ORIGINAL_ARTICLE
Navigating Life with Multiple Sclerosis from the Physical, Social, and Neurocognitive Standpoints
Multiple sclerosis (MS) is a life-long condition with a wide and varied range of symptoms which can have a profound impact on all aspects of a patient’s life including future plans, self-confidence, self-esteem, relationships, quality of life and employment prospects. Living with MS can certainly be difficult and frustrating. Over time, however, most people find ways to adapt and come to terms with many of the changes that MS can bring and do manage to live fairly full lives.
https://jamsat.sums.ac.ir/article_42481_8085ec0cc11f04e6df77c72670b2ddbb.pdf
2016-12-01
287
290
10.18869/nrip.jamsat.2.4.287
Multiple Sclerosis
Quality of life
Neurocognitive burden
Social burden
Mohammad
Nami
torabinami@sums.ac.ir
1
Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences
LEAD_AUTHOR
Costello K, Thrower BW, Giesser BS. Navigating life with Multiple Sclerosis. Oxford: Oxford University Press; 2015.
1
Lewis MN. Transformative learning in the Multiple Sclerosis (MS) Community; An ethnographic study examining how and in what ways transformative learning is realized and lived out among members of an MS community [PhD thesis]. Chicago: National Louis University; 2009.
2
Thomas SP, Pollio HR. Listening to patients: A phenomenological approach to nursing research and practice. Philadelphia: Springer Publishing Company; 2002.
3
Benito-Leon J, Manuel Morales J, Rivera-Navarro J, Mitchell AJ. A review about the impact of multiple sclerosis on health-related quality of life. Disability and Rehabilitation. 2003; 25(23):1291â303. doi: 10.1080/09638280310001608591
4
Glozman JM. Quality of life of caregivers. Neuropsychology Review. 2004; 14(4):183â96. doi: 10.1007/s11065-004-8158-5
5
Heidari M, Akbarfahimi M, Salehi M, Torabi-Nami M. Psychometric properties of the Persian version of the Fatigue Impact Scale (FIS-P) in patients with Multiple Sclerosis. Iranian Rehabilitation Journal. 2015; 13(3):32-8.
6
Mohr DC, Cox D. Multiple Sclerosis: Empirical literature for the clinical health psychologist. Journal of Clinical Psychology. 2001; 57(4):479â99. doi: 10.1002/jclp.1042
7
Strober LB, Arnett PA. An examination of four models predicting fatigue in multiple sclerosis. Archives of Clinical Neuropsychology. 2005; 20(5):631â46. doi: 10.1016/j.acn.2005.04.002
8
Phillips CJ. The cost of Multiple Sclerosis and the cost effectiveness of disease-modifying agents in its treatment. CNS Drugs. 2004; 18(9):561â74. doi: 10.2165/00023210-200418090-00002
9
ORIGINAL_ARTICLE
Simulating the Formation and Dynamics of the Implicit Attitude; a Social Cognition Study
The current study aimed to define some factors contributing to implicit attitude formation mainly in the social interaction context. An agent-based computer simulation of a society including autonomous agents and an attitude object was used to track the implicit attitude progress towards the object. The society could simulate the autonomic behaviors. We provided a complex adaptive system and observed an emergent phenomenon as the formation and dynamics of implicit attitude in the society. Our results suggested that population size and the number of high-impact individuals are important for the formation of implicit attitude in a society. Moreover, when the number of factors affecting agents’ relationships increases, the dynamics of society tended to unpredictability. Our experience showed that diverse autonomous components of a society with implemented simple rules lead to emergent and seemingly organized system behavior, and the pattern of behavior can be affected by communication and environmental stress. Our study attempted to offer some key implications since few theories within the cognitive psychology and sociology have been stated in precise and unambiguous terms.
https://jamsat.sums.ac.ir/article_42480_ec6fd6d249bff7ec54dc33efc4128fd4.pdf
2016-12-01
291
298
10.18869/nrip.jamsat.2.4.291
Implicit attitude formation
Social cognition simulation
Cognitive science
Mohsen
Oftadehal
1
AUTHOR
Babak
Mohammadi
2
AUTHOR
Kamal
Kharrazi
3
AUTHOR
Mohammad
Nami
torabinami@sums.ac.ir
4
Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences
LEAD_AUTHOR
Fazio RH. Accessible attitudes as tools for object appraisal: Their costs and benefits. Why we evaluate: Functions of attitudes. 2000; 1-36. doi: 10.4135/9781446263037
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Crano WD, Prislin R. Attitudes and attitude change. Newyork: Psychology Press; 2011.
