New Insights into the Neuropathogenesis of Molybdenum Cofactor Deficiency
Bibliographic record
Abstract
BACKGROUND: Molybdenum cofactor deficiency (MOCOD) is a rare, progressive neurodegenerative disorder caused by sulphite oxidase enzyme deficiency. The neuropathological findings are consistent with a toxic insult to the brain that causes severe neuronal loss, reactive astrogliosis and spongiosis. The mechanisms responsible for these changes are unknown. METHODS: The case is a male infant with MOCOD who died at nine months of age from pneumonia. At autopsy, a complete neuropathological examination was performed including conventional immunohistochemical staining. In addition, brain sections were stained cytochemically with shikata and orcein which stain for disulphide bonds. The elemental composition of cortical cells was then analyzed in the scanning electron microscope using backscatter electron imaging and energy dispersive X-ray spectrometry. RESULTS: Neurons demonstrated cytoplasmic staining with shikata and orcein cytochemically when compared to control sections. Energy dispersive X-ray spectrometry analysis of these neurons confirmed the presence of excess sulphur and unexpectedly revealed excess magnesium accumulation. None of these findings was found in an age-matched control. CONCLUSIONS: In MOCOD we found abnormal accumulation of sulphur and magnesium in neurons. It is postulated that sulphur-containing compound(s) that are formed as a result of MOCOD cause excitotoxic neuronal injury in the presence of excess magnesium.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".