Methadone: Efficacy for Reduction of Heroin/Opiate Use and Opiate Withdrawal Syndrome

Here is another review I did for my senior seminar course. A bit in-depth, but feel free to leave questions below.

Introduction

Heroin and opiate addiction are major problems in America. Approximately 4.2 million American citizens (over the age of 12) have used heroin at some point in their lifetime. Of the number of Americans who have tried heroin 23% of the users became addicted, which is equated to approximately 1.3 million people (NIDA, 2014). Methadone-based treatments are typical for both the symptomology of opiate withdrawal syndrome as well as the general reduction of heroin/opiate use.

Prescribed under normal circumstances, methadone is given to individuals with an opiate addiction. Varying quantities are given to taper the patient’s use of heroin until they no longer need the prescription. Studies have shown that methadone can be effective if prescribed responsibly and knowledgably, which includes monitoring the pharmaco-dynamics (the study of the physiological effects that a drug, in this case methadone, engenders within the body) /kinetics ( the study of the distribution and effect the body has upon a drug) effects of the drug to circumvent the pain that is typical with opiate withdrawal syndrome (Garrido & Troconiz, 2000). Garrido and Troconiz (2000) further the discussion upon the efficacy of methadone based treatments by calling for concentrated research and work to be conducted within the field of pharmaco-dynamic/kinetics.

Confusion about dosing creates grounds for pharmacological ignorance of methadone and has lead to relapse and ineffective opioid treatment programs. Since the mid 1960’s the amount of methadone prescribed has fluctuated (Dole and Nyswander, 1965). By the mid 1970’s researchers were giving opioid addicted patients doses as small as 30 mg/ daily (Maremmani, 1993). In order to provide effective treatment for patients with opioid addiction, it is necessary to have a cogent understanding of methadone’s binding site within the brain, the pharamco-dynamics/kinetics, and also problems that may lead some patients to relapse after or during methadone treatment.

Methadone: Where it binds and binding effects

Methadone binds to a number of different subtypes upon the opiate receptors in a non-specific pattern, including μ, δ, κ, and λ. More specifically, methadone binds to the μ opiate receptors with greater efficacy. Opiate receptors are typically seven transmembrane g-protein coupled receptors. Opioid receptors can be endogenously activated via neuropeptides such as endorphins or through exogenous sources such as heroin/morphine/ methadone.(Elde et al., 1971). Methadone binding to the μ opioid receptor starts a signaling cascade that is only possible because of this receptor’s ability to be versatile.

Opioid receptors are extremely dynamic and therefore have the ability to bind multiple ligands. In the case of methadone, once it is bound to the opioid receptors it acts as an opioid receptor agonist. When methadone binds to the opioid receptors it causes a confirmation change at the transmembrane protein 3 and 7 (TM3/ TM7) (Pogozheva, Lomize, Mosberg, 1998). The change in the membrane confirmation stimulates the G-protein inhibitory pathway (Gi). The Gi pathway will then inhibit adenylyl cyclases and voltage gates calcium channels. This entire process aids in the opioid receptor endocytosis and eventually makes synapses depotentiated and therefore, less active (New and Wong, 2002; Garrido and Troconiz, 2000).

Much like the other receptors in the brain, the μ receptor is versatile and when activated by ligands, such as methadone, has the ability to revert synapses to their original states. The μ receptor can be sensitized by long-term opioid dependence to have hyperalgesic effects (Wolff, 1991). Hyperalgesia is the sensation that increases pain sensitivity to normally innocuous stimuli. It has been observed that in animals and humans receiving opioid administration can lead to progressive and lasting reduction of baseline nociceptive thresholds, this would then result in nociceptive sensitivity (Mao, Price, Mayer, 1994; Mao et al., 2002a; 2002b; Vanderah et al., 2001; Vinik, Igor, 1998; Crawford et al., 2006). According to Bulka and colleauges (2002), methadone can actually have an anti-hyperalgesic effect on rats with severed sciatic nerves. Methadone induced anti-hyperalgesia could be looked at as a way to reduce the overwhelming sensitivity that can be experienced by patients going through opioid withdrawal who tend to experience pain during their withdrawal.