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Fazio RH, Towles-Schwen T. The MODE model of attitude-behavior processes. In: Chaiken S, Trope Y, editors. Dual Process Theories in Social Psychology. New York: Guilford; 1999.
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Fazio RH, Ledbetter JE, Towles-Schwen T. On the costs of accessible attitudes: detecting that the attitude object has changed. Journal of personality and social psychology. 2000; 78(2):197-210. doi: 10.1037/0022-3514.78.2.197
7
Fazio RH. On the power and functionality of attitudes: The role of attitude. In: Pratkanis A, Breckler SJ, Greenwald AG, editors. Attitude Structure and Function. Hillsdale, N.J.: Erlbaum; 1989.
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Maio GR. The psychology of human values. Oxford: Psychology Press; 2016.
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10
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12
Fazio RH. Multiple processes by which attitudes guide behavior: The MODE model as an integrative framework. Advances in Experimental Social Psychology. 1990; 23:75-109. doi: 10.1016/s0065-2601(08)60318-4
13
Greenwald AG, McGhee DE, Schwartz JL. Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology. 1998; 74(6):1464-80. doi: 10.1037/0022-3514.74.6.1464
14
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15
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Zuckerman M. Broad or narrow affect scores for the multiple affect adjective check list? Comment on Hunsleyâs âdimensionality of the multiple affect adjective check list-revisedâ. Journal of Psychopathology and Behavioral Assessment. 1990; 12(1):93-7. doi:10.1007/BF00960456
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Olson MA, Fazio RH. Implicit acquisition and manifestation of clasically conditioned attitudes. Social Cognition. 2002; 20(2):89-104. doi: 10.1521/soco.20.2.89.20992
18
Baumeister RF, Vohs KD. Self regulation, ego depletion, and motivation. Social and Personality Psychology Compass. 2007; 1(1):115-28. doi: 10.1111/j.1751-9004.2007.00001.x
19
Betsch T, Plessner H, Schwieren C, Gütig R. I like it but I donât know why: A value-account approach to implicit attitude formation. Personality and Social Psychology Bulletin. 2001; 27(2):242-53. doi: 10.1177/0146167201272009
20
Fazio RH, Powell MC, Herr PM. Toward a process model of the attitudeâbehavior relation: Accessing oneâs attitude upon mere observation of the attitude object. Journal of Personality and Social Psychology. 1983; 44(4):723-735. doi: 10.1037//0022-3514.44.4.723
21
Gorman DM, Mezic J, Mezic I, Gruenewald PJ. Agent-based modeling of drinking behavior: A preliminary model and potential applications to theory and practice. American Journal of Public Health. 2006; 96(11):2055-60. doi: 10.2105/ajph.2005.063289
22
Penzar D, SrbljinoviÄ A. Dynamic modeling of ethnic conflicts. International Transactions in Operational Research. 2004; 11(1):63-76. doi: 10.1111/j.1475-3995.2004.t01-1-00439.x
23
Sellers WI, Hill RA, Logan B. An agent-based model of group decision making in baboons. Philosophical Transactions of the Royal Society B: Biological Sciences. 2007; 362(1485):1699-710. doi: 10.1098/rstb.2007.2064
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26
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27
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35
ORIGINAL_ARTICLE
An Investigation on the Utility and Reliability of Electroencephalogram Phase Signal Upon Interpreting Cognitive Responses in the Brain: A Critical Discussion
Within the neuroscience and computational neuroscience communities, applications such as evaluating different cognitive responses of the brain, brain-computer interface (BCI) systems and brain connectivity studies have increasingly been using EEG phase information during the past few decades. The utility of EEG phase can be directly linked to the neural propagation and synchronized firing of neuronal populations during different cognitive states of the brain. Nevertheless, it has previously been shown that phase of narrow-band (frequency specific) foreground EEG (desired) is prone to contain fake spikes and variations (unrelated to brain activity) in the presence of background spontaneous EEG and low SNRs of foreground EEG (the low-amplitude analytic signals or LAAS problem). Accordingly, extracting the instantaneous EEG phase sequence for further utilization upon interpreting the cognitive states of the brain using phase related quantities, such as instantaneous frequency, phase shift, phase resetting and phase locking value, is a very sensitive and rigorous process. In this study, a simple procedure is proposed to illustrate the effects of LAAS problem on the utility of EEG phase related quantities in aforementioned applications, also to investigate the reliability of interpretations of the brain’s cognitive states based on such quantities. Results show that, without a proper and effective solution strategy, such potential flaws lead to incorrect physiological and pathological interpretations.
