Cell-Biological Requirements for the Generation of Dentate Gyrus Granule Neurons
Bibliographic record
Abstract
The dentate gyrus (DG) receives highly processed information from the associative cortices functionally integrated in the trisynaptic hippocampal circuit, which contributes to the formation of new episodic memories and the spontaneous exploration of novel environments. Remarkably, the DG is the only brain region currently known to have high rates of neurogenesis in adults (Andersen et al., 1966; Andersen et al., 1971). The DG is involved in several neurodegenerative disorders, including clinical dementia, schizophrenia, depression, bipolar disorder and temporal lobe epilepsy. The principal neurons of the DG are the granule cells. DG granule cells generated in culture would be an ideal model to investigate their normal development and the causes of the pathologies in which they are involved and as well as possible therapies. Essential to establish such in vitro models is the precise definition of the most important cell-biological requirements for the differentiation of DG granule cells. This requires a deeper understanding of the precise molecular and functional attributes of the DG granule cells in vivo as well as the DG cells derived in vitro. In this review we outline the neuroanatomical, molecular and cell-biological components of the granule cell differentiation pathway, including some growth- and transcription factors essential for their development. We summarize the functional characteristics of DG granule neurons, including the electrophysiological features of immature and mature granule cells and the axonal pathfinding characteristics of DG neurons. Additionally, we discuss landmark studies on the generation of dorsal telencephalic precursors from pluripotent stem cells (PSCs) as well as DG neuron differentiation in culture. Finally, we provide an outlook and comment critical aspects.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".