Analgesic effects of optogenetic inhibition of basolateral amygdala inputs into the prefrontal cortex in nerve injured female mice
Bibliographic record
Abstract
Peripheral nerve injury can lead to remodeling of brain circuits, and this can cause chronification of pain. We have recently reported that male mice subjected to spared injury of the sciatic nerve undergo changes in the function of the medial prefrontal cortex (mPFC) that culminate in reduced output of layer 5 pyramidal cells. More recently, we have shown that this is mediated by alterations in synaptic inputs from the basolateral amygdala (BLA) into GABAergic interneurons in the mPFC. Optogenetic inhibition of these inputs reversed mechanical allodynia and thermal hyperalgesia in male mice. It is known that the processing of pain signals can exhibit marked sex differences. We therefore tested whether the dysregulation of BLA to mPFC signaling is equally altered in female mice. Injection of AAV-Arch3.0 constructs into the BLA followed by implantation of a fiberoptic cannula into the mPFC in sham and SNI operated female mice was carried out, and pain behavioral responses were measured in response to yellow light mediated activation of this inhibitory opsin. Our data reveal that Arch3.0 activation leads to a marked increase in paw withdrawal thresholds and latencies in response to mechanical and thermal stimuli, respectively. However, we did not observe nerve injury-induced changes in mPFC layer 5 pyramidal cell output in female mice. Hence, the observed light-induced analgesic effects may be due to compensation for dysregulated neuronal circuits downstream of the mPFC.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".