Neurological susceptibility to environmental exposures: pathophysiological mechanisms in neurodegeneration and multiple chemical sensitivity
Bibliographic record
Abstract
The World Health Organization lists air pollution as one of the top five risks for developing chronic non-communicable disease, joining tobacco use, harmful use of alcohol, unhealthy diets and physical inactivity. This review focuses on how host defense mechanisms against adverse airborne exposures relate to the probable interacting and overlapping pathophysiological features of neurodegeneration and multiple chemical sensitivity. Significant long-term airborne exposures can contribute to oxidative stress, systemic inflammation, transient receptor subfamily vanilloid 1 (TRPV1) and subfamily ankyrin 1 (TRPA1) upregulation and sensitization, with impacts on olfactory and trigeminal nerve function, and eventual loss of brain mass. The potential for neurologic dysfunction, including decreased cognition, chronic pain and central sensitization related to airborne contaminants, can be magnified by genetic polymorphisms that result in less effective detoxification. Onset of neurodegenerative disorders is subtle, with early loss of brain mass and loss of sense of smell. Onset of MCS may be gradual following long-term low dose airborne exposures, or acute following a recognizable exposure. Upregulation of chemosensitive TRPV1 and TRPA1 polymodal receptors has been observed in patients with neurodegeneration, and chemically sensitive individuals with asthma, migraine and MCS. In people with chemical sensitivity, these receptors are also sensitized, which is defined as a reduction in the threshold and an increase in the magnitude of a response to noxious stimulation. There is likely damage to the olfactory system in neurodegeneration and trigeminal nerve hypersensitivity in MCS, with different effects on olfactory processing. The associations of low vitamin D levels and protein kinase activity seen in neurodegeneration have not been studied in MCS. Table 2 presents a summary of neurodegeneration and MCS, comparing 16 distinctive genetic, pathophysiological and clinical features associated with air pollution exposures. There is significant overlap, suggesting potential comorbidity. Canadian Health Measures Survey data indicates an overlap between neurodegeneration and MCS (p < 0.05) that suggests comorbidity, but the extent of increased susceptibility to the other condition is not established. Nevertheless, the pathways to the development of these conditions likely involve TRPV1 and TRPA1 receptors, and so it is hypothesized that manifestation of neurodegeneration and/or MCS and possibly why there is divergence may be influenced by polymorphisms of these receptors, among other factors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.003 | 0.001 |
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".