Targeting spinal mechanistic target of rapamycin complex 2 alleviates inflammatory and neuropathic pain
Bibliographic record
Abstract
The development and maintenance of chronic pain involve the reorganization of spinal nocioceptive circuits. The mechanistic target of rapamycin complex 2 (mTORC2), a central signalling hub that modulates both actin-dependent structural changes and mechanistic target of rapamycin complex 1 (mTORC1)-dependent mRNA translation, plays key roles in hippocampal synaptic plasticity and memory formation. However, its function in spinal plasticity and chronic pain is poorly understood. Here, we show that pharmacological activation of spinal mTORC2 induces pain hypersensitivity, whereas its inhibition, using downregulation of the mTORC2-defining component Rictor, alleviates both inflammatory and neuropathic pain. Cell type-specific deletion of Rictor showed that the selective inhibition of mTORC2 in a subset of excitatory neurons impairs spinal synaptic potentiation and alleviates inflammation-induced mechanical and thermal hypersensitivity and nerve injury-induced heat hyperalgesia. The ablation of mTORC2 in inhibitory interneurons strongly alleviated nerve injury-induced mechanical hypersensitivity. Our findings reveal the role of mTORC2 in chronic pain and highlight its cell type-specific functions in mediating pain hypersensitivity in response to peripheral inflammation and nerve injury.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".