Methadone also has a high affinity to bind to N-methyl-D-aspertate receptors (NMDA) which are coupled with a G- protein. More specifically, methadone binds efficaciously at the [H]MK-801 binding site. Ebert and colleagues (1995) also observed that methadone affects the opiate receptors in a quantity specific pattern. Therefore as the dosage proliferates, the more inhibited, or antagonized, the NMDA receptors become. Methadone has been also observed to have a slow off rate. A slow off rate means that methadone stays bound to the [H]MK-801 binding site for a longer period of time than an average opioid antagonist. The slow off rate of methadone results in a greater lasting effect, which will be explained within the pharmacodynamics section of this review. All of these effects help to reduce opiate withdrawal syndrome (Ebert Andersen, Krogsgaard-Larsen, 1995).

Once methadone binds to the NMDA receptors, it acts as a non-competitive antagonist. A non-competitive antagonist provides that the receptors confirmation is changed and will therefore occlude glutamate binding as well as the conduction of sodium ions (Na+) (Ebert, Andersen, Krogsgaard-Larsen, 1995; Gorman, Elliot, Inturrissi, 1997; Inturrissi, 1997; Mao, Price, Mayer, 1994). Neurons, which have built strong connections within areas of the brain, such as the reward pathway, can then be depotentiated by NMDA receptors being anatagonized by the binding of methadone. (New &Wong, 2002; Garrido, Troconiz, 2000). Reverting back to the depotentiated state of the neuron may also be responsible for the anti-hyperalegsic and reduction in opiate withdrawal syndrome via synapse desensitization.

Methadone: Pharmacodynamics

In the field of methadone research, attention has been paid towards the investigation of pharmacodynamics to better understand the physiological effects that methadone engenders within the body. While studying methadone pharmacodynamics, it has been observed that the binding of opiates produce analgesic effects upon the subject when administered. This is particularly the case when opiates bind to the μ receptor, more specifically the μ2 receptor subtype (Elde et al., 1980). Matthes and colleagues (1996) have also observed that if the MOR gene (which codes for the μ receptor) is knocked out in mice, the mutation produces an attenuated analgesic effect. A qualitative study performed by De Maeyer and colleagues (2011) helped to understand why methadone treatments are used to restore quality of life when opiate withdrawal syndrome can be a painful process. Therefore, taking methadone promotes analgesic effects as positive symptoms as well as desirable symptoms. However, while this is a wanted effect of methadone, there are also pharmacodynamic negative effects of methadone treatment, which include respiratory depression and physiological dependence.

Adverse pharmacodynamic effects of methadone treatment include respiratory depression and methadone-induced dependence. The cause of respiratory depression in methadone treatment have been shown to occur when methadone binds to the specific μ receptor subtype, μ2 (Ling; Spiegel; Lockhard; Pasternak., 1985). It has also been observed that Methadone can be highly addictive in mice but seems to have a lowered addictive effect upon humans when binding with the μ receptor (Blake; Bot; Freeman; Reisine, 1997). Cross-tolerance caused by long term opioid abuse can also be an unintended effect and thus the patient must stay on methadone for a longer period of time (Paronis & Holtzman, 1992). A longer period of time in a methadone treatment program may result from cross tolerance because the patient must now start at a higher methadone dose which in turn will take longer to be tapered off of.

Methadone: Pharmacokinetics

Methadone is administered orally in a clinical setting. Once in the body, the absorption of methadone begins. Although it is typical for methadone to be taken in the form of a tablet, it can also be dispensed in the form of a solution. If in a solution it takes approximately 2 and a half hours for the methadone to reach its full concentration within the blood (Wolff et al., 1993). For tablet administration, it can take up to 3 hours to be fully absorbed into the individual’s blood and reach full concentration (Nilsson et al., 1982). Once methadone has been fully absorbed the drug’s effects are fulfilled and the analgesic effects fully take hold. Methadone activates analgesic effects by passing through the blood brain barrier and binding to various opioid receptors, more specifically, μ opioid receptors.

