As shown by the representative experiment depicted in Fig. 3, four peaks of enzyme activity were resolved by MonoQ chromatography , which were all effectively inhibited by BTNP . Multiple peaks of anandamide amidohydrolase activity have been already observed after pa tial purification from pig brain microsomes, but the significance of these putative isoforms is still unknown.The recent cloning of an hydrolase involved in the degradation of long-chain fatty acid amides, including anandamide, should help shed light on this question. In the rat, anandamide amidohydrolase activity is mainly localized in liver and brain. When tested on crude microsomes prepared from rat liver tissue, BTNP inhibited anandamide hydrolysis with an IC50 that was about 100-fold greater than that measured in brain microsomes . However, this marked difference likely resulted from BTNP degradation by liver enzymes, rather than from the existence of tissue-specific amidohydrolase isoenzymes. Two findings support such conclusion. First, after FPLC fractiona tion, anandamide amidohydrolase activity from liver was in hibited by BTNP as effectively as the activity from brain . Second, incubation of BTNP with a mixture of brain and liver microsomes for 10 min at 37°C prevented the inhibition of anandamide hydrolysis . The regional distribution of anandamide hydrolysis in the rat central nervous system, paralleling that of CBi cannabinoid receptors, suggests that this enzymatic reaction may be at least in part responsible for the biological disposition of anan damide. Yet, it is still unclear whether anandamide ami dohydrolase activity is localized in neurons, in glial cells or in both. We prepared cell-type specific cultures of neurons or astrocytes from the cortex of embry onic rats,grow table and measured anandamide amidohydrolase activity in homogenates of these cultures. Supporting a preferential neuronal localization, we found that the enzyme activity was 12-fold greater in neurons than in astrocytes .
BTNP was equally potent in inhibiting anandamide amidohydrolase activity, producing in either cell type an in hibition of approximately 80% at 0.5 xM . Noteworthy, Shivachar and coworkers have previously reported that cultures of rat cortical astrocytes contain negligible levels of anandamide amidohydrolase activity. This discrepancy may be due to different culture con ditions and/or assay sensitivity. To determine whether BTNP inhibits anandamide hydrol ysis in intact cells, we tested its effects on primary cultures of rat cortical neurons, incubated for 4 min in a medium con taining [ 3H]anandamide. As previously noted, [ 3H]anand amide was readily hydrolyzed by the neurons, and virtually all of the [ 3H]arachidonate produced in this reaction was found esterified into cellular phospholipids, most prominently into phosphatidylcholine and phosphatidylethanolamine. BTNP prevented [ 3H]anandamide hydrolysis by theneurons in a concentration-dependent manner, as indicated by a reduced incorporation of [3H]arachidonate into PC and PE, as well as by an increased intracellular accumulation of un metabolized [3H]anandamide. Both effects occurred with an IC5o close to 0.1 u,M . We have also investigated the effects of BTNP on the en zymes involved in anandamide biosynthesis. In mixed cortical cultures, formation of anandamide and other 7V-acylethanol amines is thought to be mediated by a D-type phospholipase activity, and is stimulated by the Ca2+ ionophore ionomycin. To determine whether BTNP inhibits JV-acyletha nolamine formation we labeled cortical cultures overnight with [3H]ethanolamine, and stimulated them with ionomycin either in the presence or in the absence of BTNP . Radioactivity in the TV-acylethanolamine fractions, de termined after TLC fractionation, was: control 83 ±41 dpm, ionomycin 123 ±9 dpm, ionomycin plus BTNP 248 ± 35 dpm . These results suggest that BTNP inhibits anandamide degradation without affecting the formation of anandamide and other JV-acylethanolamines. Next, we measured the effects of BTNP on the biosynthesis of 7V-arachidoyl PE, a putative anadamide precursor. Particulate fraction of the rat brain tissue were incubated at 37°C for 60 min in the presence of di[14C]arachidonoyl phosphatidylethanolamine and the N arachidonoyl PE produced was fractionated by TLC. Under these conditions, BTNP inhibited A^-arachidonoyl PE with an IC50 of approximately 2 u.M. Despite having a comprehensive tobacco control policy, cigarette smoking continues to be the leading cause of preventable morbidity and mortality in China and other developing countries, as it already is in developed countries today, and accounts for 5 million deaths globally each year. When cigarettes are smoked, a host of harmful chemicals contribute to the deleterious effects. Mounting scientific evidence proves the association between chronic smoking and lung cancer, chronic obstructive pulmonary disease, vascular disease, stroke, and peptic ulcer disease, as well as a wide range of other adverse health effects.
