Progranulin is expressed within motor neurons, promotes neuronal cell survival, and is secreted at least in part via the constitutive secretory pathway
Bibliographic record
Abstract
Progranulin is a secreted high molecular weight growth factor. While inappropriate over-expression of the progranulin gene has been associated with many cancers, haploinsufficiency leads to atrophy of the frontotemporal lobes and development of a form of dementia (FTLD-U). We have demonstrated that progranulin is abundantly expressed in mouse motor neurons in vivo and primary cultures in vitro. The cellular location of progranulin was examined using confocal microscopy. Progranulin was localised to organelles using immunocytochemistry and by examining the intracellular fate of exogenously expressed flu orescently-labelled progranulin. Taken together these studies revealed progranulin to be located within compartments of the secretory pathway. Stable transfection of the human progranulin gene into the NSC-34 cell line stimulates the appearance of dendritic structures and provides protection against apoptosis. Control cells, while expressing basal levels of progranulin do not survive in serum free conditions. This work highlights the importance of progranulin as a neuroprotective growth factor and may represent a therapeutic target for neurodegenerative diseases including FTLD-U and ALS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".