Protein misfolding in the late‐onset neurodegenerative diseases: Common themes and the unique case of amyotrophic lateral sclerosis
Bibliographic record
Abstract
Enormous strides have been made in the last 100 years to extend human life expectancy and to combat the major infectious diseases. Today, the major challenges for medical science are age-related diseases, including cancer, heart disease, lung disease, renal disease, and late-onset neurodegenerative disease. Of these, only the neurodegenerative diseases represent a class of disease so poorly understood that no general strategies for prevention or treatment exist. These diseases, which include Alzheimer's disease, Parkinson's disease, Huntington's disease, the transmissible spongiform encephalopathies, and amyotrophic lateral sclerosis (ALS), are generally fatal and incurable. The first section of this review summarizes the diversity and common features of the late-onset neurodegenerative diseases, with a particular focus on protein misfolding and aggregation-a recurring theme in the molecular pathology. The second section focuses on the particular case of ALS, a late-onset neurodegenerative disease characterized by the death of central nervous system motor neurons, leading to paralysis and patient death. Of the 10% of ALS cases that show familial inheritance (familial ALS), the largest subset is caused by mutations in the SOD1 gene, encoding the Cu, Zn superoxide dismutase (SOD1). The unusual kinetic stability of SOD1 has provided a unique opportunity for detailed structural characterization of conformational states potentially involved in SOD1-associated ALS. This review discusses past studies exploring the stability, folding, and misfolding behavior of SOD1, as well as the therapeutic possibilities of using detailed knowledge of misfolding pathways to target the molecular mechanisms underlying ALS and other neurodegenerative 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".