DnaJC7 in Amyotrophic Lateral Sclerosis
Bibliographic record
Abstract
Protein misfolding is a common basis of many neurodegenerative diseases including amyotrophic lateral sclerosis (ALS). Misfolded proteins, such as TDP-43, FUS, Matrin3, and SOD1, mislocalize and form the hallmark cytoplasmic and nuclear inclusions in neurons of ALS patients. Cellular protein quality control prevents protein misfolding under normal conditions and, particularly, when cells experience protein folding stress due to the fact of increased levels of reactive oxygen species, genetic mutations, or aging. Molecular chaperones can prevent protein misfolding, refold misfolded proteins, or triage misfolded proteins for degradation by the ubiquitin–proteasome system or autophagy. DnaJC7 is an evolutionarily conserved molecular chaperone that contains both a J-domain for the interaction with Hsp70s and tetratricopeptide domains for interaction with Hsp90, thus joining these two major chaperones’ machines. Genetic analyses reveal that pathogenic variants in the gene encoding DnaJC7 cause familial and sporadic ALS. Yet, the underlying ALS-associated molecular pathophysiology and many basic features of DnaJC7 function remain largely unexplored. Here, we review aspects of DnaJC7 expression, interaction, and function to propose a loss-of-function mechanism by which pathogenic variants in DNAJC7 contribute to defects in DnaJC7-mediated chaperoning that might ultimately contribute to neurodegeneration in ALS.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".