Investigation of brain-derived neurotrophic factor as a diagnostic marker of neuroplasticity in children with motor disorder delay
Bibliographic record
Abstract
The relevance of researching biomarkers of neuroplasticity lies in the growing prevalence of motor disorders in children, as timely diagnosis and early intervention are critical for improving prognosis. The aim of the study was to evaluate the diagnostic significance of brain-derived neurotrophic factor levels as a potential marker of neuroplasticity in children aged 7-8 months with motor development delay through an integrated analysis of gestational age, body weight, motor skills according to the Alberta Infant Motor Scale, and brain-derived neurotrophic factor concentration. The study involved 25 healthy children aged 7-8 months without motor disorders and 56 children of the same age with motor development delay, including 28 children who were born full-term but had motor disorders and 28 children who were born prematurely with motor disorders. The study found a significant correlation between the level of brain-derived neurotrophic factor in blood serum and the degree of motor development impairment in children. Median levels of brain-derived neurotrophic factor were highest in the control group (22.76 pg/mL) and progressively decreased in groups with motor development disorders (11.25 pg/mL and 8.30 pg/mL). Statistically significant differences in serum brainderived neurotrophic factor levels were found between all study groups (p < 0.00001). The results indicated that children with motor development disorders had significantly lower levels of brain-derived neurotrophic factor than their healthy peers, which may indicate reduced neuroplasticity in these groups. These results highlighted the potential of brainderived neurotrophic factor as an objective criterion for early diagnosis, prognosis, and evaluation of the effectiveness of rehabilitation interventions in children with motor development delays
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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 | 0.001 | 0.015 |
| 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 | 0.001 |
| 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 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".