Generation of mice with combined <i>Hexa</i> Gly269Ser KI or KO and <i>Neu3</i> KO alleles to create new models of GM2 gangliosidoses
Bibliographic record
Abstract
The GM2 gangliosidoses are lysosomal storage disorders exhibiting a spectrum of neurological phenotypes ranging from childhood death to debilitating adult-onset neurological impairment. To date, no mouse model harbouring a specific human mutation causing GM2 gangliosidosis has been created. We used CRISPR/Cas9 to generate knockin (KI) mice with the common adult-onset Hexa Gly269Ser variant as well as knockout (KO) mice with Hexa mutations expected to cause complete HexA deficiency. We also created Neu3 KO alleles that combined with Hexa KO or KI alleles were expected to create acute and chronic models of GM2 gangliosidosis, respectively. However, both models accumulated GM2 ganglioside throughout the brain when compared to controls (CON), and exhibited progressive loss of reflexes, gait abnormalities, and premature death by 24 weeks of age. Although survival and behavioural phenotypes did not differ between KO and KI models, the KI model had substantial Hexa mRNA and evidence of GM2 turnover. This KI model will be useful for developing gene editing to correct the variant causing the Gly269Ser substitution and its novel biochemical phenotype suggests it may be suitable for testing therapies that treat partial β-hexosaminidase A deficiency.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".