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Antioxidant Activity is Associated With Neurocognitive Protection After World Trade Center Particulate Matter Exposure

2025· article· en· W4410272680 on OpenAlexaboutno aff
A. Fallah Zadeh, Sophia Kwon, H.L. Bernier, Jin Zhou, Daniel Kim, S. Podury, Theresa Schwartz, Rachel Zeig‐Owens, David J. Prezant, Meilin Liu, Anna Nolan

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsWorld trade centerMedicineNeurocognitiveParticulatesAntioxidantEnvironmental healthPsychiatryCognitionEcology

Abstract

fetched live from OpenAlex

Abstract RATIONALE Particulate matter (PM) exposure during the World Trade Center (WTC) destruction caused several short- and long-term complications, especially among first-responder firefighters. Other groups have found that WTC responders with high PM exposure had significantly higher risk of early-onset dementia. Oxidative stress has been linked to accelerated epigenetic aging and cognitive decline. We quantified aging-related biomarkers, antioxidant levels, and cognitive measures in WTC-exposed firefighters. METHODS. We enrolled subjects from a random sub-cohort of 20% of firefighters consented as part of the FDNY WTC-Health-Program with normal pre-9/11 lung function. Recruited subjects were invited for repeat blood sampling and cognitive assessment (Montreal Cognitive Assessment [MoCA] and Mini-Mental State Examination [MMSE]), ClinicalTrials.gov#NCT05216133. Fasting plasma samples were banked at -80° C, thawed once, and assayed for CTACK, FGF-21, GDF-11, GDF-15, GnRH, Leptin (Millipore), total antioxidant capacity (TAC), and superoxide dismutase (SOD) activity (Abcam). Binary logistic regression compared participants with mild cognitive impairment (MCI), defined as a MoCA<26 or MMSE<25, to non-MCI (SPSSv28). RESULTS Of the 29 enrolled participants, N=9 (31%) had MCI. There was no significant difference in age between MCI and non-MCI (61.4 vs 64.7 years, p=0.29). MCI scored significantly lower in mean executive functions (3.5 vs 4.5), delayed recall (1.7 vs 3.6), and memory index (10 vs 13) compared to non-MCI, p<0.05. No subjects were found to have severe cognitive impairment (MoCA<18). Aging Biomarkers. Leptin was significantly higher in MCI compared to non-MCI (13.32 vs 5.03 ng/ml, p=0.014) and was negatively correlated with MoCA (r=-0.58, p=0.005). However, other aging biomarkers were not significantly different between two groups. For each ng/mL increase in leptin, the odds of MCI increased by 32% (OR:1.317 [95%CI: 0.99-1.74], p=0.05), adjusted for age and BMI. (Figure1) Measures of Oxidative Stress. SOD activity was significantly lower in MCI compared to non-MCI (21.4% vs 37.9%, p=0.009). For each percent increase in SOD activity, the odds of developing MCI significantly decreased by 11% (adjusted-OR=0.89 [95% CI:0.81-0.97], p=0.01). TAC levels were not associated MCI. CONCLUSIONS MCI, characterized by worse performance in executive functions and memory, was seen in WTC-exposed firefighters. Lower SOD activity correlated with increased odds of MCI, suggesting a protective role for antioxidants, as shown in previous translational studies. Additionally, higher leptin was associated with MCI and negatively correlated with cognitive performance. Our findings highlight the need for ongoing monitoring of oxidative and metabolic factors to improve cognitive health. Further research with a larger sample is needed to develop targeted interventions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.022
GPT teacher head0.309
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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