O5‐04‐02: ALZHEIMER RISK FACTOR PICALM IS INVOLVED IN TAU PATHOLOGY IN ALZHEIMER AND OTHER TAUOPATHIES
Bibliographic record
Abstract
Recently, genome-wide association studies identified single nucleotide polymorphisms in the gene of PICALM as genetic risk factors for late-onset Alzheimer disease (LOAD). PICALM is ubiquitously expressed and plays a key role for Clathrin-mediated endocytosis. The role of PICALM in AD pathogenesis, however, remained elusive. In this study, we analysed the level and expression of PICALM in AD brains and in other neurodegenerative diseases in order to understand how PICALM is involved in AD aetiology. Western blotting and immunohistochemistry on human post-mortem brain tissues. In vitro assay for calpain and caspase activation. Co-immunoprecipitation. By western blotting of control and AD samples, we found that level of PICALM full-length protein was significantly decreased in AD T1 isocortex and that PICALM was also cleaved into smaller fragments. By in vitro cleavage assay, we demonstrated that PICALM was cleaved by both caspase and calpain. Immunohistochemistry revealed that PICALM was associated with neurofibrillary tangles of LOAD, familial AD and Down syndrome cases. Hyperphosphorylated tau co-immunoprecipitated with PICALM. We further analysed the involvement of PICALM in other neurodegenerative diseases and found that PICALM was associated with tau positive inclusions of several tauopathies such as Pick's disease and Progressive supranuclear palsy (PSP). Taken together, our results indicate that PICALM processing is modified in AD and is associated to tau pathology in AD and in some other tauopaties.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".