In-vivo pharmacological evaluation of the CB1-receptor allosteric modulator Org-27569
Bibliographic record
Abstract
Several allosteric modulators (AMs) of the CB1 receptor have been characterized in vitro, including Org27569, which enhances CB1-specific binding of [H]CP55,940, but behaves as an insurmountable CB1-receptor antagonist in several biochemical assays. Although a growing body of research has investigated the molecular actions of this unusual AM, it is unknown whether these actions translate to the whole animal. The purpose of the present study was to determine whether Org27569 would produce effects in well-established mouse behavioral assays sensitive to CB1 orthosteric agonists and antagonists. Similar to the orthosteric CB1 antagonist/inverse agonist rimonabant, Org27569 reduced food intake; however, this anorectic effect occurred independently of the CB1 receptor. Org27569 did not elicit CB1-mediated effects alone and lacked efficacy in altering antinociceptive, cataleptic, and hypothermic actions of the orthosteric agonists anandamide, CP55,940, and Δ-tetrahydrocannabinol. Moreover, it did not alter the discriminative stimulus effects of anandamide in FAAH-deficient mice or Δ-tetrahydrocannabinol in wild-type mice in the drug discrimination paradigm. These findings question the utility of Org27569 as a 'gold standard' CB1 AM and underscore the need for the development of CB1 AMs with pharmacology that translates from the molecular level to the whole animal.
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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 | 0.000 | 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 | 0.001 |
| 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".