The distribution of methadone molecules, made up of a mixture of R-methadone and S-methadone, have been shown in rats to move into tissues such as the brain, gut, kidneys, liver, muscles and lungs (Gabrielsson, Johansso, Bondesson, Paalzow, 1985). Inturrisi and colleagues (1987) deduced that the approximate binding affinity of methadone to specific plasma proteins was 88%. These findings show that methadone naturally has a high efficacy to bind to plasma proteins and can thus be readily distributed throughout the body. Methadone is able to do this by binding to the α1 glycoprotein (AAG) (Romach; Piafsky; Khouw & Sellers, 1981). Olsen (1975) showed that AAG actively binds to blood plasma. It has also been shown that under stressful conditions, such as withdrawal, AAG levels will increase thus leading to a greater drug affect (Abramson, 1982). In order to administer methadone properly, a patient’s AAG levels should be monitored to ensure that the patient is not receiving a lower dosage than is needed. If the patient receives a lower dose of methadone they may have a continuation of their withdrawal symptoms. The patient is then more likely to relapse back into opioid abuse in order to alleviate said withdrawal symptoms.

The rate at which elimination of methadone occurs can be troublesome. Rate of eradication is of importance when trying to ensure that patients are not eliminating the drug within a short time period. Abolition of methadone is an obvious pharmacokinetic problem because once eliminated by the body, the drugs effects cease to exist. Methadone riddance has been shown to be dependent upon the pH of the patient’s urinary tract. If the patient has a pH above 6 then the elimination will be approximately 4%. However, if the pH of the patient’s urinary tract is below 6, the elimination percentage will be closer to 30% (Inturrisi; Colburn; Kaiko; Houde & Foley, 1987). The relatively quick rate of eradication of some individual’s methadone dosage will cause those patients to experience withdrawal like symptoms. Therefore, it is of vital importance to monitor the elimination and dosage of each patient prescribed methadone.

Relapse

            When studying the effectiveness of methadone an integral piece of the puzzle is what conditions cause relapse. Wikler (1973) observed that even after long periods of abstained opioid exposure, contact to drug conditioned cues could induce significant drug cravings and possible relapse to the drug. The molecular mechanisms behind this phenomenon still remain largely unclear. In a study conducted by Jafari and colleagues (2014), long-time heroin users treated with methadone were placed in an functional magnetic resonance imaging system (fMRI) while simultaneously shown visual cues pertaining to heroin, such as needles. Results showed that activation in the anterior cingulate cortex (ACC) had occurred while viewing the experimental drug cues (Jafari et al., 2014). The ACC has been shown to possibly have a role in the positive and negative associations with drug related stimuli (Walton, Croxson, Behrens, Kennerley & Rushworth, 2007). In Jafari’s 2014 study they also showed that methadone based therapy patients were observed to have activation in the cerebellum when shown heroin based visual stimuli. The cerebellum was shown to play a role in long term memories devoted towards drugs such as drug use and behaviors that occur during drug use (Miquel, Toledo, Garcia, Coria-Avila, Manzo, 2009). The visual cortex, specifically the lingual gyrus, was also shown to have a high level of activation during the display of heroin visual stimuli. This occurred more so in methadone based therapy patients than those whom were a part of the abstinence based program in the study. This can be explained because patients in methadone based treatments never learn to disassociate pleasurable feelings with heroin or its visual stimuli (Jafari et al., 2014). The lingual gyrus activation is significant because it correlates with enhanced visual attention being paid towards the stimulus, in this case the heroin related visual stimulus (Xiao, Lee, Zhang, Wu, Wu, Weng, Hu, 2006). The idea that visual heroin stimuli cause greater activation in patients who are in methadone based treatments may be a factor that leads to relapse to opiate abuse, as opposed to patients who are in abstinence based programs.

