Retinoic acid induces changes in electrical properties of adult neurons in a dose- and isomer-dependent manner
Bibliographic record
Abstract
The electrical activity of neurons is known to play a role in neuronal development, as well as repair of adult nervous tissue. For example, the extension of neurites and motility of growth cones can be modulated by changes in the electrical firing of neurons. The vitamin A metabolite retinoic acid also plays a critical role during nervous system development and is also known to elicit regenerative responses, namely the induction, enhancement, and directionality of neurite outgrowth. However, no studies have previously reported the ability of retinoic acid to modify the electrical activity of neurons. In this study, we determined whether retinoic acid might exert effects on the nervous system by altering the electrical properties of neurons. Using cultured adult neurons from Lymnaea stagnalis, we showed that acute application of retinoic acid can rapidly elicit changes in neuronal firing properties. Retinoic acid caused the presence of atypical firing behavior such as rhythmic bursting and altered the shape of action potentials, causing increases in half-amplitude duration and decay time. Retinoic acid also caused cell silencing, whereby neuronal activity was halted within an hour. These effects of retinoic acid were shown to be both dose and isomer dependent. We then showed that the effects of retinoic acid on cell firing (but not silencing) were significantly reduced in the presence of an retinoid X receptor pan-antagonist HX531. This study suggests that some of the effects of retinoic acid during neuronal development or regeneration might possibly occur as a result of changes in electrical activity of neurons.
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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".