Understanding the mechanism of nicotine dependence and developing better therapies to help with smoking cessation is an urgent need. Emerging technologies, such as neuroimaging and genomics, have contributed to new insights into the neurophar macology of tobacco addiction. There is considerable literature from functional neuroimaging studies assessing the effects of chronic cigarette smoking on brain structure and function. However, while several studies have examined gray matter differences between smokers and non-smokers, much is less known about the white matter structural changes in brain in chronic cigarette smokers. Using magnetic resonance imaging to examine the brain structure and function in chronic cigarette smoker provides a better understanding about the adverse effects of chronic cigarette smoking on brain. Diffusion tensor imaging is a sensitive method to measure micro-structural changes by detecting self-diffusion of water molecules caused by Brownian motion and providing parameters of the diffusion tensor, the most commonly used parameter is fractional anisotropy.Increased FA indicates a non-spherical tensor with preferential orientation in a particular direction, while a decreased FA indicates more isotropic diffusion which has been found to becharacteristic of disrupted or damaged whiter matter. It has been widely used to identify and quantify white matter abnormalities in psychiatric and neurological diseases, such as schizophrenia showed significantly higher levels of FA in the corpus callosum than nonsmokers; the low Fagerstro¨m scores group exhibited significantly higher levels of FA in the body of the corpus callosum than the high Fagerstro¨m group and the nonsmokers. Jacobsen et al reported that prenatal and adolescent exposure to tobacco smoke showed higher FA in anterior cortical white matter; adolescent smoking also showed higher FA in internal capsule. Recently, Xiaochu Zhang et al examined a relatively large sample of smokers and found that the most highly dependent smokers exhibited lower prefrontal FA, which was negatively correlated with Fagerstro¨m Test of Nicotine Dependence. In the present study,4×8 grow table with wheels we examined white matter changes in a relatively large sample of nicotine dependent smokers and non smokers matched for a number of demographic variables using DTI.Eighty-eight subjects , 19–39 years of age, were recruited from the local community using advertisements. They were initially screened during a semi-structured telephone interview to assess smoking, medical, psychiatric, medication, and substance use history.
