Cerebral perfusion and tractography in obese children
Bibliographic record
Abstract
OBJECTIVE: To study the relationship of the structure of the white matter of the brain, neurovascularization and cognitive functions in obese children and adolescents. MATERIAL AND METHODS: The study included 64 obese patients, aged 12-17 years, and 54 children without excess body weight. A general clinical examination, neuropsychological testing (the Raven's test with the calculation of IQ, MoCA, the Rey 15-Item Memory Test (RMT), 1 and 2), magnetic resonance imaging (MR) tractography and contrast-free perfusion of the brain were conducted. RESULTS: Obese children and adolescents had both a decrease in scores on MoCA and the Raven's test, and in terms of IQ, while according to RMT-1, there were significant differences in the two groups, and in RMT-2 the results were comparable. Perfusion analysis showed a decrease in vascularization in the white matter area of the occipital lobe on the left and its increase in the temporal lobe area also on the left. When assessing the white matter according to MR tractography, a decrease in fractional anisotropy was noted in the area of the hook-shaped beam on the right and left, anterior and posterior commissural tracts. These changes were correlated with neuropsychological results. CONCLUSION: In obese children and adolescents, there was a destruction of the integrity of the white matter and neurovascularization of the brain associated with a deficit of cognitive functions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".