Progranulin Deficiency Decreases Gross Neural Connectivity But Enhances Transmission at Individual Synapses
Bibliographic record
Abstract
Frontotemporal dementia (FTD) has been linked to mutations in the progranulin gene (GRN) that lead to progranulin (PGRN) haploinsufficiency. Thus far, our understanding of the effects of PGRN depletion in the brain has been derived from investigation of gross pathology, and more detailed analyses of cellular function have been lacking. We report that knocking down PGRN levels in rat primary hippocampal cultures reduces neural connectivity by decreasing neuronal arborization and length as well as synapse density. Despite this, the number of synaptic vesicles per synapse and the frequency of mEPSCs are increased in PGRN knockdown cells, suggesting an increase in the probability of release at remaining synapses. Interestingly, we demonstrate that the number of vesicles per synapse is also increased in postmortem brain sections from FTD patients with PGRN haploinsufficiency, relative to controls. Our observations show that PGRN knockdown severely alters neuronal connectivity in vitro and that the synaptic vesicle phenotype observed in culture is consistent with that observed in the hippocampus of FTD patients.
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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) | 0.001 | 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".