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1.
Front Pharmacol ; 13: 996143, 2022.
Article in English | MEDLINE | ID: mdl-36304144

ABSTRACT

Gegen-Qinlian decoction (GQD) is a classic traditional Chinese medicine (TCM) formula. GQD is effective against colon or liver-related diseases including ulcerative colitis, non-alcoholic fatty liver, and type 2 diabetes. In this study, a liquid chromatography-tandem mass spectrometry method was developed, validated, and then applied to reveal the tissue distribution and integrated pharmacokinetic properties of major effective constituents of oral GQD in mice. The established method was quick, sensitive, and accurate enough to analyze GQD constituents in plasma and tissue homogenate samples quantitatively. According to their concentrations in the portal vein, systemic circulation, liver and colon samples of the mice after oral administration of GQD, the concentration-time curves of the constituents were respectively plotted. The results showed that daidzein, baicalin, and baicalein had relatively high exposure levels in the livers, while puerarin, berberine, epiberberine, coptisine, palmatine, jatrorrhizine, magnoflorine, glycyrrhizic acid, and glycyrrhetinic acid were enriched in the colons. Given that these constituents have significant biological activity, they could be regarded as the major effective constituents of GQD in treating colon or liver-related diseases, respectively. In addition, the integrated pharmacokinetic properties of GQD were studied. The GQD "integrated constituent" reached peak concentration at 4.0 h in the portal vein, the systemic circulation, the livers, and the colons, with half-lives of 1.5-4.1 h and mean retention time of 4.5-6.3 h, respectively. Furthermore, the concentration of the GQD "integrated constituent" in the colons was approximately 10 times higher than that in the livers, both of which were much higher than that in the systemic circulation, indicating its accumulation in these tissues, especially in the colons. In conclusion, the tissue distribution and integrated pharmacokinetic properties of oral GQD were revealed in the study. The results of the tissue distribution study would contribute to identifying the major target tissues and effective constituents of GQD, while the results of the integrated pharmacokinetic study would help to explain the pharmacokinetic properties of oral GQD as a whole.

2.
Metab Brain Dis ; 34(2): 417-429, 2019 04.
Article in English | MEDLINE | ID: mdl-30535618

ABSTRACT

The orbitofrontal cortex (OFC) and the medial prefrontal cortex (mPFC) are known to participate in risk-based decision-making. However, whether neuronal activities of these two brain regions play similar or differential roles during different stages of risk-based decision-making process remains unknown. Here we conducted multi-channel in vivo recordings in the OFC and mPFC simultaneously when rats were performing a gambling task. Rats were trained to update strategy as the task was shifted in two stages. Behavioral testing suggests that rats exhibited different risk preferences and response latencies to food rewards during stage-1 and stage-2. Indeed, the firing patterns and numbers of non-specific neurons and nosepoking-predicting neurons were similar in OFC and mPFC. However, there were no reward-expecting neurons and significantly more reward-excitatory neurons (fired as rats received rewards) in the mPFC. Further analyses suggested that nosepoking-predicting neurons may encode the overall value of reward and strategy, whereas reward-expecting neurons show more intensive firing to a big food reward in the OFC. Nosepoking-predicting neurons in mPFC showed no correlation with decision-making strategy updating, whereas the response of reward-excitatory neurons in mPFC, which were barely observed in OFC, were inhibited during nosepoking, but were enhanced in the post-nosepoking period. These findings indicate that neurons in the OFC and mPFC exhibit distinct responses in decision-making process during reward consumption and strategy updating. Specifically, OFC encodes the overall value of a choice and is thus important for learning and strategy updating, whereas mPFC plays a key role in monitoring and execution of a strategy.


Subject(s)
Action Potentials/physiology , Decision Making/physiology , Neurons/physiology , Prefrontal Cortex/physiology , Risk Assessment , Animals , Behavior, Animal , Learning/physiology , Male , Rats, Sprague-Dawley , Reaction Time/physiology , Reward
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