https://jamsat.sums.ac.ir/article_42482_f01a4203bf812e69cbf7f32eabc6d64a.pdf
2016-12-01
299
312
10.18869/nrip.jamsat.2.4.299
Cognitive state
Electroencephalogram phase
EEG Phase Synchronization
EEG Phase Desynchronization
Cognitive neuroscience
Esmaeil
Seraj
e.seraj@cse.shirazu.ac.ir
1
Department of Computer Science and Engineering and Information Technology, School of Electrical and Computer Engineering, Shiraz University
LEAD_AUTHOR
Gray CM, Konig P, Engel AK, Singer W, et al. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature. 1989; 338(6213):334-337. doi: 10.1038/338334a0
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Marshall W. Statistical analysis of EEG phase shift events [PhD thesis]. Waterloo: University of Waterloo; 2014.
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Krusienski DJ, McFarland DJ, Wolpaw JR. Value of amplitude, phase, and coherence features for a sensorimotor rhythm-based brain-computer interface. Brain Research Bulletin. 2012; 87(1):130-134. doi: 10.1016/j.brainresbull.2011.09.019
3
He W, Wei P, Zhou Y, Wang L. Combination of amplitude and phase features under a uniform framework with EMD in EEG-based brain-computer interface. Paper presented at: The Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2012 Aug 28-1; San Diego, USA.
4
Townsend G, Feng Y. Using phase information to reveal the nature of event-related desynchronization. Biomedical Signal Processing and Control. 2008; 3(3):192-202. doi: 10.1016/j.bspc.2008.01.003
5
Razavipour F, Sameni R. A study of event related potential frequency domain coherency using multichannel electroencephalogram subspace analysis. Journal of Neuroscience Methods. 2015; 249:22-28. doi: 10.1016/j.jneumeth.2015.03.037
6
Picton TW, Dimitrijevic A, John MS, Van Roon P. The use of phase in the detection of auditory steady-state responses. Clinical Neurophysiology. 2001; 112(9):1698-1711. doi: 10.1016/s1388-2457(01)00608-3
7
De Tommaso M, Marinazzo D, Guido M, Libro G, Stramaglia S, Nitti L, et al. Visually evoked phase synchronization changes of alpha rhythm in migraine: Correlations with clinical features. International Journal of Psychophysiology. 2005; 57(3):203-210. doi: 10.1016/j.ijpsycho.2005.02.002
8
Sakkalis V. Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG. Computers in Biology and Medicine. 2011; 41(12):1110-1117. doi: 10.1016/j.compbiomed.2011.06.020
9
Friston KJ. Functional and effective connectivity: A review. Brain Connectivity. 2011; 1(1):13-36. doi: 10.1089/brain.2011.0008
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Gomez-Herrero G. Brain connectivity analysis with EEG [PhD thesis]. Tampere: Tampere University of Technology; 2010.
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Sauseng P. Brain oscillations: Phase-locked EEG alpha controls perception. Current Biology. 2012; 22(9):R306-R308. doi: 10.1016/j.cub.2012.03.029
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Fell J, Axmacher N. The role of phase synchronization in memory processes. Nature reviews neuroscience. 2011; 12(2):105-118. doi: 10.1038/nrn2979
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Siegel M, Warden MR, Miller EK. Phase-dependent neuronal coding of objects in short-term memory. Proceedings of the National Academy of Sciences. 2009; 106(50):21341-21346. doi: 10.1073/pnas.0908193106
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Thatcher RW, North DM, Biver CJ. Development of cortical connections as measured by EEG coherence and phase delays. Human Brain Mapping. 2008; 29(12):1400-1415. doi: 10.1002/hbm.20474
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Thatcher RW, North D, Biver C. Intelligence and EEG phase reset: A two compartmental model of phase shift and lock. NeuroImage. 2008; 42(4):1639-1653. doi: 10.1016/j.neuroimage.2008.06.009
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58
ORIGINAL_ARTICLE
A Computational Visual Neuroscience Model for Object Recognition
In this study with the inspirations from both neuroscience and computer science, a combinatorial framework for object recognition was proposed having benefited from the advantages of both biologically-inspired HMAX_S architecture model for feature extraction and Extreme Learning Machine (ELM) as a classifier. HMAX model is a feed-forward hierarchical structure resembling the ventral pathway in the visual cortex of the brain and ELM is a powerful neural network, which randomly chooses hidden nodes and specifies analytically the single-hidden layer. ELM theories conjecture that this randomness may be true for biological learning in animal brains. It should be noted that the principle reason of using ELM is mainly as a result of its biological structure in order to imitate the biological object recognition system of mammalians and partly for its incredible speed which drastically lessens the runtime. Classification results are reported in Caltech101 dataset, at the focal point with its combinatorial framework serving considerable improvements over latest studies in both classification rate (96.39%) and the low runtime (0.417s).
