Passive immunization against phosphorylated tau improves features of Huntington's disease pathology
Bibliographic record
Abstract
Huntington's disease is classically described as a neurodegenerative disorder of monogenic aetiology. The disease is characterized by an abnormal polyglutamine expansion in the huntingtin gene, which drives the toxicity of the mutated form of the protein. However, accumulation of the microtubule-associated protein tau, which is involved in a number of neurological disorders, has also been observed in patients with Huntington's disease. In order to unravel the contribution of tau hyperphosphorylation to hallmark features of Huntington's disease, we administered weekly intraperitoneal injections of the anti-tau pS202 CP13 monoclonal antibody to zQ175 mice and characterized the resulting behavioral and biochemical changes. After 12 weeks of treatment, motor impairments, cognitive performance and general health were improved in zQ175 mice along with a significant reduction in hippocampal pS202 tau levels. Despite the lack of effect of CP13 on neuronal markers associated with Huntington's disease pathology, tau-targeting enzymes and gliosis, CP13 was shown to directly impact mutant huntingtin aggregation such that brain levels of amyloid fibrils and huntingtin oligomers were decreased, while larger huntingtin protein aggregates were increased. Investigation of CP13 treatment of Huntington's disease patient-derived induced pluripotent stem cells (iPSCs) revealed a reduction in pS202 levels in differentiated cortical neurons and a rescue of neurite length. Collectively, these findings suggest that attenuating tau pathology could mitigate behavioral and molecular hallmarks associated with Huntington's disease.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".