Spin-spin relaxation in experimental allergic Encephalomyelitis. Analysis of CPMG data using a non-linear least squares method and linear inverse theory

We have used the CPMG pulse sequence to measure proton T₂ values and water content in spinal cord and brain samples from Hartley guinea pigs inoculated to produce experimental allergic encephalomyelitis (EAE). Relaxation data were fitted using minuit, a non-linear curve fitting routine. Three exponentials provided the best fit to spinal cord data (10 ms (13%), 76 ms (57%), 215 ms (30%)) and two exponentials for brain tissue (10 ms (4%), 92 ms (96%)). Least squares algorithms were also used to analyse the spinal cord data in terms of discrete and smooth distributions of relaxation times. The discrete least squares solutions consisted of three to five isolated spikes between 0.010 and 0.300 s. This type of solution was difficult to interpret in terms of water reservoirs. Smooth solutions consisted of two broad peaks, a small peak with a T₂ near 0.010 s and a larger peak near 0.100 s. The integral ratio of the larger to the smaller peak was 7.092 ± 1.782 for normal tissue, and increased to a maximum of 16 with increasing parenchymal cellular infiltration and demyelination. The short T₂ peak has been assigned to water in the hydration layers of the myelin sheath. The width of the longer T₂ peak was sensitive to tissue heterogeneity. The least squares and smooth distribution analysis models could be used to distinguish samples with extensive parenchymal infiltration from normal tissue, even though only a maximum of 60% of the tissue was affected. The short T₂ component could provide a direct method of measuring intact myelin, which would have a profound effect on the understanding of the evolution of pathology in multiple sclerosis.     

Comparing the effects of scopolamine on operant and aggressive responses in squirrel monkeys

The anticholinergic drug, scopolamine, causes disinhibition or an increase in response that an animal normally suppresses. Experiment 1 confirmed this effect in squirrel monkeys. Experiment 2 explored the implications of drug-produced disinhibition on aggressive interactions. In Experiment 1, scopolamine produced increased unreinforced responding on a DRL schedule and increased responding during unreinforced (Time Out) periods. In contrast, the peripheral control drug, methyl scopolamine, caused decreased responding in both situations. In Experiment 2, social rank and drug treatment interacted. When space was restricted so that the opportunity for social interactions was maximized, scopolamine consistently increased aggressiveness in the dominant monkey and decreased aggressiveness in a submissive monkey. When space was increased so that the opportunity for social interactions was minimized, scopolamine caused decreased aggressive responses in all monkeys. Neither the effective dosage nor the drug's effect on the operant task could be easily generalized to aggressive responses.     

Modulation of cytochrome P450 activity: implications for cancer therapy

Although metabolism mediated by cytochrome P450 isoenzymes is known to play a major part in the biotransformation of anticancer agents in vivo, few clinical studies have investigated activity of cytochrome P450s and therapeutic outcome in people with cancer. Variability between individuals in the pharmacokinetics of cancer chemotherapy has important consequences in terms of therapeutic efficacy and safety. We discuss here the effect of drug metabolism mediated by cytochrome P450 on therapeutic outcome. As examples, the biotransformation pathways of cyclophosphamide, ifosfamide, tamoxifen, docetaxel, paclitaxel, and irinotecan are discussed. Since most anticancer agents are transformed by enzymes, better knowledge of their metabolic pathways could help improve treatment outcome and safety. Furthermore, a more complete understanding of the metabolism of anticancer agents through phenotyping and genotyping approaches will facilitate the prediction of interactions between drugs. More clinical evidence is needed on the metabolic transformation and drug interactions with these agents to improve cancer therapeutics.     

Mode of action: disruption of brain cell replication, second messenger, and neurotransmitter systems during development leading to cognitive dysfunction--developmental neurotoxicity of nicotine

Developmental exposure to nicotine in rats results in neurobehavioral effects such as reduced locomotor and cognitive function. Key events in the animal mode of action (MOA) include binding to the nicotinic cholinergic receptor during prenatal and/or early postnatal development. This leads to premature onset of cell differentiation at the expense of cell replication, which leads to brain cell death or structural alterations in regional brain areas. Other events include an initial increase followed by a decrease in adenyl cyclase activity, as well as effects on the noradrenergic, dopaminergic, and serotonergic neurotransmitter systems. Because the nicotine receptor is also present in the developing human brain and the underlying biology for DNA synthesis and cell signaling is comparable, this MOA is likely to be relevant for humans. Although the effects of nicotine exposure in developing humans is not well documented, nicotine exposure as a result of cigarette smoking during pregnancy is associated with several physiological and behavioral outcomes that are reminiscent of the effects of nicotine alone in animal models. As data become available with the advent of the use of the nicotine patch in pregnant humans, the question as to the relative importance of smoking per se versus nicotine alone may be determined.     

Predictive in silico modeling for hERG channel blockers

hERG-mediated sudden death as a side effect of non-antiarrhythmic drugs has been receiving increased regulatory attention. Perhaps owing to the unique shape of the ligand-binding site and its hydrophobic character, the hERG channel has been shown to interact with pharmaceuticals of widely varying structure. Several in silico approaches have attempted to predict hERG channel blockade. Some of these approaches are aimed primarily at filtering out potential hERG blockers in the context of virtual libraries, others involve understanding structure-activity relationships governing hERG-drug interactions. This review summarizes the most recent efforts in this emerging field.