https://jamsat.sums.ac.ir/article_42484_0360ceea81c99adabce6a8c7fc78d95d.pdf
2016-12-01
313
320
10.18869/nrip.jamsat.2.4.313
Cortex-like model
Biological object recognition
Biologically inspired neural network
HMAX
ELM
Sahar
Seifzadeh
seifzadeh.sahar5@yahoo.com
1
Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
LEAD_AUTHOR
Mohammad
Rezaei
mohammad.rezaei@kums.ac.ir
2
AUTHOR
Omid
Farahbakhsh
ai.farahbakhsh@yahoo.com
3
AUTHOR
Hubel DH, Wiesel TN. Receptive fields, binocular interaction and functional architecture in the catâs visual cortex. Journal of Physiology. 1962; 160(1):106-54. doi: 10.1113/jphysiol.1962.sp006837
1
Riesenhuber M, Poggio T. Hierarchical models of object recognition in cortex. Nature Neuroscience. 1999; 2(11):1019â25. doi: 10.1038/14819
2
Serre T, Wolf L, Bileschi S, Riesenhuber M, Poggio T. Robust object recognition with cortex-like mechanisms. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2007; 29(3):411â26. doi: 10.1109/tpami.2007.56
3
Mutch J, Lowe DG. Object class recognition and localization using sparse features with limited receptive fields. International Journal of Computer Vision. 2008; 80(1):45â57. doi: 10.1007/s11263-007-0118-0
4
Lee YJ, Tsai CY, Chen LG. A cortex-like model for rapid object recognition using feature-selective hashing. Paper presented at: The 2011 International Joint Conference; 2011 31 Jul - 5 Aug; San Jose, CA, USA.
5
Seifzadeh S, Faez K. A cortex-like model for animal recognition based on texture using feature-selective hashing. Paper presented at: The 2014 Iranian Conference on Intelligent Systems (ICIS); 2014 Feb 4-6; Bam, Iran.
6
Theriault C, Thome N, Cord M. Extended Coding and Pooling in the HMAX Model. IEEE Transactions on Image Processing. 2013; 22(2):764â77. doi: 10.1109/tip.2012.2222900
7
Huang GB. An insight into extreme learning machines: random neurons, random features and kernels. Cognitive Computation. 2014; 6(3):376â90. doi: 10.1007/s12559-014-9255-2
8
Lee H, Grosse R, Ranganath R, Ng AY. Convolutional deep belief networks for scalable unsupervised learning of hier
9
ORIGINAL_ARTICLE
A Hypothetical Animal Model for Psychosis Based on the Silencing of GABAergic System
Although many studies have highlighted the role of gamma-aminobutyric acid (GABA) in the pathophysiology of psychosis, there is no drug-induced animal model in which GABA is manipulated. In this article we propose a hypothetical animal model for psychosis based on the silencing GABAergic system. The presentation also suggest Pre-Pulse Inhibition test as a preferred approach towards proving this hypothesis.
https://jamsat.sums.ac.ir/article_42479_a8d3dc48d8b9de8917cb54c894aef704.pdf
2016-12-01
321
322
10.18869/nrip.jamsat.2.4.321
Psychosis
GABA
Animal model
Reza
Dehghani
reza_dehghani_dvm@yahoo.com
1
Department of Pharmacology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
AUTHOR
Ali
Shahbazi
shahbazial@yahoo.com
2
Department of Neuroscience, faculty of Advance Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
LEAD_AUTHOR
Gelder, Michael G, Richard Mayou, John Geddes. Psychiatry. New York: Oxford University Press; 2005.
