Attention-deficit/hyperactive disorder updates
Bibliographic record
Abstract
Background: Attention-deficit/hyperactive disorder (ADHD) is a neurodevelopmental disorder that commonly occurs in children with a prevalence ranging from 3.4 to 7.2%. It profoundly affects academic achievement, well-being, and social interactions. As a result, this disorder is of high cost to both individuals and society. Despite the availability of knowledge regarding the mechanisms of ADHD, the pathogenesis is not clear, hence, the existence of many challenges especially in making correct early diagnosis and provision of accurate management. Objectives: We aimed to review the pathogenic pathways of ADHD in children. The major focus was to provide an update on the reported etiologies in humans, animal models, modulators, therapies, mechanisms, epigenetic changes, and the interaction between genetic and environmental factors. Methods: References for this review were identified through a systematic search in PubMed by using special keywords for all years until January 2022. Results: . Some of these genes have evidence both from human beings and animal models, while others have evidence in either humans or animal models only. Notably, most of these animal models are knockout and do not generate the genetic alteration of the patients. Besides, some of the gene polymorphisms reported differ according to the ethnic groups. The majority of the available animal models are related to the dopaminergic pathway. Epigenetic changes including SUMOylation, methylation, and acetylation have been reported in genes related to the dopaminergic pathway. Conclusion: The dopaminergic pathway remains to be crucial in the pathogenesis of ADHD. It can be affected by environmental factors and other pathways. Nevertheless, it is still unclear how environmental factors relate to all neurotransmitter pathways; thus, more studies are needed. Although several genes have been related to ADHD, there are few animal model studies on the majority of the genes, and they do not generate the genetic alteration of the patients. More animal models and epigenetic studies are required.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".