The Ciliary Neurotrophic Factor/Leukemia Inhibitory Factor/gp130 Receptor Complex Operates in the Maintenance of Mammalian Forebrain Neural Stem Cells
Bibliographic record
Abstract
The cytokines that signal through the common receptor subunit gp130, including ciliary neurotrophic factor (CNTF), interleukin-6, leukemia inhibitory factor (LIF) and oncostatin M, have pleiotropic functions in CNS development. Given the restricted expression domain of the CNTF receptor alpha (CNTFR) in the developing forebrain germinal zone and adult forebrain periventricular area, we have examined the putative role of CNTFR/LIFR/gp130-mediated signaling in regulating forebrain neural stem cell fate in vivo and in vitro. Analysis of LIFR-deficient mice revealed that a decreased level of LIFR expression results in a reduction in the number of adult neural stem cells. In adult LIFR heterozygote (+/-) mice, the number of neural stem cells and their progeny in the forebrain subependyma and TH-immunoreactive neurons in the olfactory bulb were significantly reduced. Intraventricular infusion of CNTF into the adult mouse forebrain, in the absence or presence of epidermal growth factor (EGF), enhanced self-renewal of neural stem cells in vivo. Analyses of EGF-responsive neural stem cells proliferating in vitro found that CNTF inhibits lineage restriction of neural stem cells to glial progenitors, which in turn results in enhanced expansion of stem cell number. These results suggest that CNTFR/LIFR/gp130-mediated signaling supports the maintenance of forebrain neural stem cells, likely by suppressing restriction to a glial progenitor cell fate.
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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) | 0.000 | 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".