Subgroup differences in ‘brain-type’ transferrin and α-synuclein in Parkinson’s disease and multiple system atrophy
Bibliographic record
Abstract
Two transferrin (Tf) glycan-isoforms were previously found in cerebrospinal fluid (CSF); one appears to be derived from serum (Tf-2) and the other from choroid plexus, a CSF-producing tissue (Tf-1). To analyse metabolic differences associated with the two isoforms, their ratio (Tf-2/Tf-1) was defined as the Tf index. Here we report that Tf indices of patients with tauopathies including Alzheimer's disease (2.29 + 0.64) were similar to those of neurological controls (2.07 + 0.87) (P = 0.147). In contrast, Tf indices with Parkinson's disease (PD, 3.38 ± 1.87) and multiple system atrophy (MSA, 3.15 ± 1.72) were higher than those of the controls (2.07 ± 0.87), the P-values being < 0.001 and 0.024, respectively. Tf indices of PD and MSA did not appear to be normally distributed. Indeed, detrended normal Quantile-Quantile plot analysis revealed the presence of an independent subgroup showing higher Tf indices in PD and MSA. The subgroup of PD showed higher levels of CSF α-synuclein (38.3 ± 17.8 ng/ml) than the rest (25.3 ± 11.3 ng/ml, P = 0.012). These results suggest that PD (and MSA) includes two subgroups, which show different metabolism of CSF transferrin and α-synuclein.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".