In vivo optogenetic activation of Na<sub>v</sub>1.8<sup>+</sup> cutaneous nociceptors and their responses to natural stimuli
Bibliographic record
Abstract
Optogenetic methods that utilize expression of the light-sensitive protein channelrhodopsin-2 (ChR2) in neurons have enabled selective activation of specific subtypes or groups of neurons to determine their functions. Using a transgenic mouse model in which neurons natively expressing Nav1.8 (a tetrodotoxin-resistant voltage-gated sodium channel) also express the light-gated channel ChR2, we have been able to determine the functional properties of Nav1.8-expressing cutaneous nociceptors of the glabrous skin in vivo. Most (44 of 53) of the C-fiber nociceptors isolated from Nav1.8-ChR2+ mice were found to be responsive to blue (470 nm) light. Response characteristics, including conduction velocity and responses to mechanical stimuli, were comparable between nociceptors isolated from Nav1.8-ChR2+ and control mice. Interestingly, while none of the non–light-responsive C-fibers were sensitive to heat or cold, nearly all (77%) light-sensitive fibers were excited by mechanical and thermal stimuli, suggesting that Nav1.8 is predominantly expressed by C-fiber nociceptors that are responsive to multiple stimulus modalities. The ability to activate peripheral nociceptors with light provides a method of stimulation that is noninvasive, does not require mechanical interruption of the skin, and accesses receptive fields that might be difficult or impossible to stimulate with standard stimuli while allowing repeated stimulation without injuring the skin. NEW & NOTEWORTHY Transgenic mice that express the blue light-sensitive protein channelrhodopsin2 (ChR2) in nociceptive nerve fibers that contain voltage-gated sodium channel Nav1.8 were used to determine functional properties of these afferent fibers. Electrophysiological recordings in vivo revealed that most nociceptive fibers that possess Nav1.8 are C-fiber nociceptors that respond to multiple stimulus modalities. Furthermore, responses evoked by blue light stimulation were comparable to those elicited by noxious mechanical, heat, and cold stimuli.
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 | 0.000 |
| 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) | 0.002 | 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".