High blood lead level correlates with selective hippocampal subfield atrophy and neuropsychological impairments
Bibliographic record
Abstract
BACKGROUND: Lead contamination is a major public health concern. Previous studies have demonstrated that lead exposure could affect the hippocampus, which is a complex and heterogeneous structure composed of 12 subregions. Here, we explored volumetric and functional changes in hippocampal subfields and neuropsychological alterations after lead exposure. METHODS: We performed a cross-sectional study at a smelting company between September 2020 and December 2021. Blood lead level was recorded, and neuropsychological functions were assessed by Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). The hippocampus was segmented into 12 subfields in each hemisphere in magnetic resonance images (MRIs). Then, the effect of altered hippocampal subfield volumes on brain functions were studied by seed-based functional connectivity (FC) analysis. Finally, the relationships between the lead level with hippocampal subfield volumes and neuropsychological functions were investigated. Baseline characteristics, hippocampal subfield volumes, and FC analysis were compared between lead-exposed (≥ 300 μg/L) and the control group (≤ 100 μg/L). RESULTS: In 76 participants, lead level positively correlated with SDS(r = 0.422) and negatively correlated with MoCA(r = -0.414), MMSE(r = -0.251), Concentration(r = -0.331), Recall(r = -0.319), Orientation(r = -0.298) and Executive Function/Visuospatial abilities(r = -0.231). Lead group (26 participants) had lower MoCA and MMSE and higher SDS than control group (23 participants). A significantly decreased volume in the left CA4 and GC-ML-DG subfields was found in the lead group compared with the control group. The left GC-ML-DG of the lead group showed a decreased FC with the bilateral postcentral gyrus. The left CA4(r = -0.409) and left GC-ML-DG (r = -0.383) volumes negatively correlated with lead level. The FC between left GC-ML-DG and left postcentral gyrus positively correlated with MoCA(r = 0.318), MMSE(r = 0.379) and Recall(r = 0.311). The FC between left GC-ML-DG and right postcentral gyrus positively correlated with MoCA(r = 0.326), Executive Function/Visuospatial abilities(r = 0.307) and Concentration(r = 0.297). CONCLUSION: High blood lead level was associated with neuropsychological alterations, hippocampal structural and functional changes. The left GC-ML-DG and CA4 atrophy might serve as predictive imaging markers for neurological damage associated with high lead exposure.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".