Differential Uptake of NAGLU-IGF2 and Unmodified NAGLU in Cellular Models of Sanfilippo Syndrome Type B
Bibliographic record
Abstract
acetylglucosaminidase (NAGLU). Deficiency in NAGLU disrupts the lysosomal turnover of heparan sulfate (HS), which results in the abnormal accumulation of partially degraded HS in cells and tissues. BMN 250 (NAGLU-insulin-like growth factor 2 [IGF2]) is a recombinant fusion protein developed as an investigational enzyme replacement therapy for MPS IIIB. The IGF2 peptide on BMN 250 promotes enhanced targeting of the enzyme to lysosomes through its interaction with the mannose 6-phosphate receptor. The focus of these studies was to further characterize the ability of NAGLU-IGF2 to clear accumulated HS compared to unmodified NAGLU in primary cellular models of MPS IIIB. Here, we establish distinct primary cell models of MPS IIIB with HS accumulation. These cellular models revealed distinct NAGLU uptake characteristics that depend on the duration of exposure. We found that with sustained exposure, NAGLU uptake and HS clearance occurred independent of known lysosomal targeting signals. In contrast, under conditions of limited exposure duration, NAGLU-IGF2 was taken up more rapidly than the unmodified NAGLU into MPS IIIB primary fibroblasts, astrocytes, and cortical neurons, where it efficiently degraded accumulated HS. These studies illustrate the importance of using physiologically relevant conditions in the evaluation of enzyme replacement therapies in cellular models.
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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 | 0.001 |
| 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".