Progranulin expression in the developing and adult murine brain
Bibliographic record
Abstract
Frontotemporal lobar degeneration (FTLD) is a neurodegenerative condition characterized by focal degeneration of the frontal and temporal lobes of the brain. Autosomal dominantly inherited mutations of the progranulin gene (GRN) have been identified as the cause of a subset of cases of familial FTLD. In order to better understand the function of progranulin in the central nervous system (CNS), we have assessed the spatiotemporal expression pattern of both the murine progranulin gene (Grn) and the protein (Grn) by using transgenic knock-in mice expressing a reporter gene from the Grn locus and by immunohistochemistry, respectively. We compared Grn expression with a panel of established markers for distinct neuronal developmental stages and specific cell lineages at time points ranging from embryonic day 13.5 through to the mature adult. We find that Grn is expressed in both neurons and microglia within the CNS, but that it shows a different developmental expression pattern in each cell type. Grn expression in neurons increases as the cells mature, whereas expression in microglia varies with the cells' state of activation, being specifically upregulated in microglia in response to excitotoxic injury. Our results suggest that progranulin plays distinct roles in neurons and microglia, both of which likely contribute to overall neuronal health and function.
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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".