Under the specific conditions of this study, SC as a single agent was inactive in patients with advanced-stage cancer and had no salutary effect on quality of life. The 16.7% rate of SD was similar to results in patients with advanced cancer treated with supportive care alone.
Dopamine D 2 receptor antagonism contributes to the therapeutic action of antipsychotic drugs (APDs) but also produces undesirable side effects, including extrapyramidal motor deficits, cognitive dulling, and prolactinemia. The introduction of atypical APDs was a significant advancement in the treatment of schizophrenia. Whereas these agents are D 2 receptor antagonists, they are also potent 5-hydroxytryptamine (5-HT) 2A receptor inverse agonists, a feature that may explain their improved efficacy and tolerability. Recently, we reported that
N-(4-fluorophenylmethyl)-N-(1-methylpiperidin-4-yl)-N'-(4-(2-methylpropyloxy)phenylmethyl) carbamide (2R,3R)-dihydroxybutanedioate (2:1) (ACP-103), a novel selective 5-HT 2A receptor inverse agonist that fails to bind D 2 receptors, is active in several models predictive of antipsychotic activity. Using ACP-103, we tested the hypothesis that combining high levels of 5-HT 2A inverse agonism with low levels of D 2 antagonism would result in a favorable interaction, such that antipsychotic efficacy could be achieved with reduced D 2 receptor-related adverse effects. Here we show that ACP-103 1) potently inhibited head-twitching produced by the 5-HT 2A/2C receptor agonist (Ϯ)-2,5-dimethoxy-4-iodoamphetamine, 2) increased the potency of haloperidol against amphetamine-induced hyperactivity, 3) interacted synergistically with haloperidol or risperidone to suppress hyperactivity induced by the N-methyl-D-aspartate receptor antagonist (5R,10S)-(ϩ)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine hydrogen maleate (MK-801), and, by contrast, 4) attenuated haloperidol-or risperidone-induced prolactinemia. ACP-103 also attenuated catalepsy produced by haloperidol or risperidone. However, the doses that were required for this effect were higher than would be expected for a 5-HT 2A receptor-mediated mechanism. These data indicate that utilizing ACP-103 as an adjunctive therapy to currently used APDs may result in enhanced antipsychotic efficacy while reducing adverse effects including those attributable to D 2 receptor antagonism.
A microcomputer-based control system applies a combination of steady state and sinusoidal power to a thermistor probe which is inserted into the tissue of interest. The steady-state temperature response is an indication of the effective thermal conductivity (keff), which includes a component due to intrinsic conduction plus a convective component due to the tissue blood flow near the probe. By careful choice of the excitation frequency, the sinusoidal temperature response can be used to measure intrinsic thermal conductivity (km) in the presence of blood flow. Optimal sinusoidal heating frequency depends on the thermistor size. Experimental results in the alcohol-fixed canine kidney cortex show that perfusion is linearly related to the difference keff minus km. The instrument can measure tissue thermal conductivity with an accuracy of 2%. The instrument can resolve changes in perfusion of 10 mL/100g-min with a Thermometrics P60DA102M thermistor. The maximum error in measured perfusion is about 30%. When tissue trauma due to probe insertion is minimized, the self-heated thermistor method gives a reliable indication of local tissue blood flow.
This paper proposes a quantitative method to describe how complex an environment looks to an individual robot. The assumption is that robots are designed to perform a task in a specific setting or group of settings. The structure of the environment and knowledge the robot has about the environment determine how sophisticated the robot hardware and control algorithms need to be to perform a given task. Information about the environment can be 1) obtained from a robot sensors; 2) downloaded or programmed into a robot; or 3) placed in the environment for a robot to read, as needed. Extensive simulations of a search task indicate that a combination of two factors can describe environmental complexity: a measure of entropy and the compressibility of the environment as seen by a robot's sensors. These combined measures can be used as a yardstick by engineers in determining how to design a robot-environment system. They allow the designer to determine how to divide his/her resources between robot hardware/software capabilities and information/structure in an environment. The complexity measure also allows the designer to determine quantitatively what information is most important for improving a robot's performance.
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