Detection of Endogenous Retinoids in the Molluscan CNS and Characterization of the Trophic and Tropic Actions of 9- <i>cis</i> Retinoic Acid on Isolated Neurons
Bibliographic record
Abstract
Retinoic acid (RA) is an active metabolite of Vitamin A that plays an important role in the growth and differentiation of many cell types. All-trans RA (atRA) is the retinoic acid isomer that has been most widely studied in the nervous system, and can induce and direct neurite outgrowth from both vertebrate and invertebrate preparations. The presence and role of the 9-cis-RA isomer in the nervous system is far less well defined. Here, we used high-pressure liquid chromatography (HPLC) and mass spectrometry (MS) to show for the first time, the presence of both atRA and 9-cis-RA in the CNS of an invertebrate. We then demonstrated that 9-cis-RA was capable of exerting the same neurotrophic and chemotropic effects on cultured neurons as atRA. In this study, significantly more cells showed neurite outgrowth in 9-cis-RA versus the EtOH vehicle control, and 9-cis-RA significantly increased the number and length of neurites from identified neurons after 4 d in culture. 9-cis-RA also extended the duration of time that cells remained electrically excitable in culture. Furthermore, we showed for the first time in any species, that exogenous application of 9-cis-RA induced positive growth cone turning of cultured neurons. This study provides the first evidence for the presence of both atRA and 9-cis-RA in an invertebrate CNS and also provides the first direct evidence for a potential physiological role for 9-cis-RA in neuronal regeneration and axon pathfinding.
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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".