Kinetic parameters of alpha-synuclein seed amplification assay correlate with cognitive impairment in patients with Lewy body disorders
Bibliographic record
Abstract
The alpha-synuclein (aSyn) seed amplification assay (SAA) can identify aSyn aggregates as indicator for Lewy body pathology in biomaterials of living patients and help in diagnosing Parkinson´s disease and dementia syndromes. Our objective was to confirm that qualitative results of aSyn SAA are reproducible across laboratories and to determine whether quantitative findings correlate with patient clinical characteristics. Therefore cerebrospinal fluid samples were re-analysed by aSyn SAA in a second laboratory with four technical replicates for each sample. Kinetic parameters derived from each aggregation curve were summarized and correlated with patient characteristics. We found that qualitative findings were identical between the two laboratories for 54 of 55 patient samples. The number of positive replicates for each sample also showed good agreement between laboratories. Moreover, specific kinetic parameters of the SAA showed a strong correlation with clinical parameters, notably with cognitive performance evaluated by the Montreal Cognitive Assessment. We concluded that SAA findings are highly reproducible across laboratories following the same protocol. SAA reports not only the presence of Lewy pathology but is also associated with clinical characteristics. Thus, aSyn SAA can potentially be used for patient stratification and determining the target engagement of aSyn targeting treatments.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".