Neuronal Adenylyl Cyclase Targeting Central Plasticity for the Treatment of Chronic Pain
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
Chronic pain is a major health problem and the effective treatment for chronic pain is still lacking. The recent crisis created by the overuse of opioids for pain treatment has clearly shown the need for non-addictive novel pain medicine. Conventional pain medicines usually inhibit peripheral nociceptive transmission and reduce central transmission, especially pain-related excitatory transmission. For example, both opioids and gabapentin produce analgesic effects by inhibiting the release of excitatory transmitters and reducing neuronal excitability. Here, we will review recent studies of central synaptic plasticity contributing to central sensitization in chronic pain. Neuronal selective adenylyl cyclase subtype 1 (AC1) is proposed to be a key intracellular protein that causes both presynaptic and postsynaptic forms of long-term potentiation (LTP). Inhibiting the activity of AC1 by selective inhibitor NB001 blocks behavioral sensitization and injury-related anxiety in animal models of chronic pain. We propose that inhibiting injury-related LTPs will provide new mechanisms for designing novel medicines for the treatment of chronic pain and its related emotional disorders.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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