It has been shown that the extracellular matrix may play a more integral role in regulation of drug seeking while Oever and colleagues (2008) have shown that neurons in the medial prefrontal cortex (mPFC) and the nucleus accumbens (NAc) play a critical role in the drug seeking during a self-administration experiment with rats. Self-administration of heroin in rats results in protein changes specifically within several components of the extracellular matrix. It changes main components of perineuronal nets, which are located proximally to dendritic spines and synapses in the central nervous system (Oever et al., 2010). Perineuronal nets play an important role to synapses and spines because they work as neurotransmitter buffers, electrical insulation, as well as growth factor suppliers (Yamaguchi, 2000). Thus, without growth factor, the neurons will not make proper connections and function properly. Oever (2010) also showed that forced abstinence from heroin leads to a decrease in vital proteins to these perineuronal nets in Tnr, proteoglycan, and Bcan,(all extracellular matrix proteins) all of which are found at mPFC and NAc synapses. According to Oever (2008), the mPFC-NAc pathway has an essential role in defining drug-seeking actions. The aforementioned results lead to a suggestion that cessation of long-term heroin use is associated with the changes in the extra-cellular matrices in the mPFC-NAc pathway.

Long-term structural and neurobiological changes occur within various areas of the brain and can have lasting effects upon dopamine, the main reward neurotransmitter. Galynker and colleagues (2000) suggested that methadone withdrawal could lead to significant glucose metabolism in the anterior cingulate gyrus, which in turn contributes to the idea that long term neurobiological effects can occur with persistent use of opiates. Anterior cingulate gyrus activation has been shown to be correlated with the processing of emotional pain (Talbot, Marrett, Evans, Meyer, Bushnell, Duncan, 1991). Furthering the argument for neurobiological changes after long-term exposure to opiates is Shi and colleagues (2008), who discovered (using PET imaging) that dopamine transporter (DAT) availability was decreased in prolonged exposure to methadone within the striatum. More specifically they found that DAT uptake was reduced in the bilateral caudate and putamen and bilateral putamen vs. healthy controls. All of these findings would further imply that one would have unnaturally high levels of dopamine within the given synaptic areas (Shi et al., 2008). Mosner and colleagues (2006) help to explain the significance of Shi and colleagues (2008) findings. Mosner and colleagues (2006) found that DAT-/- mice showed stronger responses to morphine rewards. Further findings by Shi and colleagues, (2008) have shown that DAT uptake function decrease can lead to higher levels of anxiety, specifically when the DAT uptake function decrease is found in the bilateral caudate within methadone treatment patients. Higher levels of anxiety can thus lead to individuals seeking to relieve their anxiety and possibly reverting back to heroin abuse.

Tolerance to opioids may affect methadone maintenance treatment programs. Opioid tolerance is the effect that occurs when decreased therapeutic effect of the opioid drug or need for higher dose to maintain the same effect occurs. A patient could have an innate tolerance, which is a genetically determined sensitivity or lack of sensitivity to opioids (Collett, 1998). Other types of tolerance are acquired tolerance. Acquired tolerance is when the patient has pharmacodynamic, pharmacokinetic, and learned tolerance (conditioned tolerance/ environmental cues) effect based upon a previous history of opioid dependence or abuse (Collett, 1998). In order to treat someone successfully with methadone, a broader understanding of the patient must be achieved. Better treatment for the patient and understanding that patient’s specific addiction will aid in the prevention of relapse.

