HPLC-MS-MS Determination of ZCZ-011, A Novel Pharmacological Tool for Investigation of the Cannabinoid Receptor in Mouse Brain Using Clean Screen FASt Column Extraction
Bibliographic record
Abstract
A high-performance liquid chromatography tandem mass spectrometry method was developed for the detection and quantification of 6-methyl-3-(2-nitro-1-(thiophen-2-yl)propyl)-2-phenyl-1H-indole (ZCZ-011) using 2-phenylindole as the internal standard (ISTD). ZCZ-011 was synthesized as a possible positive allosteric modulator with the CB1 cannabinoid receptor. The analytical method employs a rapid extraction technique using Clean Screen FASt™ columns with a Positive Pressure Manifold. FASt™ columns were originally developed for urine drug analysis but we have successfully adapted them to the extraction of brain tissue. Chromatographic separation was performed on a Restek Allure Biphenyl 5 µ, 100 × 3.2 mm column (Bellefonte, PA). The mobile phase consisted of 1:9 deionized water with 10 mmol ammonium acetate and 0.1% formic acid-methanol. The following transition ions (m/z) were monitored for ZCZ-011: 363 > 207 and 363 > 110 and for the ISTD: 194 > 165 and 194 > 89. The FASt™ columns lowered and stabilized the ion suppression over the linear range of the assay (40-4,000 ng/g). The method was evaluated for recovery, ion suppression, accuracy/bias, intraday and interday precision, bench-top stability, freeze-thaw and post-preparative stability. The method was successfully applied to brain tissue from C57BL/6J mice that received intraperitoneal (i.p.) injections with 40 mg/kg of ZCZ-011 or vehicle.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".