Chinese Journal of Magnetic Resonance ›› 2021, Vol. 38 ›› Issue (3): 345-355.doi: 10.11938/cjmr20212890
• Articles • Previous Articles Next Articles
Ying-dan HU1,2,Yue CAI1,2,Xu-xia WANG1,2,Si-jie LIU1,2,Yan KANG1,2,Hao LEI1,2,Fu-chun LIN1,2,*(
)
Received:2021-02-23
Published:2021-09-05
Online:2021-03-31
Contact:
Fu-chun LIN
E-mail:fclin@wipm.ac.cn
CLC Number:
Ying-dan HU,Yue CAI,Xu-xia WANG,Si-jie LIU,Yan KANG,Hao LEI,Fu-chun LIN. Magnetic Resonance Imaging the Brain Structures Involved in Nicotine Susceptibility in Rats[J]. Chinese Journal of Magnetic Resonance, 2021, 38(3): 345-355.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
Fig.2
The effect of nicotine administration on the dependence score of rats. (a) The effect of nicotine administration and administration time on dependence score; (b) The effect of nicotine administration on the relative dependence score. The data are presented in the form of mean±standard deviation, *p < 0.000 1
Fig.3
The PrL GM volume of rats in the Nic group is significantly correlated with DD and DR. (a) The PrL_R of rats in the Nic group; (b) PrL_R GM volume of rats in the Nic group is significantly negatively correlated with DD (r=-0.768, p=0.000 8); (c) PrL_R GM volume of rats in the Nic group is significantly positively correlated with DR (r=0.787, p=0.000 5); (d) The PrL_L of rats in the Nic group; (e) PrL_L GM volume of rats in the Nic group is significantly negatively correlated with DD (r=-0.740, p=0.001 6); (f) PrL_L GM volume of rats in the Nic group is significantly positively correlated with DR (r=0.752, p=0.001 2)
Fig.4
The GI_L GM volume of rats in the Nic group is significantly correlated with DD and DR. (a) The GI_L of rats in the Nic group; (b) GI_L GM volume of rats in the Nic group is significantly negatively correlated with DD (r=-0.683, p=0.005); (c) GI_L GM volume of rats in the Nic group is significantly positively correlated with DR (r=0.699, p=0.003 8)
Fig.5
The CA1_R GM volume of rats in the Nic group is significantly correlated with DD and DR. (a) The CA1_R of rats in the Nic group; (b) CA1_R GM volume of rats in the Nic group is significantly positively correlated with DD (r = 0.735, p = 0.001 8); (c) CA1_R GM volume of rats in the Nic group is significantly negatively correlated with DR (r = -0.743, p = 0.001 5)
Fig.6
The Thalamus_L GM volume of rats in the Nic group is significantly correlated with DD and DR. (a) The Thalamus_L of rats in the Nic group; (b). Thalamus_L GM volume of rats in the Nic group is significantly positively correlated with DD (r=0.933, p < 0.000 1); (c) Thalamus_L GM volume of rats in the Nic group is significantly negatively correlated with DR (r=-0.882, p < 0.000 1)
Fig.7
The volume of white matter (WM) in the thalamus of rats in the Nic group was significantly correlated with DD and DR. (a) The Thalamus_R of rats in the Nic group; (b) Thalamus_R WM volume of rats in the Nic group is significantly negatively correlated with DD (r = -0.738, p=0.001 7); (c) Thalamus_R WM volume of rats in the Nic group is significantly positively correlated with DR (r=0.678, p=0.005 5); (d) The Thalamus_L of rats in the Nic group; (e) Thalamus_L WM volume of rats in the Nic group is significantly negatively correlated with DD (r = -0.705, p=0.003 3); (f) Thalamus_L WM volume of rats in the Nic group is significantly positively correlated with DR (r=0.646, p=0.009 2)
| 1 |
CHEN Z M , PETO R , ZHOU M G , et al. Contrasting male and female trends in tobacco-attributed mortality in China: evidence from successive nationwide prospective cohort studies[J]. The Lancet, 2015, 386 (10002): 1447- 1456.
doi: 10.1016/S0140-6736(15)00340-2 |
| 2 |
BRITTON J . Death, disease, and tobacco[J]. The Lancet, 2017, 389 (10082): 1861- 1862.
