Presidential Symposium and Presentation of Top Abstracts
Bibliographic record
Abstract
Mucopolysaccharidosis IIIC (MPSIIIC) is one of four Sanfilippo diseases sharing clinical signs and symptoms of severe cognitive and later motor decline and shortened life span. Unlike most other lysosomal diseases the missing enzyme, heparan sulfate acetyl CoA: α-glucosaminide N-acetyltransferase (HGSNAT), is bound to the lysosomal membrane and thus cannot cross the blood-brain barrier or diffuse between cells. We have previously demonstrated behavioural, biochemical and pathological correction of this disease in the mouse model of MPSIIIC using an Adeno-Associated Vector (AAV) delivering recombinant human HGSNAT from two intraparenchymal injections into the brain using an AAV-2 derived AAV truetype (AAV-TT) serotype with improved distribution over AAV9. Current AdenoAssociated Vector (AAV) gene therapy delivery routes are sub-optimal for effective neuronal delivery in the entire human brain, which is essential in diseases characterised by global neurological pathology such as Mucopolysaccharidosis (MPS) IIIC. We describe AAV delivery using Brainlab targeted catheters or Hamilton syringes for convection enhanced delivery (CED) in sheep, designed to reduce proximal vector expression and improve spread in intraparenchymal injections. Using AAV-GFP, we found that Brainlab cranial navigation is optimal for gene therapy, although Hamilton syringes gave improved distribution over catheters, despite higher doses and titres of vector used in catheter delivery. Intraparenchymal CED gives better distribution compared to intracerebroventricular delivery for the same vector dose. We demonstrate that we can effectively deliver functional HGSNAT enzyme in 24-37% of a 140g gyrencephalic sheep brain using AAV9-HGSNAT in only 3 injections in one hemisphere. AAV serotype may also be important, as AAVTT-GFP displayed moderately better transduction compared to AAV9-GFP but both serotypes almost exclusively transduced neurons via this route. In addition, the presence of pre-existing IgG antibodies in serum does not seem to affect AAV transduction in the brain. Despite variabilities in vector purification, volume and titre, we found the primary attribute for efficient brain delivery is catheter design. These data help to inform a future potential clinical trial for MPSIIIC.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.085 | 0.045 |
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".