Dioxins as potential risk factors for autism spectrum disorder
Bibliographic record
Abstract
Autism spectrum disorder (ASD) has emerged as a major public health concern due to its fast-growing prevalence in recent decades. Environmental factors are thought to contribute substantially to the variance in ASD. Interest in environmental toxins as causes of ASD has arisen due to the high sensitivity of the developing human brain to toxic chemicals, particularly to dioxin and certain dioxin-like compounds (dioxins). As a group of typical persistent organic pollutants, dioxins have been found to exert adverse effects on human brain development. In this paper, we review the evidence for association of exposure to dioxins with neurodevelopmental abnormalities related to ASD based on both human epidemiological and animal studies. It has been documented that exposure to dioxins during critical developmental periods increased risk for ASD. This notion has been demonstrated in different populations exposed to high or background level of dioxins. Furthermore, the effects and mechanisms of action of dioxins relevant to the pathophysiology and pathogenesis of ASD are summarized, describing potential underlying mechanisms linking dioxin exposure with ASD onset. Further studies focusing on effects of prenatal/perinatal exposure to individual dioxin congeners or to mixtures of dioxins on ASD-associated behavioral and neurobiological consequences in animal models, and on the mechanisms of actions of dioxins, are needed in order to better understand how dioxin exposure might contribute to increased risk for ASD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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; both teacher heads agree on what is shown here.
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".