Growth Hormone Promotes Axon Growth in the Developing Nervous System
Bibliographic record
Abstract
Postnatally, endocrine GH is primarily produced by pituitary somatotrophs. GH is, however, also produced in extrapituitary sites, including tissues of the developing nervous system such as the neural retina. Whereas GH roles in the nervous system are starting to emerge, they are still largely unknown. We show here that GH in the neural retina is mainly present in the axons of retinal ganglion cells (RGCs) in embryonic day (E) 4-12 chick embryos, but it is no longer present at E14-18. This temporal window corresponds to the period of RGC axon growth. GH receptor mRNA was also detected within cells of the E7 RGC layer and GH receptor protein colocalized with GH in RGC axons. The possibility that GH promotes axon growth was thus investigated. Exogenous GH induced a significant increase in axon elongation at 10(-9) and 10(-6) M in E7 RGC culture purified by immunopanning. RNA interference-mediated gene silencing was used to examine whether endogenous GH similarly alters axon outgrowth. The ability of GH small-interfering RNA to knock down GH was first tested using HEK cells on a LacZ-cGH expression plasmid and found to reach 90%. Upon transfection of GH small-interfering RNA to immunopanned RGC culture, a 63% knockdown of endogenous GH was detected and RGC axon length was found to be reduced by 40%. Taken together, these data suggest that GH acts as an autocrine or paracrine signaling molecule to promote axon growth in a developing nervous tissue, the neural retina of chick embryos.
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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".