Electron Microscopy Can Still Have a Role in the Diagnosis of Selected Inborn Errors of Metabolism
Bibliographic record
Abstract
Many anatomic pathology laboratories no longer have electron microscopy facilities. A retrospective review of autopsies was performed to identify cases of inborn errors of metabolism (IEM) and determine the contribution of electron microscopy in making the diagnosis in those cases. Over a period of 17 years, there were 900 perinatal and pediatric autopsies. There were 7 cases (1%) of IEM, including 4 cases of Pompe disease, 1 case of I-cell disease, 1 case of bile acid synthesis defect, and 1 case of mitochondrial disease (Leigh syndrome). Electron microscopy was important in the diagnosis of I-cell disease and Pompe disease in our series. This technique enabled a prenatal diagnosis to be made from a chorionic villus biopsy in 2 cases with a positive family history. In less developed countries where upfront genetic testing may be too expensive and may need international referral, electron microscopy can still be useful for diagnosis of IEM, providing an affordable alternative with a more rapid turnaround time compared to gene mutation analysis or enzyme assay. Results can be used both for patient management and as a screen for which cases might benefit from genetic testing.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".