Smokers who had smoked 10 cigarettes per day or more during the previous year and had no period of smoking abstinence longer than 3 months in the past year, and met DSM-IV criteria for nicotine dependence were eligible for this study. All smokers self reported no smoking for the 12 hours before scanning. Nicotine patches were provided as needed. Nonsmoking history was defined as having smoked no more than five cigarettes lifetime. Participants were excluded if they were a minority other than Han Chinese or had: a diagnosis of mental retardation, current or past alcohol or drug abuse/dependence, a current or past central nervous system disease or condition, a medical condition or disease with likely significant central nervous system effects, history of head injury with skull fracture or loss of consciousness greater than 10 min, a physical problem that would render study measures difficult or impossible, any current or previous psychiatric disorder, a family history of a psychotic disorder, current or previous use of electroconvulsive therapy or psychotropic medications, or a positive pregnancy test. A licensed psychiatrist conducted all clinical interviews. The protocol was approved by the university ethics committee and the studies were carried out in accordance with the Declaration of Helsinki. Subjects were fully informed about the measurement and MRI scanning in the study. Written informed consent was given by all study participants. None of the participants reported daily consumption of alcohol, and none reported experiencing social consequences secondary to alcohol use, or any history with difficulty ceasing alcohol intake. All non-smokers in this sample reported no history of smoking behavior in the past.Diffusion tensor images were preprocessed using previously published methods . The diffusion data set was pre-aligned to correct for head motion, and the effects of gradient coil eddy currents using software tools from the FMRIB software library . After these steps, the diffusion tensor at each voxel was calculated using the FMRIB diffusion toolbox in FSL. The resulting FA images were trans formed into Montreal Neurological Institute standard space with Statistical Parametric Mapping 5 by means of the following steps: the b = 0 images were co-registered with the structural T1 image for that individual, the same co-registration parameters were applied to the FA maps , each individual’s T1 image was then normalized to the SPM T1 template , and the same normalization parameters were then applied to the co-registered FA images. Finally, FA images were smoothed with an 8-mm full width at half-maximum Gaussian kernel. Then, all images were re sampled with a final voxel size of 26262 mm3 . Each FA image was then spatially smoothed by an 8-mm full-width at half the maximum Gaussian kernel in order to decrease spatial noise and compensate for the inexact nature of normalization.Between-group tests were performed on diffusion tensor images of FA using a parametric two sample t-test on a voxel-by-voxel basis using SPM5 software. A prior white matter mask from WFU_PickAtlas was used to restrict the search volume for analysis.
Clusters of 100 voxels or more, surviving an uncorrected threshold of p,0.001, were considered significant. For visualization of the regions showing significantly different FA values between the two groups, significant clusters were superimposed onto SPM5’s spatially normalized template brain. Fiber tracts corresponding to the clusters were identified with reference to the Johns Hopkins University DTI-based White Matter Atlas analyses was performed. MarsBar 0.41 was used to extract ROIs containing all the voxels classified as white matter from spatially normalized and smoothed FA images. Then, mean FA values of the ROI were calculated using log_roi_batch v2.0 . Finally, the aver age FA values of individual clusters were calculated for each subject. A two-sample t-test was used to compare these FA values of the clusters between smokers and non-smoking controls. We used P,0.05 as a statistical threshold to search for significant differences. Correlational analysis of FA values with smoking-related factors including age of smoking onset, number of cigarettes smoked per day, years of smoking and smoking cravings were examined using bivariate correlational analysis . The T1-weighted images were segmented by using VBM5.1 procedures into white matter, gray matter, and CSF . Then, the white matter volumes were compared between groups by univariate GLM using total brain volume as covariate.The present study provides evidence of micro-structural white matter modifications in chronic smokers as measured by whole brain analysis of FA using DTI. Specifically, increased FA was found in white matter of the bilateral fron to-parietal cortices in cigarette smokers relative to healthy non-smoking comparison subjects. In contrast to the findings here with chronic cigarette smokers, previous studies with other drug dependent subjects revealed decreased FA in white matter of the brain. In patients with heroin dependence, reduced FA was observed in the bilateral frontal subgyral cortices, right precentral, and left cingulate gyrus. In cocaine-dependent subjects, lower FA was reported in inferiorfrontal white matter at the anterior-posterior commissure plane, in frontal white matter at the anterior commissure-posterior commissure plane, and in the genu and rostral body of the anterior corpus callosum. Similarly, lower FA in the right frontal white matter is also frequently reported in methamphet amine users and alcohol drinkers, and recently reported in chronic ketamine users. Convergent evidence suggests that chronic drug use is associated with decreased FA in white matter of the multiple brain regions, especially in the frontal lobe. Results of this study, along with previous findings, suggest increased FA, such that the effects of chronic cigarette smoking on brain white matter are different from effects of other addictive drugs. Increased FA may reflect increased maturation in cell packing density, fiber diameter, and directional coherence.