MANGANESE-INDUCED PARKINSONISM IN CHILDHOOD
Bibliographic record
Abstract
Objectives: To review the clinical presentation, routes of exposure and mechanism of manganese-induced neurotoxicity. Methods: A previously healthy 5 year old girl presented with pica, emotional lability and marked gait abnormalities. She had severe iron deficiency anemia and polycythemia. Blood levels of manganese were extremely elevated and MRI showed increased signal in the basal ganglia on T1-weighted images consistent with manganese neurotoxicity. Chelation therapy resulted in improvement in her mobility but she continued to have significant gait impairment. Results: Manganese neurotoxicity is rarely reported in the pediatric literature. There are a few reports with liver disease and TPN-induced toxicity. Occupational exposure is the most common source of manganism in adults. Environmental exposure is the probable source in this pediatric case as other known etiologies have been excluded. The prognosis of manganese neurotoxicity in childhood is uncertain. Conclusion: Manganese neurotoxicity may result in devastating neurologic sequelae in both childhood and adult forms. Exposure to airborne manganese from industrial emissions and fuel-additives remains an important public health concern as the long term effects are unknown.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".