Hematopoietic Stem Cell Transplantation in Late‐Onset Krabbe Disease: No Evidence of Worsening Demyelination and Axonal Loss 4 Years Post‐allograft
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Late-onset adult Krabbe disease is a very rare demyelinating leukodystrophy, affecting less than 1 in a million people. Hematopoietic stem cell transplantation (HSCT) strategies can stop the accumulation of toxic metabolites that damage myelin-producing cells. We used quantitative advanced imaging metrics to longitudinally assess the impact of HSCT on brain abnormalities in adult-onset Krabbe disease. METHODS: A 42-year-old female with late-onset Krabbe disease and an age/sex-matched healthy control underwent annual 3T MRI (baseline was immediately prior to HSCT for the Krabbe subject). Imaging included conventional scans, myelin water imaging, diffusion tensor imaging, and magnetic resonance spectroscopy. RESULTS: Brain abnormalities far beyond those visible on conventional imaging were detected, suggesting a global pathological process occurs in Krabbe disease with adult-onset etiology, with myelin being more affected than axons, and evidence of wide-spread gliosis. After HSCT, our patient showed clinical stability in all measures, as well as improvement in gait, dysarthria, and pseudobulbar affect at 7.5 years post-transplant. No MRI evidence of worsening demyelination and axonal loss was observed up to 4 years post-allograft. CONCLUSIONS: Clinical evidence and stability of advanced MR measures related to myelin and axons supports HSCT as an effective treatment strategy for stopping progression associated with late-onset Krabbe disease.
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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 | 0.000 | 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) | 0.000 | 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".