCGTACG and CACCGCGTACG haplotypes with TMT_A and TMT_B performance respectively. Our results confirmed the involvement of BDNF in the regulation of psychomotor speed, working memory and executive function in healthy subjects measured by a task engaging visuoperceptual abilities.
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) | 0.001 | 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".