Genetic and Developmental Perspective of Language Abnormality in Autism and Schizophrenia
Bibliographic record
Abstract
Language and communication through it are two of the defining features of normally developed human beings. However, both these functions are often impaired in autism and schizophrenia. In the former disorder, the problem usually emerges in early childhood (~2 years old) and typically includes a lack of communication. In the latter condition, the language problems usually occur in adolescence and adulthood and presents as disorganized speech. What are the fundamental mechanisms underlying these two disorders? Is there a shared genetic basis? Are the traditional beliefs about them true? Are there any common strategies for their prevention and management? To answer these questions, we searched PubMed by using autism, schizophrenia, gene, and language abnormality as keywords, and we reconsidered the basic concepts about these two diseases or syndromes. We found many functional genes, for example, FOXP2, COMT, GABRB3, and DISC1, are actually implicated in both of them. After observing the symptoms, genetic correlates, and temporal progression of these two disorders as well as their relationships more carefully, we now infer that the occurrence of these two diseases is likely developmentally regulated via interaction between the genome and the environment. Furthermore, we propose a unified view of autism and schizophrenia: a single age-dependently occurred disease that is newly named as Systemic Integral Disorder: if occurring in children before age 2, it is called autism; if in adolescence or a later age, it is called schizophrenia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".