Progranulin: a new avenue towards the understanding and treatment of neurodegenerative disease
Bibliographic record
Abstract
Progranulin, a secreted glycoprotein, is encoded in humans by the single GRN gene. Progranulin consists of seven and a half, tandemly repeated, non-identical copies of the 12 cysteine granulin motif. Many cellular processes and diseases are associated with this unique pleiotropic factor that include, but are not limited to, embryogenesis, tumorigenesis, inflammation, wound repair, neurodegeneration and lysosome function. Haploinsufficiency caused by autosomal dominant mutations within the GRN gene leads to frontotemporal lobar degeneration, a progressive neuronal atrophy that presents in patients as frontotemporal dementia. Frontotemporal dementia is an early onset form of dementia, distinct from Alzheimer's disease. The GRN-related form of frontotemporal lobar dementia is a proteinopathy characterized by the appearance of neuronal inclusions containing ubiquitinated and fragmented TDP-43 (encoded by TARDBP). The neurotrophic and neuro-immunomodulatory properties of progranulin have recently been reported but are still not well understood. Gene delivery of GRN in experimental models of Alzheimer's- and Parkinson's-like diseases inhibits phenotype progression. Here we review what is currently known concerning the molecular function and mechanism of action of progranulin in normal physiological and pathophysiological conditions in both in vitro and in vivo models. The potential therapeutic applications of progranulin in treating neurodegenerative diseases are highlighted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".