<i>TMEM230</i>: How does it fit in the etiology and pathogenesis of Parkinson's disease?
Bibliographic record
Abstract
Mutations in the transmembrane protein 230 (TMEM230) gene were recently identified in a large Canadian pedigree and 7 smaller Chinese families, nominating TMEM230 as the third gene causing a Mendelian form of late onset Parkinson's disease (PD) with typical Lewy-body pathology (after synuclein alpha (SNCA) and leucine rich repeat kinase 2 (LRRK2)). The protein encoded by TMEM230 remains largely uncharacterized, but initial evidence points to roles in the trafficking of recycling vesicles, retromers, and endosomes, suggesting intriguing links to the pathways targeted by other PD-causing genes. The focus on family-based studies is gaining new momentum in the next-generation sequencing era, for the discovery of further, high-penetrance (medically relevant) genetic variants in PD. However, at this junction, important aspects of the TMEM230 story remain unclear, such as the prevalence of these mutations in the Chinese and other populations of the world, the penetrance of the mutations, and even their mode of inheritance. The first replication studies among Chinese and White PD patients have been largely negative. Furthermore, much more work remains ahead to elucidate the mechanisms by which these mutations might lead to neuronal cell death, alpha-synuclein pathology, and parkinsonism. © 2017 International Parkinson and Movement Disorder Society.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".