Mercury neurotoxicity and the development of peripheral biochemical markers of central nervous system function
Bibliographic record
Abstract
Methylmercury (MeHg) is a neurotoxic global pollutant that accumulates at high levels in predatory fish and marine mammals. The dietary intake of these animals is the main source of MeHg exposure in humans. At high levels, MeHg is known to damage the sensory and motor systems in both adults and children. Due to the complexity and inaccessibility of the central nervous system (CNS), early dysfunction is difficult to detect. Biochemical markers in the CNS have been used to identify MeHg neurotoxicity in animal models. Analogues of these biochemical targets are also present in peripheral blood tissue and may reflect early CNS dysfunction in human populations. The proposed peripheral biomarkers include (1) lymphocyte muscarinic acetylcholine (mACh) receptor, (2) serum cholinesterase (ChE) and (3) platelet monoamine oxidase (MAO). This thesis evaluates the effects of mercury (Hg) compounds on these CNS and peripheral biochemical markers in laboratory and epidemiological studies. In vitro studies showed that inorganic Hg (HgCl2) and MeHg inhibited mACh receptor binding in human, rat, and mouse brain tissue. Additionally, studies demonstrated that a low-level gestational exposure to MeHg reduced MAO activity in the developing embryo and in adult female offspring. Combined, these studies provide a framework for the assessment of biochemical targets of Hg compounds in humans. A cross sectional study was conducted to evaluate the association between peripheral biochemical markers and MeHg exposure in fish-eating adults (n=129) from Lac St-Pierre, Quebec. Blood-Hg concentrations were used as a marker of exposure and ranged from 0.2 to 17.0 mug/L. Multiple linear regression analysis demonstrated that both blood-Hg (p=0.011) and heavy smoking (p=0.001) were associated with reduced platelet-MAO activity. However, neither lymphocyte mACh receptor nor serum ChE was related to blood-Hg. These results suggest that exposure to MeHg may result in reduced plat
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".