Preventing relapse into opioid use can be a difficult task, one that may hinge upon proper dosage of methadone. Originally it was thought that high quantities of methadone should be given (approximately 80-120 mg/daily) for a greater success rate (Dole and Nyswander, 1965). However by the 1970’s researchers and clinicians were using smaller doses, around 30 mg/daily (Maremmani, Nardini, Zolesi, Castrogiovanni, 1994). Maremmani and colleagues (1994) used urinanalysis to determine the success rate of methadone based treatment at various doses. The experiment consisted of three groups, a low dosage group (0-30mg/daily), a intermediate dosage group (30-60 mg/daily) and a high dosage group (> 60 mg/dialy). Results showed that patients with the highest dosage had the highest negative incidence rating for heroin upon urinanalysis (97.33%) (Table 1). The results showed that the most effective dosage was approximately 85 mg/daily. It was further determined that patients who chose a shorter term and more rapid tapering of methadone saw lower success rates than those patients that opted for a longer and gradual tapering of methadone (Table 2)(Maremmani, Nardini, Zolesi, Castrogiovanni, 1994). Garrido and Troconiz (2000) have since posed a different and in some way more intricate argument that dosage of methadone should be determined upon the rate at which methadone is metabolized. A possibility for future treatment is higher doses while measuring the rate a methadone metabolism. If methadone is metabolized at a rapid rate then it may be advisable to increase that individual’s dose, or vice-versa for the opposite scenario. Further research should investigate the field of temporal release of methadone. If methadone (at higher doses) could be released at a slower rate than it may be more effective at cessation of opiates. Another method that could be employed is the use of sublingual capsules that sustain methadone within the patient’s system. This method could be used to absolve the patient’s opiate withdrawal syndrome completely.

Conclusions

While methadone is a highly popular form of treatment in America with approximately 306 thousand patients in the United States in 2011 (SAMHSA, 2013), it remains still only a treatment and not a cure for opiate addition. Relapse back into heroin addiction is still a major problem and many studies have suggested that this is due to the neurobiological changes that an individual accrues over their long-term use of the substance (Shi et al., 2008). According to Garrido & Troconiz (2000), the overarching problem is the inability to fully understand the pharamco-dynamics/ kinetics; in order to stop opiate withdrawal syndrome from occurring and thus having many of the patients relapse back to heroin abuse. Further research should be done upon the methadone-based treatments in the fields of pharmaco-dynamics/ kinetics as well as the neurobiological effects of opiates in general.

A contradiction has occurred within the research. Jafari and colleagues (2014) provided evidence that activation in various anatomical structures within the brain are activated during displayed drug cues. These results seem to explain the opposite of what was found by New & Wong (2002) and also Garrido &Troconiz (2000). They found that as methadone is administered to individuals that have potentiated synaptic densities, these synaptic densities are reduced in a dose dependent fashion by the reduction of receptors at the described post-synaptic densities. The contradiction between high levels of brain activation and the molecular trafficking of receptors point to a research gap within the literature. This gap is vital to determining whether or not methadone should be prescribed more, less, or not at all. It could be that if the gap is filled with new evidence that there is other pharmaceutical products that would work better in the treatment of opioid addicts.

Methadone based treatments, while sometimes end in success, can at times end in relapse. The question of how to administer methadone and how much to administer at a given time to circumvent opioid withdrawal syndrome is one that is still being debated. As it stands now, many people are given similar amounts of methadone as to what they were self-administering the drug of abuse to start with. As time progresses they are weaned off methadone. However, the lower dosage may be eliminated too quickly and the individual may experience opioid withdrawal syndrome. If this occurs then the patient may be more likely to relapse to their opioid substance abuse. More research is needed in both pharmacodynamics and pharmacokinetics, not just in methadone based treatments, but a greater understanding of opioids in general would be advantageous to understanding how to treat their addictive properties.

References

Abramson, F. P. (1982). Methadone plasma protein binding: Alterations in cancer and displacement from alpha 1-acid glycoprotein. Clinical Pharmacology and Therapeutics, 32(5), 652-8. vi. doi:10.1038 /clpt.1982.217

Administration,Subastance Abuse and Mental Health Services. (2013). Trends in the use of methadone and buprenorphine at substance abuse treatment facilities : 2003 to 2011. The N-SSATS Report, , 1-5.

