Ultrasensitive measurement of huntingtin protein in cerebrospinal fluid demonstrates increase with Huntington disease stage and decrease following brain huntingtin suppression
Bibliographic record
Abstract
Quantitation of huntingtin protein in the brain is needed, both as a marker of Huntington disease (HD) progression and for use in clinical gene silencing trials. Measurement of huntingtin in cerebrospinal fluid could be a biomarker of brain huntingtin, but traditional protein quantitation methods have failed to detect huntingtin in cerebrospinal fluid. Using micro-bead based immunoprecipitation and flow cytometry (IP-FCM), we have developed a highly sensitive mutant huntingtin detection assay. The sensitivity of huntingtin IP-FCM enables accurate detection of mutant huntingtin protein in the cerebrospinal fluid of HD patients and model mice, demonstrating that mutant huntingtin levels in cerebrospinal fluid reflect brain levels, increasing with disease stage and decreasing following brain huntingtin suppression. This technique has potential applications as a research tool and as a clinical biomarker.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".