The role of neuregulin–ErbB4 interactions on the proliferation and organization of cells in the subventricular zone
Bibliographic record
Abstract
Coordinated regulation of neuronal progenitor differentiation in the subventricular zone (SVZ) is a fundamental feature of adult neurogenesis. However, the molecular control of this process remains mostly undeciphered. Here, we investigate the role of neuregulins (NRGs) in this process and show that a NRG receptor, ErbB4, is primarily expressed by polysialylated neural cell adhesion molecule immature neuroblasts but is also detected in a subset of GFAP+ astroglial cells, ependymal cells, and Dlx2+ precursors in the SVZ. Of the NRG ligands, both NRG1 and -2 are expressed by immature polysialylated neural cell adhesion molecule neuroblasts in the SVZ. NRG2 is also expressed by some of the GFAP+ putative stem cells lining the ventricles. Infusion of exogenous NRG1 leads to rapid aggregation of Dlx2+ cells in the SVZ and affects the initiation and maintenance of organized neuroblast migration from the SVZ toward the olfactory bulb. In contrast, the infusion of NRG2 increased the number of Sox2 and GFAP+ precursors in the SVZ. An outcome of this NRG2 effect is an increase in the number of newly generated migrating neuroblasts in the rostral migratory stream and GABAergic interneurons in the olfactory bulb. The analysis of conditional null mice that lack NRG receptor, ErbB4, in the nervous system revealed that the observed activities of NRG2 require ErbB4 activation. These results indicate that different NRG ligands affect distinct populations of differentiating neural precursors in the neurogenic regions of the mature forebrain. Furthermore, these studies identify NRG2 as a factor capable of promoting SVZ proliferation, leading to the formation of new neurons in vivo.
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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".