1
Marcotte ER, Pearson DM, Srivastava LK. Animal models of schizophrenia: A critical review. Journal of Psychiatry Neuroscience. 2001; 26(5):395-410. PMID: 11762207
2
Kapur S, Mizrahi R, Li M. From dopamine to salience to psychosis--linking biology, pharmacology and phenomenology of psychosis. Schizophrenia Research. 2005; 79(1):59-68. doi: 10.1016/j.schres.2005.01.003
3
Howes OD, Egerton A, Allan V, McGuire P, Stokes P, Kapur S. Mechanisms underlying psychosis and antipsychotic treatment response in schizophrenia: insights from PET and SPECT imaging. Current Pharmaceutical Design. 2009; 15(22):2550-9. doi: 10.2174/138161209788957528
4
Riederer P, Lange KW, Kornhuber J, Danielczyk W. Glutamatergic-dopaminergic balance in the brain. Its importance in motor disorders and schizophrenia. Arzneimittelforschung. 1992; 42(2A):265-8. doi: PMID: 1350197
5
Halberstadt AL. The Phencyclidine-glutamate model of schizophrenia.Clinical Neuropharmacology. 1995; 18(3):237-49. doi: 10.1097/00002826-199506000-00004
6
Kang JI, Park HJ, Kim SJ, Kim KR, Lee SY, Lee E, et al. Reduced binding potential of GABA-A/benzodiazepine receptors in individuals at ultra-high risk for psychosis: An [18F]-fluoroflumazenil positron emission tomography study. Schizophrenia Bulletin. 2014; 40(3):548-57. doi: 10.1093/schbul/sbt052
7
Guidotti A, Auta J, Davis JM, Dong E, Grayson DR, Veldic M, et al. GABAergic dysfunction in schizophrenia: New treatment strategies on the horizon. Psychopharmacology. 2005; 180(2):191-205. doi: 10.1007/s00213-005-2212-8
8
Costa E, Davis JM, Dong E, Grayson DR, Guidotti A, Tremolizzo L, et al. A GABAergic cortical deficit dominates schizophrenia pathophysiology. Critical Reviews in Neurobiology. 2004; 16(1-2):1-23. doi: PMID: 15581395
9
Wieronska JM, Kusek M, Tokarski K, Wabno J, Froestl W, Pilc A. The GABA B receptor agonist CGP44532 and the positive modulator GS39783 reverse some behavioural changes related to positive syndromes of psychosis in mice. British Journal of Pharmacology. 2011; 163(5):1034-47. doi: 10.1111/j.1476-5381.2011.01301.x
10
Lavielle S, Tassin JP, Thierry AM, Blanc G, Herve D, Barthelemy C, et al. Blockade by benzodiazepines of the selective high increase in dopamine turnover induced by stress in mesocortical dopaminergic neurons of the rat. Brain Research. 1979;168(3):585-94. doi: 10.1016/0006-8993(79)90311-1
11
Fadda P, Scherma M, Fresu A, Collu M, Fratta W. Baclofen antagonizes nicotine-, cocaine-, and morphine-induced dopamine release in the nucleus accumbens of rat. Synapse 2003; 50(1):1-6. doi: 10.1002/syn.10238
12
Kurup RK, Kurup PA. Endogenous strychnine: description of hypoand hyperstrychninergic state in relation to neuropsychiatric diseases. International Journal of Neuroscience 2002; 2(10):1229â41. doi: 10.1080/00207450290026175
13
Garbutt JC, van Kammen DP. The interaction between GABA and dopamine: Implications for schizophrenia. Schizophrenia bulletin. 1983; 9(3):336-53. doi: 10.1093/schbul/9.3.336
14
Geyer MA, Moghaddam B. Animal models relevant to schizophrenia disorders. In: Davis KL, Charney D, Coyle JT, Nemeroff Ch, editors. Neuropsychopharmacology: The fifth generation of progress. Philadelphia: Lippincott Williams & Wilkins; 2002.