doi: 10.1016/S0140-6736(17)30867-X |
| 3 |
GARCIA-RIVAS V , DEROCHE-GAMONET V . Not all smokers appear to seek nicotine for the same reasons: implications for preclinical research in nicotine dependence[J]. Addic Biol, 2019, 24 (3): 317- 334.
doi: 10.1111/adb.12607 |
| 4 |
LIU M Z , JIANG Y , WEDOW R , et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use[J]. Nat Genet, 2019, 51 (2): 237- 244.
doi: 10.1038/s41588-018-0307-5 |
| 5 |
LI S F , YANG Y H , HOFFMANN E , et al. CYP2A6 genetic variation alters striatal-cingulate circuits, network hubs, and executive processing in smokers[J]. Biol Psychiat, 2017, 81 (7): 554- 563.
doi: 10.1016/j.biopsych.2016.09.013 |
| 6 |
HONG L E , HODGKINSON C A , YANG Y , et al. A genetically modulated, intrinsic cingulate circuit supports human nicotine addiction[J]. Proc Natl Acad Sci U S A, 2010, 107 (30): 13509- 13514.
doi: 10.1073/pnas.1004745107 |
| 7 |
HSU L M , KEELEY R J , LIANG X , et al. Intrinsic insular-frontal networks predict future nicotine dependence severity[J]. J Neurosci, 2019, 39 (25): 5028- 5037.
doi: 10.1523/JNEUROSCI.0140-19.2019 |
| 8 | CAI W Q , WANG Y J . Advances in construction of human brain atlases from magnetic resonance images[J]. Chinese J Magn Reson, 2020, 37 (2): 241- 253. |
| 蔡文琴, 王远军. 基于磁共振成像的人脑图谱构建方法研究进展[J]. 波谱学杂志, 2020, 37 (2): 241- 253. | |
| 9 |
ZHANG X , SALMERON B J , ROSS T J , et al. Factors underlying prefrontal and insula structural alterations in smokers[J]. Neuroimage, 2011, 54 (1): 42- 48.
doi: 10.1016/j.neuroimage.2010.08.008 |
| 10 |
FRITZ H C , WITTFELD K , SCHMIDT C O , et al. Current smoking and reduced gray matter volume-a voxel-based morphometry study[J]. Neuropsychopharmacol, 2014, 39 (11): 2594- 2600.
doi: 10.1038/npp.2014.112 |
| 11 |
LIAO Y H , TANG J S , LIU T Q , et al. Differences between smokers and non-smokers in regional gray matter volumes: a voxel-based morphometry study[J]. Addict Biol, 2012, 17 (6): 977- 980.
doi: 10.1111/j.1369-1600.2010.00250.x |
| 12 |
PAN P L , SHI H C , ZHONG J G , et al. Chronic smoking and brain gray matter changes: evidence from meta-analysis of voxel-based morphometry studies[J]. Neurol Sci, 2013, 34 (6): 813- 817.
doi: 10.1007/s10072-012-1256-x |
| 13 |
HANLON C A , OWENS M M , JOSEPH J E , et al. Lower subcortical gray matter volume in both younger smokers and established smokers relative to non-smokers[J]. Addict Biol, 2016, 21 (1): 185- 195.
doi: 10.1111/adb.12171 |
| 14 |
WANG K C , YANG J Y , ZHANG S Y , et al. The neural mechanisms underlying the acute effect of cigarette smoking on chronic smokers[J]. PLoS One, 2014, 9 (7): e102828.
doi: 10.1371/journal.pone.0102828 |
| 15 |
STOECKEL L E , CHAI X J , ZHANG J H , et al. Lower gray matter density and functional connectivity in the anterior insula in smokers compared with never smokers[J]. Addict Biol, 2016, 21 (4): 972- 981.
doi: 10.1111/adb.12262 |
| 16 |
BRYNILDSEN J K , NAJAR J , HSU L M , et al. A novel method to induce nicotine dependence by intermittent drug delivery using osmotic minipumps[J]. Pharmacology Biochemistry and Behavior, 2016, 142, 79- 84.
doi: 10.1016/j.pbb.2015.12.010 |
| 17 |
WU H , WANG X , GAO Y , et al. NMDA receptor antagonism by repetitive MK801 administration induces schizophrenia-like structural changes in the rat brain as revealed by voxel-based morphometry and diffusion tensor imaging[J]. Neuroscience, 2016, 322, 221- 233.
