Dissecting the Heterogeneity of Autism: Focus on Phelan-McDermid Syndrome
Bibliographic record
Abstract
Introduction Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders that show delays and deficits in the development of multiple brain functions, which are characterized by social communication, poor language development, and restricted and stereotyped patterns of interests and behaviours. ASD affects about 1-2 % of the population and are considered to be highly genetic in nature. Structural variations of chromosomes have been identified in some ASD individuals, most common on chromosome 7q, 15q and 22q. Objectives 1-To present a systematic literature review of the natural history of individuals with 22q13.3 deletion syndrome, Phelan-McDermid syndrome (PMS). PMS, increase awareness of different phenotypes 2- Correlation of clinical manifestations of PMS with hypothesized underlying biological mechanisms 3-Rational for novel treatments is inferred through translational neuroscience approaches. Methods We have conducted a systematic literature review of the natural history of individuals with PMS, including both cross-sectional and long-term longitudinal analyses and correlation with hypothesized underlying biological mechanisms, including roles in regulation synaptic development, function, and plasticity. This systematic review includes the basis for a promising common pathway for ASD pathogenesis and the clinical implications of novel therapeutic strategies inferred through translational neuroscience approaches. Results This systematic review, therefore, outlines the: (1) Pathophysiological basis and clinical manifestations of PMS; (2) PMS pre-clinical models and applications to ASD; and (3) clinical implications of novel therapeutic strategies. Conclusions A promising common pathway for ASD pathogenesis and rational for novel treatments is inferred through translational neuroscience approaches. Neurobiological basis for lithium treatment is indeed supported by experimental results and current clinical findings. Disclosure No significant relationships.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".