15
Watanabe M, Maemura K, Kanbara K, Tamayama T, Hayasaki H. GABA and GABA receptors in the central nervous system and other organs. A Survey of Cell Biology. 2002; 213:1-47. doi: 10.1016/s0074-7696(02)13011-7
16
Mena A, Ruiz-Salas JC, Puentes A, Dorado I, Ruiz-Veguilla M, De la Casa LG. Reduced prepulse inhibition as a biomarker of schizophrenia. Frontiers in Behavioral Neuroscience. 2016; 10:202. doi: 10.3389/fnbeh.2016.00202
17
ORIGINAL_ARTICLE
A Paradigm Shift in Glioblastoma Treatment and Research: A Multi-mechanistic, Multi-agent Approach to Target Glioblastoma Multiforme
The majority of patients with glioblastoma multiforme (GBM) suffer dismal outcomes. Adopting a broader, multi-mechanistic, multi-agent approach targeting GBM using readily available and fairly benign agents in combination with standard therapy may improve outcomes. Such agents include fluoxetine, fenofibrate, cimetidine, citrulline, valacyclovir, 1,3 1-6 beta glucan, and tadalafil, among others. In the context of in vitro and animal studies, these agents appear to target GBM cells and modify the tumor microenvironment. The current approach to GBM treatment focuses on limited molecular attributes of the condition. The following article highlights the relevance of the aforementioned agents in GBM treatment and proposes a multi-mechanistic, multi-agent paradigm shift, addressing a broader range of molecular attributes in the quest to improve patient outcomes.
https://jamsat.sums.ac.ir/article_42483_1ebb955a63ee234c2945b88f59071ef3.pdf
2016-12-01
323
326
10.18869/nrip.jamsat.2.4.323
Fluoxetine
Fenofibrate
Cimetidine
Citrulline
Valacyclovir
Tadalafil
Glioblastoma multiforme
John
Berg
johnandrewbergmd@yahoo.com
1
LEAD_AUTHOR
Liu KH, Yang ST, Lin JW, Lee YH, Wang JY, Hu CJ, et al. Fluoxetine, an antidepressant, suppresses glioblastoma by evoking AMPAR-mediated calcium-dependent apoptosis. Oncotarget. 2015; 6(7):5088-101. doi: 10.18632/oncotarget.3243
1
Song T, Li H, Tian Z, Xu C, Liu J, Guo Y. Disruption of NF-kB signaling by fluoxetine attentuates MGMT expression in glioma cells. Journal of OncoTargets and Therapy. 2015; 8:2199-2208. doi: 10.2147/ott.s85948
2
Han D, Wei W, Chen X, Zhang Y, Wang Y, Zhang J, et al. NF-kB/RelA-PKM2 mediates inhibition of glycolysis by fenofibrate in gliobastoma cells. Oncotarget. 2015; 6(28):26119-26128. doi: 10.18632/oncotarget.4444
3
Wilk A, Wyczechowska D, Zapata A, Dean M, Mullinax J, Marrero L, et al. Molecular mecanisms of fenobrate-induced metabolic catastrophe and glioblastoma cell death. Molecular and Cellular Biology. 2014; 35(1):182-198. doi: 10.1128/mcb.00562-14
4
Grabacka MM, Wilk A, Antonczyk A, Banks P, Walczyk-Tytko E, Dean M, et al. Fenofibrate induces ketone body production in melanoma and glioblastoma cells. Front Endocrinol (Lausanne). 2016; 7:5. doi: 10.3389/fendo.2016.00005
5
Pantsiarka P, Bouche G, Meheus L, Sukhatme V, Sukhatme VP. Repurposing drugs in oncology (ReDO)-cimetidine as an anti-cancer agent. Ecancermedicalscience. 2014; 8(2):485. doi: 10.3332/ecancer.2016.680
6
Zheng Y, Xu M, Li X, Jia J, Fan K, Lai G. Cimetidine suppresses lung tumor growth in mice through proapoptosis of myeloid-derived suppressor cells. Molecular Immunology. 2013; 54(1):7483. doi: 10.1016/j.molimm.2012.10.035
7
Lefranc F, James S, Camby I, Gaussin JF, Darro F, Brotchi J, et al. Combined cimetidine and temozolomide, compared with temozolomide alone: significant increases in survival in nude mice bearing U373 human glioblastoma multiforme orthotopic xenografts. Journal of Neurosurgery. 2005; 102(4):706-14. doi: 10.3171/jns.2005.102.4.0706
8
Li B, Cao F, Zhu Q, Li B, Gan M, Wang D. Perioperative cimetidine administration improves systematic immune response and tumor infiltrating lymphocytes in patients with colorectal cancer. Hepatogastroenterology. 2013; 60(122):244-7. doi: 10.5754/hge12573
9