doi: 10.1016/j.neuroscience.2016.02.043 |
| 18 | XIN H T , WU G Y , WEN Z , et al. Effects of antiretroviral therapy on brain gray matter volumes in AIDS patients[J]. Chinese J Magn Reson, 2021, 38 (1): 69- 79. |
| 辛红涛, 吴光耀, 文之, 等. 抗逆转录病毒治疗对艾滋病患者脑灰质体积的影响[J]. 波谱学杂志, 2021, 38 (1): 69- 79. | |
| 19 |
HAYASHI T , KO J H , STRAFELLA A P , et al. Dorsolateral prefrontal and orbitofrontal cortex interactions during self-control of cigarette craving[J]. Proc Natl Acad Sci U S A, 2013, 110 (11): 4422- 4427.
doi: 10.1073/pnas.1212185110 |
| 20 |
LI Y D , YUAN K , CAI C X , et al. Reduced frontal cortical thickness and increased caudate volume within fronto-striatal circuits in young adult smokers[J]. Drug Alcohol Depen, 2015, 151, 211- 219.
doi: 10.1016/j.drugalcdep.2015.03.023 |
| 21 |
PICARD F , SADAGHIANI S , LEROY C , et al. High density of nicotinic receptors in the cingulo-insular network[J]. Neuroimage, 2013, 79, 42- 51.
doi: 10.1016/j.neuroimage.2013.04.074 |
| 22 |
NAQVI N H , RUDRAUF D , DAMASIO H , et al. Damage to the insula disrupts addiction to cigarette smoking[J]. Science, 2007, 315 (5811): 531- 534.
doi: 10.1126/science.1135926 |
| 23 |
MORALES A M , GHAHREMANI D , KOHNO M , et al. Cigarette exposure, dependence, and craving are related to insula thickness in young adult smokers[J]. Neuropsychopharmacol, 2014, 39 (8): 1816- 1822.
doi: 10.1038/npp.2014.48 |
| 24 | LIN F C , WU G Y , ZHU L , et al. Region-specific changes of insular cortical thickness in heavy smokers[J]. Front Hum Neurosci, 2019, 13, 265. |
| 25 |
TSAI P J , KEELEY R J , CARMACK S A , et al. Converging structural and functional evidence for a rat salience network[J]. Biol Psychiat, 2020, 88 (11): 867- 878.
doi: 10.1016/j.biopsych.2020.06.023 |
| 26 | KENNEY J W , GOULD T J . Modulation of hippocampus-dependent learning and synaptic plasticity by nicotine[J]. Mol Neurobiol, 2008, 38 (1): 101- 121. |
| 27 |
LIN F C , WU G Y , ZHU L , et al. Altered brain functional networks in heavy smokers[J]. Addict Biol, 2015, 20 (4): 809- 819.
doi: 10.1111/adb.12155 |
| 28 |
SHEN Z J , HUANG P Y , QIAN W , et al. Severity of dependence modulates smokers' functional connectivity in the reward circuit: a preliminary study[J]. Psychopharmacology, 2016, 233 (11): 2129- 2137.
doi: 10.1007/s00213-016-4262-5 |
| 29 | WANG L , NEGREIRA A , LAVIOLETTE P , et al. Intrinsic interhemispheric hippocampal functional connectivity predicts individual differences in memory performance ability[J]. Hippocampus, 2010, 20 (3): 345- 351. |
| 30 |
BRODY A L , MANDELKERN M A , LONDON E D , et al. Cigarette smoking saturates brain α4β2 nicotinic acetylcholine receptors[J]. Arch Gen Psychiat, 2006, 63 (8): 907- 914.
