Chronic pain mediated changes in the appetitive value of affective gentle touch in mice
Bibliographic record
Abstract
Abstract The existence of skin-to-brain circuits for rewarding gentle touch highlight its critical nature across species. However, this gentle affective touch is not always appetitive and can produce aversion or negative affect in disorders such as chronic pain. Sensory neurons expressing the protein MrgprB4 detect gentle stroking in mice and their activation of these neurons known to be positively reinforcing. Here we assess whether activation of channelrhodopsin (ChR2) expressing MrgprB4 afferents signal positively valenced tactile information and whether this is altered in models of chronic pain. We further interrogate how this this sensory information is reflected in the downstream circuits recruited. Optogenetic activation of MrgprB4 lineage afferents was found to be appetitive in control and capsaicin sensitized mice but not nerve injured mice, indicating that the appetitive value is diminished in neuropathic pain. Remarkably, this appetitive value was partially recovered in male nerve injured mice by treatment with the analgesic gabapentin. These behavioral changes were also accompanied by different patterns of neuronal activity throughout the brain, including altered activation of sites that receive direct projections from the spinal cord between sham and nerve injured mice. Together, these findings highlight the plastic nature of these affective tactile circuits under pathological conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".