Promise and challenges of dystonia brain banking: establishing a human tissue repository for studies of X-Linked Dystonia-Parkinsonism
Bibliographic record
Abstract
X-Linked Dystonia-Parkinsonism (XDP) is a neurodegenerative disease affecting individuals with ancestry to the island of Panay in the Philippines. In recent years there has been considerable progress at elucidating the genetic basis of XDP and candidate disease mechanisms in patient-derived cellular models, but the neural substrates that give rise to XDP in vivo are still poorly understood. Previous studies of limited XDP postmortem brain samples have reported a selective dropout of medium spiny neurons within the striatum, although neuroimaging of XDP patients has detected additional abnormalities in multiple brain regions beyond the basal ganglia. Given the need to fully define the CNS structures that are affected in this disease, we created a brain bank in Panay to serve as a tissue resource for detailed studies of XDP-related neuropathology. Here we describe this platform, from donor recruitment and consent to tissue collection, processing, and storage, that was assembled within a predominantly rural region of the Philippines with limited access to medical and laboratory facilities. Thirty-six brains from XDP individuals have been collected over an initial 4 years period. Tissue quality was assessed based on histologic staining of cortex, RNA integrity scores, detection of neuronal transcripts in situ by fluorescent hybridization chain reaction, and western blotting of neuronal and glial proteins. The results indicate that this pipeline preserves tissue integrity to an extent compatible with a range of morphologic, molecular, and biochemical analyses. Thus the algorithms that we developed for working in rural communities may serve as a guide for establishing similar brain banks for other rare diseases in indigenous populations.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".