Impact of Manganese on Neuronal Function: An Exploratory Multi-Omics Study on Ferroalloy Workers in Brescia, Italy
Bibliographic record
Abstract
Abstract Interest is growing in the potential role of manganese (Mn) in Alzheimer’s Disease (ADRD). This nested pilot study of a ferroalloy workers cohort was aimed to investigate the effects of long-term occupational Mn exposure on cognitive function through β-amyloid (Aβ) modification and brain deposition, as well as metabolomic, lipidomic and proteomic profiling. We examined 6 male exposed workers (median age 63, exposure duration 31 yrs), and 5 historical controls (median age 60) who had undergone brain PET scan imaging showing higher Aβ deposition among the exposed compared to the controls (p < 0.05). The average annual cumulative respirable Mn of the ferroalloy workers was 329.23 ± 516.39 µg/m 3 (geometric mean 118.59). Average Mn level in plasma of the exposed subjects (0.704 ± 0.2 ng/mL) was significantly higher than the controls (0.397 ± 0.18). Pathway analyses using LC-MS/MS results revealed impacted metabolomic pathways such as olfactory signaling, mitochondrial fatty acid beta-oxidation, biogenic amine synthesis, SLC-mediated transmembrane transport, and glycerophospholipid and choline metabolism in the Mn exposed group. Single molecule arrays (Simoa) analysis revealed notable modifications of AD-related plasma biomarkers; protein microarray (chip) showed significant changes (p < 0.05) in the levels of some plasma antibodies targeting autoimmune and neuronal associated proteins such as Aβ (25-35), GFAP, Serotonin, Human NOVA1, and Human Siglec-1/CD169 among the Mn exposed individuals. This data provides evidence on Mn-induced alterations of pathways and biomarkers associated with cognitive neurodegenerative diseases.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".