In vitro metabolism of tiletamine, zolazepam and nonbenzodiazepine sedatives: Identification of target metabolites for equine doping control

A review of equine anesthetic induction: Are all equine anesthetic inductions "crash" inductions?

Horses are the most challenging of the common companion animals to anesthetize. Induction of anesthesia in the horse is complicated by the fact that it is accompanied by a transition from a conscious standing position to uncconconscious recumbency. The purpose of this article is to review the literature on induction of anesthesia with a focus on the behavioral and physiologic/pharmacodynamic responses and the actions and interactions of the drugs administered to induce anesthesia in the healthy adult horse with the goal of increasing consistency and predictability.

Cardiopulmonary (No Ventilation) and Anesthetic Effects of Dexmedetomidine-Tiletamine in Dogs

The aim of the present study was to evaluate the anesthetic and cardiopulmonary effects of dexmedetomidine in combination with tiletamine (without zolazepam) as a general anesthetic. The study was divided into two phases. In Phase 1, 18 adult healthy mixed-breed dogs were randomly allocated into three groups: Group TD8 (4.5 mg kg⁻¹ tiletamine and 8 μg kg⁻¹ dexmedetomidine), Group TD10 (4.5 mg kg⁻¹ tiletamine and 10 μg kg⁻¹ dexmedetomidine), or Group TD12 (4.5 mg kg⁻¹ tiletamine and 12 μg kg⁻¹ dexmedetomidine). After drug administration, the heart rate (HR), respiratory rate (f_R), mean arterial pressure (MAP), systolic arterial pressure (SAP), diastolic arterial pressure (DAP), peripheral hemoglobin oxygen saturation (SpO₂), behavioral score, quality of induction and recovery, extent of ataxia, the time taken for induction, and the duration of anesthesia were recorded. The recovery time and quality were recorded after administration of atipamezole (50 μg kg⁻¹) after 60 min. In phase 2, the feasibility of combining dexmedetomidine (10 μg kg⁻¹) and tiletamine (4.5 mg kg⁻¹) as general anesthetics for orchiectomy was evaluated in dogs (n = 6). HR, f_R, MAP, SAP, DAP, temperature, SpO₂, behavioral scores, and adverse reactions were recorded during each surgical procedure. In phase 1, the dogs were anesthetized for 5 min after administration of drugs and achieved a maximum behavioral score in TD10 and TD12 after 10 min. Although HR, MAP, SAP, DAP, and NIBP decreased in all three groups, they still maintained within the normal range. In phase 2, orchiectomy was completed smoothly in all dogs with little fluctuation in the physiological variables. We found that a combination of tiletamine (4.5 mg kg⁻¹) and dexmedetomidine (10 μg kg⁻¹) intramuscularly induced moderate anesthesia in dogs and could be utilized for short-term anesthesia and minor surgery.

Identification and characterization of new impurities in zopiclone tablets by LC-QTOF-MS

Zopiclone, a non-benzodiazepine hypnotic, is the first-line treatment for insomnia. The quality and stability of zopiclone tablets directly affects its efficacy and safety. However, the impurity investigation in zopiclone tablets remain incomplete. In this study, the accelerated and long-term stabilities of zopiclone tablets, as well as the stability characteristics under thermal and photolytic conditions were evaluated according to the ICH guidelines. In addition, a sensitive and specific LC-QTOF-MS method was developed for the separation and identification of all the impurities in zopiclone tablets and its stability test samples. Nine impurities were found in the test samples, five among them have not been reported before. Based on the accurate mass and elemental compositions of the parent and product ions obtained, the structures of all the detected impurities were identified. Combined with the formulation composition analysis and stability studies, the origins and the formation mechanisms of these impurities were elucidated. The obtained results are useful for the establishment of the optimum formulation, storage condition, manufacturing processes and quality control of zopiclone tablets.

Identification of metabolites of liquiritin in rats by UHPLC-Q-TOF-MS/MS: metabolic profiling and pathway comparisonin vitroandin vivo

Liquiritin (LQ), the main bioactive constituent of licorice, is a common flavoring and sweetening agent in food products and has a wide range of pharmacological properties, including antidepressant-like, neuroprotective, anti-cancer and anti-inflammatory properties. This study investigated the metabolic pathways of LQ in vitro (rat liver microsomes) and in vivo (rat model) using ultra high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS). Moreover, supplementary tools such as key product ions (KPIs) were employed to search for and identify compounds. As a result, 56 in vivo metabolites and 15 in vitro metabolites were structurally characterized. Oxidation, reduction, hydrolysis, methylation, acetylation, and sulfate and glucuronide conjugation were determined to be the major metabolic pathways of LQ, and there were differences in LQ metabolism in vitro and in vivo. In addition, the in vitro and in vivo metabolic pathways were compared in this study.

Liquiritin (LQ), the main bioactive constituent of licorice, is a common flavoring and sweetening agent in food products and has a wide range of pharmacological properties, including antidepressant-like, neuroprotective and anti-cancer properties.

UHPLC-Q-TOF-MS/MS Method Based on Four-Step Strategy for Metabolism Study of Fisetin in Vitro and in Vivo

Fisetin has been identified as an anticancer agent with antiangiogenic properties in mice. However, its metabolism in vitro (rat liver microsomes) and in vivo (rats) is presently not characterized. In this study, ultra-high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) was employed for data acquiring, and a four-step analytical strategy was developed to screen and identify metabolites. First, full-scan was applied, which was dependent on a multiple mass defect filter (MMDF) combined with dynamic background subtraction (DBS). Then PeakView 1.2 and Metabolitepilot 1.5 software were used to load data to seek possible metabolites. Finally, metabolites were identified according to mass measurement and retention time. Moreover, isomers were distinguished based on Clog P parameter. Based on the proposed method, 53 metabolites in vivo and 14 metabolites in vitro were characterized. Moreover, metabolic pathways mainly included oxidation, reduction, hydrogenation, methylation, sulfation, and glucuronidation.