Amelioration of Inflammation and Metabolic Blockage in GALC Deficient Mice After Enzyme Replacement Therapy via Extracellular Vesicles
Bibliographic record
Abstract
Diego Zelada,1,* Natalia Saldivia,1,* Shayla Samano,1 Diann George,1 Kenvi Chaudhari,1 Duc Nguyen,1 Daniel Simchuk,2 Richard B Van Breemen,2 Maria Irene Givogri1 1Department of Anatomy and Cell Biology, College of Medicine. University of Illinois Chicago, Chicago, IL, 60612, USA; 2Linus Pauling Institute, Oregon State University, Corvallis, OR, 97331, USA*These authors contributed equally to this workCorrespondence: Maria Irene Givogri, Department of Anatomy and Cell Biology, College of Medicine, University of Illinois at Chicago, 808 S, Wood St, M/C 512, Chicago, IL, 60612, USA, Email mgivogri@uic.eduIntroduction: Krabbe disease (KD) is a fatal lysosomal storage disorder caused by a deficiency in the enzyme galactosylceramidase (GALC), leading to toxic accumulation of psychosine. This results in widespread demyelination, inflammation, and neuronal damage. Early intervention is critical to mitigate disease progression and limit neurological injury.Methods: To assess the therapeutic potential of early enzyme replacement therapy (ERT), HeLa cells were genetically engineered to overexpress GALC, and extracellular vesicles (EVs) containing GALC were isolated. A single intrathecal injection of these GALC-loaded EVs was administered to neonatal GALC-deficient twitcher mice, a well-established model of KD.Results: Although the treatment did not prolong overall survival, it significantly reduced neuroinflammation. Treated mice exhibited decreased astrogliosis and microgliosis, along with a notable reduction in cortical psychosine levels. Molecular analysis of neuroinflammatory markers showed increased expression of IL-10 and TREM2 in microglial cells following treatment.Discussion: This study demonstrates that early intervention with GALC-loaded EVs can temporarily alleviate central neuropathology in KD by reducing inflammation and psychosine burden. While not curative, this approach shows potential as an adjunctive strategy to delay disease progression and improve the neuroinflammatory environment prior to hematopoietic stem cell transplantation. Keywords: Krabbe disease, intrathecal injection, galactosylceramidase delivery, psychosine, microglia
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".