Genetic deletion of microglial Panx1 attenuates morphine withdrawal, but not analgesic tolerance or hyperalgesia in mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Opioids are among the most powerful analgesics for managing pain, yet their repeated use can lead to the development of severe adverse effects. In a recent study, we identified the microglial pannexin-1 channel (Panx1) as a critical substrate for opioid withdrawal. Here, we investigated whether microglial Panx1 contributes to opioid-induced hyperalgesia (OIH) and opioid analgesic tolerance using mice with a tamoxifen-inducible deletion of microglial Panx1. We determined that escalating doses of morphine resulted in thermal pain hypersensitivity in both Panx1-expressing and microglial Panx1-deficient mice. In microglial Panx1-deficient mice, we also found that acute morphine antinociception remained intact, and repeated morphine treatment at a constant dose resulted in a progressive decline in morphine antinociception and a reduction in morphine potency. This reduction in morphine antinociceptive potency was indistinguishable from that observed in Panx1-expressing mice. Notably, morphine tolerant animals displayed increased spinal microglial reactivity, but no change of microglial Panx1 expression. Collectively, our findings indicate microglial Panx1 differentially contributes to opioid withdrawal, but not the development of opioid-induced hyperalgesia or tolerance.
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.
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 it