Benich, J. J. (2011). Opioid dependence. Primary Care, 38(1), 59-70, vi. doi:10.1016/j.pop.2010.11.005

Blake, A. D., Bot, G., Freeman, J. C., & Reisine, T. (1997). Differential opioid agonist regulation of the mouse   opioid receptor. Journal of Biological Chemistry, 272(2), 782-790. doi:10.1074/jbc.272.2.782

Bulka, A., Plesan, A., Xu, X., & Wiesenfeld-Hallin, Z. (2002). Reduced tolerance to the anti-hyperalgesic effect of methadone in comparison to morphine in a rat model of mononeuropathy. Pain, 95(1), 103-109. doi:10.1016/S0304-3959(01)00382-7

Crawford, M. W., Hickey, C., Zaarour, C., Howard, A., & Naser, B. (2006). Development of acute opioid tolerance during infusion of remifentanil for pediatric scoliosis surgery. Anesthesia and Analgesia, 102(6), 1662-1667. doi:10.1213/01.ane.0000216036.95705.c2

Collett, B. J. (1998). Opioid tolerance: The clinical perspective. British Journal of Anaesthesia, 81(1), 58-68

De Maeyer, J., Vanderplasschen, W., Camfield, L., Vanheule, S., Sabbe, B., & Broekaert, E. (2011). A good quality of life under the influence of methadone: A qualitative study among opiate-dependent individuals. International Journal of Nursing Studies, 48(10), 1244-57. doi:10.1016/j.ijnurstu.2011.03.009

Dole, VP., Nyswander, M., (1965). A Medical Treatment for Diacetylmorphine (Heroin) Addiction: A Clinical Trial With Methadone Hydrochloride. JAMA. 193(8), 646-650. doi:10.1001/jama.1965.03090080008002

Ebert, B., Andersen, S., & Krogsgaard-Larsen, P. (1995). Ketobemidone, methadone and pethidine are non-competitive N-methyl-D-aspartate (NMDA) antagonists in the rat cortex and spinal cord. Neuroscience Letters, 187(3), 165-8. doi:10.1016/0304-3940(95)11364-3

Elde, R., Haber, S., Ho, R., Holets, V., de Lanerolle, N., Maley, B., Seybold, V. (1980). Interspecies conservation and variation in peptidergic neurons. Peptides, 1, 21-26. doi:10.1016/0196-9781(80)90100-X

Gabrielsson, J. L., Johansson, P., Bondesson, U., & Paalzow, L. K. (1985). Analysis of methadone disposition in the pregnant rat by means of a physiological flow model. Journal of Pharmacokinetics and Biopharmaceutics, 13(4), 355-372. doi:10.1007/BF01061474

Galynker, I., Watras-Ganz, S., Miner, C., Rosenthal, R., Des Jarlais, D. C., Richman, B. L., & London, E. (2000). Cerebral metabolism in opiate-dependent subjects. The Mount Sinai Journal of Medicine¦, 67, 6-9. Pmid: 11064488

Garrido, M. J., & TrocÃniz, ,I.F. (2000). Methadone: A review of its pharmacokinetic/pharmacodynamic properties. Journal of Pharmacological and Toxicological Methods, 42(2), 61-6. pmid: 10924887

Gorman, A. L., Elliott, K. J., & Inturrisi, C. E. (1997). The d- and l- isomers of methadone bind to the non-competitive site on the N -methyl- d -aspartate ( NMDA ) receptor in rat forebrain and spinal cord. Neuroscience Letters, 223, 5-8. pmid: 9058409

Inturrisi, C. E., Colburn, W. a., Kaiko, R. F., Houde, R. W., & Foley, K. M. (1987). Pharmacokinetics and pharmacodynamics of methadone in patients with chronic pain. Clinical Pharmacology and Therapeutics, 41(4), 392-401. pmid: 3829576

Inturrisi, C. E. (1997). Preclinical evidence for a role of glutamatergic systems in opioid tolerance and dependence. Seminars in Neuroscience, 9(3-4), 110-119. doi:10.1006/smns.1997.0111

Ling, G. S., Spiegel, K., Lockhart, S. H., & Pasternak, G. W. (1985). Separation of opioid analgesia from respiratory depression evidence for different receptor mechanisms.pdf. The Journal of Pharmacology and Experimental Therapeutics, 232(1), 149-55. pmid: 2981312

Mao, J., Price, D. D., & Mayer, D. J. (1995). Mechanisms of hyperalgesia and morphine tolerance: A current view of their possible interactions. Pain, 62(3), 259-274.

