Mice Doubly-Deficient in Lysosomal Hexosaminidase A and Neuraminidase 4 Show Epileptic Crises and Rapid Neuronal Loss
Bibliographic record
Abstract
Tay-Sachs disease is a severe lysosomal disorder caused by mutations in the HexA gene coding for the α-subunit of lysosomal β-hexosaminidase A, which converts G(M2) to G(M3) ganglioside. Hexa(-/-) mice, depleted of β-hexosaminidase A, remain asymptomatic to 1 year of age, because they catabolise G(M2) ganglioside via a lysosomal sialidase into glycolipid G(A2), which is further processed by β-hexosaminidase B to lactosyl-ceramide, thereby bypassing the β-hexosaminidase A defect. Since this bypass is not effective in humans, infantile Tay-Sachs disease is fatal in the first years of life. Previously, we identified a novel ganglioside metabolizing sialidase, Neu4, abundantly expressed in mouse brain neurons. Now we demonstrate that mice with targeted disruption of both Neu4 and Hexa genes (Neu4(-/-);Hexa(-/-)) show epileptic seizures with 40% penetrance correlating with polyspike discharges on the cortical electrodes of the electroencephalogram. Single knockout Hexa(-/-) or Neu4(-/-) siblings do not show such symptoms. Further, double-knockout but not single-knockout mice have multiple degenerating neurons in the cortex and hippocampus and multiple layers of cortical neurons accumulating G(M2) ganglioside. Together, our data suggest that the Neu4 block exacerbates the disease in Hexa(-/-) mice, indicating that Neu4 is a modifier gene in the mouse model of Tay-Sachs disease, reducing the disease severity through the metabolic bypass. However, while disease severity in the double mutant is increased, it is not profound suggesting that Neu4 is not the only sialidase contributing to the metabolic bypass in Hexa(-/-) mice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".