Srivastava MK, Sinha P, Clements VK, Rodriguez P, Ostrand-Rosenberg S. Myeloid-derived suppressor cells inhibit T cell activation by depleting cystine and cysteine. Cancer Res. 2009; 70(1):68-77. doi: 10.1158/0008-5472.can-09-2587
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Sevko A, Umansky V Myeloid-derived suppressor cells interact with tumors in terms of myelopoiesis, tumorigenesis and immunosuppression: thick as thieves. Journal of Cancer. 2013; 4(1):3-11. doi: 10.7150/jca.5047
11
Bansal V, Rodriguez P, Wu G, Eichler DC, Zabaleta J, Taheri F. Citrulline can preserve proliferation and prevent the loss of CD3 zeta chain under conditions of low arginine. Journal of Parenteral and Enteral Nutrition. 2004; 28(6):423-430. doi: 10.1177/0148607104028006423
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Wainwright W, Chang AL, Dey M, Balyasnikova, IV, Kwon Kim C, Tobias A, et al. Durable therapeutic efficacy utilizing combinational blockade against IDO, CTLA-4 and PD-L1 in mice with brain tumors. Clinical Cancer Research. 2014; 20(20):5290-5301. doi: 1078-0432.ccr-14-0514
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Weed DT, Vella JL, Reis IM, De la fuente AC, Gomez C, Sargi Z, et al. Tadalafil reduces myeloid-deived supressor cells and regulatory T cells and promotes tumor immunity in patients with head ad neck squamous cell carcinoma. Clinical Cancer Research. 2014; 21(1):39-48. doi: 10.1158/1078-0432.ccr-14-1711
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Serafini P, Meckel K, Kelso M, Noonan K, Califano J, Koch W, et al. Phosphodiesterase-5 inhibition augments endogenous antitumor immunity by reducing myeloid-derived suppressor cell function. Journal of Experimental Medicine. 2006; 203(12):2691-702. doi: 10.1084/jem.20061104
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De Haas N, De Koning C, Spilgies L, De Vries IJM, Hato SV Improving cancer immunotherapy by targeting the STATe of MDSCs. Oncoimmunology. 2016; 5(7):1196312. doi: 10.1080/2162402x.2016.1196312
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Soderlund J, Erhardt S, Kast RE. Acyclovir inhibition of IDO to decrease Tregs as a glioblastoma treatment adjunct. Journal of Neuroinflammation. 2010; 7:44. doi: 10.1186/1742-2094-7-44
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18
Ong S-Y, Truong H-T-T, Diong CP, Linn Y-C, Yew-Leng Ho A, Goh Y-T, et al. Use of valacyclovir for the treatment of cytomegalovirus antigenemia after hematopoietic stem cell transplantation. BMC Hematology. 2015; 15:8. doi: 10.1186/s12878-015-0028-2
19
Tian J, Ma J, Ma K, Guo H, Baidoo SE, Zhang Y, et al. Beta-glucan enhances antitumor immune responses by regulating differentiation and function of monocytic myeloid-derived suppressor cells. European Journal of Immunology. 2013; 43(5):1220-1230. doi: 10.1002/eji.201242841
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Hong F, Hansen RD, Yan J, Allendorf DJ, Baran JT, Ostroff GR, et al. Beta-glucan functions as an adjuvant for monoclonal antibody immunotherapy by recruiting tumoricidal granulocytes as killer cells. Cancer Research. 2003; 63(24):9023-9031. PMID: 14695221
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Hong F, Yan J, Baran JT, Allendorf DJ, Hansen RD, Ostroff GR, et al. Mechanism by which orally administered beta-1,3-glucans enhance the tumoricidal activity of antitumor monoconal antibodies in murine tumor models. Journal of Immunology. 2004; 173(2):797-806. doi: PMID: 15240666
22
Soderlund J, Erhardt S, Kast RE. Acyclovir inhibition of IDO to decrease Tregs as a glioblastoma treatment adjunct. Journal of Neuroinflammation. 2010; 7(1):44. doi: 10.1186/1742-2094-7-44
23
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24
Triscott J, Lee C, Hu K, Fotovati A, Berns R, Pambid M, et al. Disulfiram, a drug used widely to control alcoholism, suppresses self-renewal of glioblastoma and overrides resistance to temozolomide. Oncotarget. 2012; 3(10):1112-1123. doi: 10.18632/oncotarget.604
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