Retinoic acid and nitric oxide promote cell proliferation and differentially induce neuronal differentiation <i>in vitro</i> in the cnidarian <i>Renilla koellikeri</i>
Bibliographic record
Abstract
Retinoic acid (RA) and nitric oxide (NO) are known to promote neuronal development in both vertebrates and invertebrates. Retinoic acid receptors appear to be present in cnidarians and NO plays various physiological roles in several cnidarians, but there is as yet no evidence that these agents have a role in neural development in this basal metazoan phylum. We used primary cultures of cells from the sea pansy Renilla koellikeri to investigate the involvement of these signaling molecules in cnidarian cell differentiation. We found that 9-cis RA induce cell proliferation in dose- and time-dependent manners in dishes coated with polylysine from the onset of culture. Cells in cultures exposed to RA in dishes devoid of polylysine were observed to differentiate into epithelium-associated cells, including sensory cells, without net gain in cell density. NO donors also induce cell proliferation in polylysine-coated dishes, but induce neuronal differentiation and neurite outgrowth in uncoated dishes. No other cell type undergoes differentiation in the presence of NO. These observations suggest that in the sea pansy (1) cell adhesion promotes proliferation without morphogenesis and this proliferation is modulated positively by 9-cis RA and NO, (2) 9-cis RA and NO differentially induce neuronal differentiation in nonadherent cells while repressing proliferation, and (3) the involvement of RA and NO in neuronal differentiation appeared early during the evolutionary emergence of nervous systems.
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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) | 0.001 | 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".