How air pollution alters brain development: the role of neuroinflammation
Bibliographic record
Abstract
The present review synthesizes lines of emerging evidence showing how several samples of children populations living in large cities around the world suffer to some degree neural, behavioral and cognitive changes associated with air pollution exposure. The breakdown of natural barriers warding against the entry of toxic particles, including the nasal, gut and lung epithelial barriers, as well as widespread breakdown of the blood-brain barrier facilitatethe passage of airborne pollutants into the body of young urban residents. Extensive neuroinflammation contributes to cell loss within the central nervous system, and likely is a crucial mechanism by which cognitive deficits may arise. Although subtle, neurocognitive effects of air pollution are substantial, apparent across all populations, and potentially clinically relevant as early evidence of evolving neurodegenerative changes. The diffuse nature of the neuroinflammation risk suggests an integrated neuroscientific approach incorporating current clinical, cognitive, neurophysiological, radiological and epidemiologic research. Neuropediatric air pollution research requires extensive multidisciplinary collaborations to accomplish the goal of protecting exposed children through multidimensional interventions having both broad impact and reach. While intervening by improving environmental quality at a global scale is imperative, we also need to devise efficient strategies on how the neurocognitive effects on local pediatric populations should be monitored.
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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) | 0.002 | 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".