Developmental Neurobiology: Implications for Pediatric Psychopharmacology
Bibliographic record
Abstract
Pediatric psychopharmacology can only be properly understood within the context of developmental neurobiology. Normal maturation of the brain is characterized by the complex anatomic, molecular, and organizational changes required for optimal adaptive functioning. In many areas of the developing nervous system, neurons, cell processes, neurotransmitters, and trophic nerve growth factors are produced in far greater numbers and in different areas than in the mature brain. Psychopathology and stressful environments can lead to enduring changes in brain structure and functioning. A few select psychopharmacological treatments are reviewed to assess their potential impact on CNS development. More clinical and basic science studies are needed to determine whether current treatments have neurotoxic or neuroprotective effects when administered over extended critical early periods of the lifespan. La psychopharmacologie pédiatrique ne peut être bien comprise que dans le contexte de la neurobiologie du développement. La maturation normale du cerveau est caractérisée par les changements anatomiques, moléculaires et organisationnels complexes nécessaires à l'apprentissage fonctionnel optimal. Dans de nombreuses zones du système nerveux en développement, les neurones, les transformations des cellules, les neurotransmetteurs et les facteurs de croissance du nerf trophique sont produits en bien plus grand nombre que dans le cerveau parvenu à maturité, et dans des secteurs différents. La psychopathologie et les milieux stressants peuvent entraîner des changements permanents de la structure et du fonctionnement du cerveau. Quelques traitements psychopharmacologiques choisis sont examinés pour en évaluer l'effet potentiel sur le développement du système nerveux central. D'autres études cliniques et scientifiques fondamentales sont nécessaires pour déterminer si les traitements actuels ont des effets neurotoxiques ou neuroprotecteurs, lorsqu'on les administre sur une période prolongée durant les premières phases critiques de la durée de vie.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".