Striatal pre- and postsynaptic profile of adenosine A2A receptor antagonists

Striatal adenosine A2A receptors (A2ARs) are highly expressed in medium spiny neurons (MSNs) of the indirect efferent pathway, where they heteromerize with dopamine D2 receptors (D2Rs). A2ARs are also localized presynaptically in cortico-striatal glutamatergic terminals contacting MSNs of the direct efferent pathway, where they heteromerize with adenosine A1 receptors (A1Rs). It has been hypothesized that postsynaptic A2AR antagonists should be useful in Parkinson's disease, while presynaptic A2AR antagonists could be beneficial in dyskinetic disorders, such as Huntington's disease, obsessive-compulsive disorders and drug addiction. The aim or this work was to determine whether selective A2AR antagonists may be subdivided according to a preferential pre- versus postsynaptic mechanism of action. The potency at blocking the motor output and striatal glutamate release induced by cortical electrical stimulation and the potency at inducing locomotor activation were used as in vivo measures of pre- and postsynaptic activities, respectively. SCH-442416 and KW-6002 showed a significant preferential pre- and postsynaptic profile, respectively, while the other tested compounds (MSX-2, SCH-420814, ZM-241385 and SCH-58261) showed no clear preference. Radioligand-binding experiments were performed in cells expressing A2AR-D2R and A1R-A2AR heteromers to determine possible differences in the affinity of these compounds for different A2AR heteromers. Heteromerization played a key role in the presynaptic profile of SCH-442416, since it bound with much less affinity to A2AR when co-expressed with D2R than with A1R. KW-6002 showed the best relative affinity for A2AR co-expressed with D2R than co-expressed with A1R, which can at least partially explain the postsynaptic profile of this compound. Also, the in vitro pharmacological profile of MSX-2, SCH-420814, ZM-241385 and SCH-58261 was is in accordance with their mixed pre- and postsynaptic profile. On the basis of their preferential pre- versus postsynaptic actions, SCH-442416 and KW-6002 may be used as lead compounds to obtain more effective antidyskinetic and antiparkinsonian compounds, respectively.

Inhibition of nociceptive responses after systemic administration of amidated kyotorphin

BACKGROUND AND PURPOSE Kyotorphin (KTP; L-Tyr-L-Arg), an endogenous neuropeptide, is potently analgesic when delivered directly to the central nervous system. Its weak analgesic effects after systemic administration have been explained by inability to cross the blood-brain barrier (BBB) and detract from the possible clinical use of KTP as an analgesic. In this study, we aimed to increase the lipophilicity of KTP by amidation and to evaluate the analgesic efficacy of a new KTP derivative (KTP-amide - KTP-NH 2). EXPERIMENTAL APPROACH We synthesized KTP-NH 2. This peptide was given systemically to assess its ability to cross the BBB. A wide range of pain models, including acute, sustained and chronic inflammatory and neuropathic pain, were used to characterize analgesic efficacies of KTP-NH 2. Binding to opioid receptors and toxicity were also measured. KEY RESULTS KTP-NH 2, unlike its precursor KTP, was lipophilic and highly analgesic following systemic administration in several acute and chronic pain models, without inducing toxic effects or affecting motor responses and blood pressure. Binding to opioid receptors was minimal. KTP-NH 2 inhibited nociceptive responses of spinal neurons. Its analgesic effects were prevented by intrathecal or i.p. administration of naloxone. CONCLUSIONS AND IMPLICATIONS Amidation allowed KTP to show good analgesic ability after systemic delivery in acute and chronic pain models. The indirect opioid-mediated actions of KTP-NH 2 may explain why this compound retained its analgesic effects although the usual side effects of opioids were absent, which is a desired feature in next-generation pain medications

Neural mechanisms underlying adaptive actions after slips

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory thetabeta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

Indirect likelihood inference (revised)

Standard indirect Inference (II) estimators take a given finite-dimensional statistic, Z_{n} , and then estimate the parameters by matching the sample statistic with the model-implied population moment. We here propose a novel estimation method that utilizes all available information contained in the distribution of Z_{n} , not just its first moment. This is done by computing the likelihood of Z_{n}, and then estimating the parameters by either maximizing the likelihood or computing the posterior mean for a given prior of the parameters. These are referred to as the maximum indirect likelihood (MIL) and Bayesian Indirect Likelihood (BIL) estimators, respectively. We show that the IL estimators are first-order equivalent to the corresponding moment-based II estimator that employs the optimal weighting matrix. However, due to higher-order features of Z_{n} , the IL estimators are higher order efficient relative to the standard II estimator. The likelihood of Z_{n} will in general be unknown and so simulated versions of IL estimators are developed. Monte Carlo results for a structural auction model and a DSGE model show that the proposed estimators indeed have attractive finite sample properties.