Activity-dependent modulation of neuronal KV channels by retinoic acid enhances CaV channel activity
Bibliographic record
Abstract
The metabolite of vitamin A, retinoic acid (RA), is known to affect synaptic plasticity in the nervous system and to play an important role in learning and memory. A ubiquitous mechanism by which neuronal plasticity develops in the nervous system is through modulation of voltage-gated Ca 2+ (Ca V ) and voltage-gated K + channels. However, how retinoids might regulate the activity of these channels has not been determined. Here, we show that RA modulates neuronal firing by inducing spike broadening and complex spiking in a dose-dependent manner in peptidergic and dopaminergic cell types. Using patch-clamp electrophysiology, we show that RA-induced complex spiking is activity dependent and involves enhanced inactivation of delayed rectifier voltage-gated K + channels. The prolonged depolarizations observed during RA-modulated spiking lead to an increase in Ca 2+ influx through Ca V channels, though we also show an opposing effect of RA on the same neurons to inhibit Ca 2+ influx. At physiological levels of Ca 2+ , this inhibition is specific to Ca V 2 (not Ca V 1) channels. Examining the interaction between the spike-modulating effects of RA and its inhibition of Ca V channels, we found that inhibition of Ca V 2 channels limits the Ca 2+ influx resulting from spike modulation. Our data thus provide novel evidence to suggest that retinoid signaling affects both delayed rectifier K + channels and Ca V channels to fine-tune Ca 2+ influx through Ca V 2 channels. As these channels play important roles in synaptic function, we propose that these modulatory effects of retinoids likely contribute to synaptic plasticity in the nervous system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 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".