Cav3.2 T-type calcium channels shape electrical firing in mouse Lamina II neurons
Bibliographic record
Abstract
Abstract The T-type calcium channel, Cav3.2, is necessary for acute pain perception, as well as mechanical and cold allodynia in mice. Being found throughout sensory pathways, from excitatory primary afferent neurons up to pain matrix structures, it is a promising target for analgesics. In our study, Cav3.2 was detected in ~60% of the lamina II (LII) neurons of the spinal cord, a site for integration of sensory processing. It was co-expressed with Tlx3 and Pax2, markers of excitatory and inhibitory interneurons, as well as nNOS, calretinin, calbindin, PKCγ and not parvalbumin. Non-selective T-type channel blockers slowed the inhibitory but not the excitatory transmission in LII neurons. Furthermore, T-type channel blockers modified the intrinsic properties of LII neurons, abolishing low-threshold activated currents, rebound depolarizations, and blunting excitability. The recording of Cav3.2-positive LII neurons, after intraspinal injection of AAV-DJ-Cav3.2-mcherry, showed that their intrinsic properties resembled those of the global population. However, Cav3.2 ablation in the dorsal horn of Cav3.2 GFP-Flox KI mice after intraspinal injection of AAV-DJ-Cav3.2-Cre-IRES-mcherry, had drastic effects. Indeed, it (1) blunted the likelihood of transient firing patterns; (2) blunted the likelihood and the amplitude of rebound depolarizations, (3) eliminated action potential pairing, and (4) remodeled the kinetics of the action potentials. In contrast, the properties of Cav3.2-positive neurons were only marginally modified in Cav3.1 knockout mice. Overall, in addition to their previously established roles in the superficial spinal cord and in primary afferent neurons, Cav3.2 channel appear to be necessary for specific, significant and multiple controls of LII neuron excitability.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".