Mao J., Sung B., Ji RR., Lim, G. (2002)a. Chronic morphine induces downregulation of spinal glutamate transporters: implication sin morphine tolerance and abnormal pain sensitivity. J Neurosci. (22), 8312–23.

Mao, J., Sung, B., Ji, R., & Lim, G. (2002)b. Neuronal apoptosis associated with morphine tolerance: Evidence for an opioid-induced neurotoxic mechanism. Journal of Neuroscience, 22(17), 7650-7661.

Maremmani, I., Nardini, R., Zolesi, O., & Castrogiovanni, P. (1994). Methadone dosages and therapeutic compliance during a methadone maintenance program. Drug and Alcohol Dependence, 34(2), 163-166. doi:10.1016/0376-8716(94)90138-4

Matthes, H. W., Maldonado, R., Simonin, F., Valverde, O., Slowe, S., Kitchen, I., Kieffer, B. L. (1996). Loss of morphine induced analgesia, reward effect and withdrawal symtpoms in mice lacking the mew receptor gene.pdf. Nature, 383(6603), 819-23. doi:10.1038/383819a0

Miquel, M., Toledo, R., García, L.,I., Coria-Avila, G., & Manzo, J. (2009). Why should we keep the cerebellum in mind when thinking about addiction? Current Drug Abuse Reviews, 2(1), 26-40. pmid: 19630735

Mössner, R., Simantov, R., Marx, A., Lesch, K. P., & Seif, I. (2006). Aberrant accumulation of serotonin in dopaminergic neurons. Neuroscience Letters, 401(1), 49-54. doi:10.1016/j.neulet.2006.02.081

National Institute on Drug Abuse. (2014) . Heroin Retrieved from http://www.drugabuse.gov/publications/drugfacts/heroin

New, D. C., & Wong, Y. H. (2002). The ORL1 receptor: Molecular pharmacology and signalling mechanisms. Neurosignals, 11(4), 197-212. doi:10.1159/000065432

Nilsson, M. I., Widerlöv, E., Meresaar, U., & Anggård, E. (1982). Effect of urinary pH on the disposition of methadone in man. European Journal of Clinical Pharmacology, 22(4), 337-42. pmid: 6286317

Olsen, G. D. (1975). Morphine binding to human plasma proteins. Clinical Pharamcology and Therapeutics. 17 (1), 31-5. pmid: 47279

Paronis, C. a., & Holtzman, S. G. (1992). Development of tolerance to the analgesic activity of mu agonists after continuous infusion of morphine, meperidine or fentanyl in rats. The Journal of Pharmacology and Experimental Therapeutics, 262(1), 1-9. pmid: 1625189

Pogozheva, I. D., Lomize, A. L., & Mosberg, H. I. (1998). Opioid receptor three-dimensional structures from distance geometry calculations with hydrogen bonding constraints. Biophysical Journal, 75(2), 612-634. doi:10.1016/S0006-3495(98)77552-6

Romach, M. K., Piafsky, K. M., & Abel, J. G. (1981). Methadone binding to orosomucoid (alpa_1 acid glycoprotein): Determinant of free fraction in plasma the. Clinical Pharmacology and Therapeutics¦, pmid: 7193106

Shi, J., Zhao, L., Copersino, M. L., Fang, Y., Chen, Y., Tian, J., . . . Lu, L. (2008). PET imaging of dopamine transporter and drug craving during methadone maintenance treatment and after prolonged abstinence in heroin users. European Journal of Pharmacology, 579(1-3), 160-6. doi:10.1016/j.ejphar.2007.09.042

Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. (April 23, 2013). Retrieved from http://www.samhsa.gov

Tabatabaei-Jafari, H., Ekhtiari, H., Ganjgahi, H., Hassani-Abharian, P., Oghabian, M., Moradi, A., Zarei, M. (2014). Patterns of brain activation during craving in heroin dependents successfully treated by methadone maintenance and abstinence-based treatments. Journal of Addiction Medicine, 8(2), 123-9. doi:10.1097/ADM.0000000000000022

Talbot, J. D., Marrett, S., Evans, A. C., Meyer, E., Bushnell, M. C., & Duncan, G. H. (1991). Multiple representations of pain in human cerebral cortex. Science, 251(4999), 1355-1358. doi:10.1126/science.2003220

Van den Oever, M.,C., Goriounova, N. a., Li, K. W., Van der Schors, R.,C., Binnekade, R., Schoffelmeer, A. N. M., . . . De Vries, T.,J. (2008). Prefrontal cortex AMPA receptor plasticity is crucial for cue-induced relapse to heroin-seeking. Nature Neuroscience, 11(9), 1053-8. doi:10.1038/nn.2165

Van den Oever, M.,C., Lubbers, B. R., Goriounova, N. a., Li, K. W., Van der Schors, R.,C., Loos, M., . . . Spijker, S. (2010). Extracellular matrix plasticity and GABAergic inhibition of prefrontal cortex pyramidal cells facilitates relapse to heroin seeking. Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology, 35(10), 2120-33. doi:10.1038/npp.2010.90

Vanderah, T. W., Ossipov, M. H., Lai, J., Malan, T. P., & Porreca, F. (2001). Mechanisms of opioid-induced pain and antinociceptive tolerance: Descending facilitation and spinal dynorphin. Netherlands: Elsevier B.V. doi:10.1016/S0304-3959(01)00311-6

Vinik, H. R., & Kissin, I. (1998). Rapid development of tolerance to analgesia during remifentanil infusion in humans. Anesthesia and Analgesia, 86(6), 1307-1311. doi:10.1097/00000539-199806000-00033

Walton, M. E., Croxson, P. L., Behrens, T. E. J., Kennerley, S. W., & Rushworth, M. F. S. (2007). Adaptive decision making and value in the anterior cingulate cortex. Neuroimage, 36 Suppl 2, T142-54. doi:10.1016/j.neuroimage.2007.03.029

Wiesenfeld-hallin, Z. (1998). Combined opioid-NMDA antagonist therapies. What Advantages do they offer for the control of pain syndromes Drugs., 55(1), 1-4. pmid: 9463786

Wikler, A. (1973). Dynamics of drug dependence: Implications of a conditioning theory for research and treatment. Archives of General Psychiatry, 28(5), 611-616. doi:10.1001/archpsyc.1973.01750350005001

Wolff, K., Hay, A., Raistrick, D., Calvert, R., & Feely, M. (1991). Measuring compliance in methadone maintenance patients: Use of a pharmacologic indicator to “estimate” methadone plasma levels. Clinical Pharmacology and Therapeutics, 50(2), 199-207.

Wolff, K., Hay, a. W., Raistrick, D., & Calvert, R. (1993). Steady-state pharmacokinetics of methadone in opioid addicts. European Journal of Clinical Pharmacology, 44(2), 189-94. pmid: 8453965

Xiao, Z., Lee, T., Zhang, J. X., Wu, Q., Wu, R., Weng, X., & Hu, X. (2006). Thirsty heroin addicts show different fMRI activations when exposed to water-related and drug-related cues. Drug and Alcohol Dependence, 83(2), 157-62. doi:10.1016/j.drugalcdep.2005.11.012

Yamaguchi, Y. (2000). Lecticans: Organizers of the brain extracellular matrix. Cellular and Molecular Life Sciences : CMLS, 57(2), 276-289. doi:10.1007/PL00000690

Screenshot 2014-11-23 12.17.12 Screenshot 2014-11-23 12.05.05

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s