World Trade Center neurotoxic exposures are associated with elevated plasma amyloid, total‐tau and neurofilament light in responders
Bibliographic record
Abstract
Abstract Background The collapse of the World Trade Center towers on September 11th 2001 resulted in a 16‐acre environmental toxic disaster. More than 1.2 million tons of construction material and carcinogens including polycyclic aromatic hydrocarbons, gypsum and metals coalesced, resulting in a highly alkaline dust cloud. Police and Law enforcement were among the most highly exposed group. Method In this retrospective cohort study, we included a subset of high exposure Responders (n=424) with cross sectional plasma samples of amyloid β 40, amyloid β 42, total‐tau, neurofilament light and a baseline evaluation of cognitive functioning assessed with the Montreal Cognitive Assessment (MoCA) to examine long‐term associations between WTC neurotoxic exposures (e.g. diesel exhaust, chemicals) with levels of proteins associated with neuropathological characteristics of Alzheimer’s disease and neurodegeneration. Spearman rho p values adjusted for multiple comparisons using the false discovery rate (FDR=0.05) examined associations with participant characteristics and plasma concentrations. Multivariate regressions ascertained independent effects of WTC neurotoxic exposures in predicting plasma biomarker concentrations. Result Responders were on average 54.3 years at blood draw. Worse performance on the baseline MoCA was associated with higher levels of Aβ 40. Plasma Aβ 40 and NfL were inversely correlated with dust exposure, Aβ 42 and ratio Aβ 42‐40 were inversely correlated with total hours on site during 9/11‐9/14 and working in enclosed work areas was associated with higher concentrations of Aβ 40 and lower concentrations of ratio Aβ 42‐40 . Diesel exhaust exposure predicted levels of Aβ 40, total tau and NfL whereas early exposure predicted Aβ 42 concentrations and dust exposure predicted ratio Aβ 42‐40 . Conclusion Differences across inhaled neurotoxins and time of arrival may have differential long‐term effects on blood‐based protein biomarkers of neuropathology and brain health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".