Identification of an Adenylyl Cyclase Inhibitor for Treating Neuropathic and Inflammatory Pain
Bibliographic record
Abstract
Neuropathic pain, often caused by nerve injury, is commonly observed among patients with different diseases. Because its basic mechanisms are poorly understood, effective medications are limited. Previous investigations of basic pain mechanisms and drug discovery efforts have focused mainly on early sensory neurons such as dorsal root ganglion and spinal dorsal horn neurons, and few synaptic-level studies or new drugs are designed to target the injury-related cortical plasticity that accompanies neuropathic pain. Our previous work has demonstrated that calcium-stimulated adenylyl cyclase 1 (AC1) is critical for nerve injury-induced synaptic changes in the anterior cingulate cortex. Through rational drug design and chemical screening, we have identified a lead candidate AC1 inhibitor, NB001, which is relatively selective for AC1 over other adenylate cyclase isoforms. Using a variety of behavioral tests and toxicity studies, we have found that NB001, when administered intraperitoneally or orally, has an analgesic effect in animal models of neuropathic pain, without any apparent side effects. Our study thus shows that AC1 could be a productive therapeutic target for neuropathic pain and describes a new agent for the possible treatment of neuropathic pain.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".