Modulation of Transient and Persistent Inward Currents by Activation of Protein Kinase C in Spinal Ventral Neurons of the Neonatal Rat
Bibliographic record
Abstract
Neuronal excitability can be regulated through modulation of voltage threshold (Vth). Previous studies suggested that this modulation could be mediated by modulation of transient sodium currents (I(T)) and/or persistent inward current (PIC). Modulation of I(T) and PIC through activation of protein kinase C (PKC) has previously been described as a mechanism controlling neuronal excitability. We investigated modulation of I(T) and PIC by PKC in neonatal rat spinal ventral neurons. In whole cell voltage clamp, activation of PKC by application of 1-oleoyl-2-acetyl-sn-glycerol (OAG, 10-30 microM) resulted in 1) a reduction of I(T) amplitude by 33% accompanied an increase in half-width and a decrease in the maximal rise and decay rates of the I(T); 2) a reduction of PIC amplitude by 49%, with a depolarization of PIC onset by 4.5 mV. Activation of PKC caused varied effects on Vth for eliciting I(T), with an unchanged Vth or depolarized Vth being the most common effects. In current-clamp recordings, PKC activation produced a small but significant depolarization (2.0 mV) of Vth for action potential generation with an increase in half-width and a decrease in amplitude and the maximal rise and decay rates of action potentials. Inclusion of PKCI19-36 (10-30 microM), a PKC inhibitor, in the recording pipette could block the OAG effects on I(T) and PIC. The ability of serotonin to hyperpolarize Vth was not altered by PKC activation or inhibition. This study demonstrates that activation of PKC decreases the excitability of spinal ventral neurons and that Vth can be modulated by multiple mechanisms.
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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".