Correlation Between Brain-Derived Neurotrophic Factor and Cognitive Function in Older Adults
Bibliographic record
Abstract
<p style="font-size: medium; color: #000000;"><strong>Aim</strong> Brain Derived Neurotrophic Factor (BDNF) plays a crucial role in supporting neuronal survival, promoting neurogenesis, and enhancing synaptic plasticity, all of which are vital for cognitive health. Aim of this study was to investigate the relationship between BDNF levels and cognitive impairment in the elderly population.</p> <p style="font-size: medium; color: #000000;"><strong>Methods</strong> This was a cross-sectional study involving older adults at a social service care. Cognitive function was assessed using the Montreal Cognitive Assessment-Indonesian Version (MoCA-INA). BDNF levels were measured in peripheral blood samples using the Enzyme-Linked Immunosorbent Assay.</p> <p style="font-size: medium; color: #000000;"><strong>Results </strong>Of the 88 participants (50 females 38 males) with a median age of 69.5 years, 71 (80.7%) had cognitive impairment. The median MoCA-INA score was 15.0. The most affected cognitive domain was abstraction, absolute number of patients 87 patients (98.9%). The mean BDNF level was 1.55 (±0.62) ng/mL with 50 (56.8%) patients having normal level. A weak positive correlation was found between BDNF level and performance in the visuospatial-executive (r= 0.232; p=0.029) and abstraction domains (r= 0.249; p=0.019). BDNF levels were significantly lower in those with cognitive impairment compared to those with normal cognitive function (p=0.029).</p> <p style="font-size: medium; color: #000000;"><strong>Conclusion</strong> A correlation between BDNF levels and cognitive function, particularly in the visuospatial-executive and abstraction domains, highlighting the potential role of BDNF in cognitive decline in aging.</p> <p style="font-size: medium; color: #000000;"> </p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".