Bibliographic record
Abstract
Abstract GM2 gangliosidosis is a family of three diseases that include Tay–Sachs disease (described over a century ago), Sandhoff disease and the AB‐variant form, reflecting the need of three gene products to hydrolyse GM2 ganglioside. The recent elucidation of the crystal structures these three proteins have provided a better understanding of the molecular basis of GM2 gangliosidosis. The discovery that most deleterious missense mutations affect the folding or the assembly of the heterodimeric enzyme, and that delays in these processes invoke premature degradation by the endoplasmic reticulum‐quality control system, have suggested a novel therapeutic approach, enzyme enhancement therapy, for some forms of this and other genetic diseases. Progress is also being made on developing a more generally applicable approach, based on gene therapy, for Tay–Sachs and Sandhoff disease. If successful, this will also serve as a model for developing similar therapies for other diseases with neurological involvement. Key Concepts: The history of research into Tay–Sachs disease demonstrates the power of the classical scientific approach to problem solving involving building, over many decades, on the contributions from scientists with diverse interests and expertise. The study or rare diseases often lead to unexpected discoveries of broader‐based metabolic pathways and disease mechanisms. The study of rare diseases can also lead to the development of novel therapeutic approaches that can be adapted to more common diseases.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.007 |
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".