doi: 10.1001/archpsyc.63.8.907 |
| [1] | LI Na, XIAO Long, LI Sha, LIU Yudun, JIA Yushu, ZHANG Lei, CHEN Shizhen. 19F NMR Chemical Shift-encoded cRGD-targeted Dual-modal Probe for Multicolor Imaging [J]. Chinese Journal of Magnetic Resonance, 2026, 43(3): 279-290. |
| [2] | SU Yilin, LIU Yuanyuan, CUI Zhuoxu, LIANG Dong. Physics Guided Multi-contrast Magnetic Resonance Reconstruction Diffusion Model [J]. Chinese Journal of Magnetic Resonance, 2026, 43(3): 321-338. |
| [3] | CAI Yue, WANG Xuxia, LIU Sijie, GUO Haodong, CHEN Xi, CHENG Linlin, KANG Yan, LIN Fuchun. Magnetic Resonance Imaging Study on the Microstructure Abnormalities of Striatal White Matter in Type 2 Diabetic Mellitus Rats [J]. Chinese Journal of Magnetic Resonance, 2026, 43(2): 175-185. |
| [4] | FU Fenfang, LIN Guobing, LI Meifang. Advances in Magnetic Resonance Imaging for the Diagnosis and Prognosis of Mild Traumatic Brain Injury [J]. Chinese Journal of Magnetic Resonance, 2026, 43(2): 214-222. |
| [5] | NI Guangmao, LI Yuwei, HOU Wenxuan, LIU Caiyun, DONG Peng, ZHANG Yanhui. Research on the Influencing Factors of Acute Cerebral Infarction Recurrence Based on MR-DWI [J]. Chinese Journal of Magnetic Resonance, 2026, 43(1): 87-93. |
| [6] | CHEN Xi, LIU Sijie, CAI Yue, CHENG Linlin, WANG Xuxia, KANG Yan, LIN Fuchun, LEI Hao. Effects of Seizure-inducing Doses Nicotine on Hippocampal Structure in Adolescent Female Rats [J]. Chinese Journal of Magnetic Resonance, 2025, 42(4): 345-354. |
| [7] | LI Yinghao, WANG Lihui, WANG Sucheng, ZHU Zhongqi, HUANG Changdong, LI Renfeng, CAO Kaiming, HU Haiyang, JIA Yiming, LIANG Songtao, YANG Guang, LU Qing, WANG Hongzhi. Study on Pancreas Automatic Segmentation, Regional Quantification, and Diabetes Assessment [J]. Chinese Journal of Magnetic Resonance, 2025, 42(4): 378-389. |
| [8] | MA Yingxue, ZHAO Yanqiang, YANG Xiaodong, JIANG Bin, TAO Cheng. Opportunities and Challenges of High-field and Ultra-high-field Magnetic Resonance Imaging in China [J]. Chinese Journal of Magnetic Resonance, 2025, 42(3): 334-344. |
| [9] | SUI Meiju, ZHANG Lei, WANG Ruifang, LUO Yingying, LI Sha, QIU Maosong, XU Qiuyi, CHEN Daiqin, CHEN Shizhen, ZHOU Xin. MRI-traceable Nanoenzyme for Cascade Catalysis-enhanced Immunotherapy [J]. Chinese Journal of Magnetic Resonance, 2025, 42(3): 231-248. |
| [10] | CHEN Qun, YANG Zijian, CHENG Xinyi, JIA Siyi, DU Xiaoxia, WANG Mengxing. Application of Magnetic Resonance Imaging Technology in Pediatric Exercise Intervention Research [J]. Chinese Journal of Magnetic Resonance, 2025, 42(2): 195-204. |
| [11] | PANG Qifan, WANG Zhichao, WU Yupeng, LI Jianqi. The Impact of K-Space Filling Strategy on Fat Artifacts in APT Imaging Based on FLASH Sequence [J]. Chinese Journal of Magnetic Resonance, 2024, 41(4): 443-453. |
| [12] | XU Zhenshun, YUAN Xiaohan, HUANG Ziheng, SHAO Chengwei, WU Jie, BIAN Yun. Multi-source Feature Classification Model of Pancreatic Mucinous and Serous Cystic Neoplasms Based on Deep Learning [J]. Chinese Journal of Magnetic Resonance, 2024, 41(1): 19-29. |
| [13] | LIU Ying, LIN Ling, YUAN Binhua, ZHANG Haowei. Research Progress of MRI Gradient Waveform Generator [J]. Chinese Journal of Magnetic Resonance, 2024, 41(1): 99-115. |
| [14] | LI Pan,FANG Delei,ZHANG Junxia,MA Debei. Magnetic Resonance Compatibility Analysis Method of Surgical Robotic System Based on Image Quality Evaluation [J]. Chinese Journal of Magnetic Resonance, 2023, 40(1): 79-91. |
| [15] |
De-gang TANG,Hong-chuang LI,Xiao-ling LIU,Lei SHI,Hai-dong LI,Chao-hui YE,Xin ZHOU.
A Simulation Study on the Effect of the High Permittivity Materials Geometrical Structure on the Transmit Field |
| Viewed | ||||||
|
Full text |
|
|||||
|
Abstract |
|
|||||