Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Arc controls alcohol cue relapse by a central amygdala mechanism

A Correction to this article was published on 05 December 2022

This article has been updated

Abstract

Alcohol use disorder (AUD) is a chronic and fatal disease. The main impediment of the AUD therapy is a high probability of relapse to alcohol abuse even after prolonged abstinence. The molecular mechanisms of cue-induced relapse are not well established, despite the fact that they may offer new targets for the treatment of AUD. Using a comprehensive animal model of AUD, virally-mediated and amygdala-targeted genetic manipulations by CRISPR/Cas9 technology and ex vivo electrophysiology, we identify a mechanism that selectively controls cue-induced alcohol relapse and AUD symptom severity. This mechanism is based on activity-regulated cytoskeleton-associated protein (Arc)/ARG3.1-dependent plasticity of the amygdala synapses. In humans, we identified single nucleotide polymorphisms in the ARC gene and their methylation predicting not only amygdala size, but also frequency of alcohol use, even at the onset of regular consumption. Targeting Arc during alcohol cue exposure may thus be a selective new mechanism for relapse prevention.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: AUD-related behaviors in ArcKO mice.
Fig. 2: Arc protein is upregulated in the CeA during cue relapse.
Fig. 3: Alcohol consumption decreases Arc gene methylation and increases Arc mRNA expression in the mouse amygdala.
Fig. 4: Downregulation of Arc in CeM increases motivation and alcohol seeking during relapse induced by alcohol-predicting cues.
Fig. 5: Arc regulates synaptic strength of BLA → CeM pathway during cue relapse.
Fig. 6: Alcohol consumption affects ARC gene methylation.

Similar content being viewed by others

Change history

References

  1. American Psychiatric Association, American Psychiatric Association, editors. Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Washington, D.C: American Psychiatric Association; 2013.

  2. Carvalho AF, Heilig M, Perez A, Probst C, Rehm J. Alcohol use disorders. Lancet. 2019;394:781–92.

    Article  Google Scholar 

  3. Sinha R. How does stress lead to risk of alcohol relapse? Alcohol Res. 2012;34:432–40.

    Google Scholar 

  4. Sinha R, Li CSR. Imaging stress- and cue-induced drug and alcohol craving: association with relapse and clinical implications. Drug Alcohol Rev. 2007;26:25–31.

    Article  Google Scholar 

  5. Venniro M, Caprioli D, Shaham Y Animal models of drug relapse and craving. Progress in Brain Research, vol. 224, Elsevier; 2016. p. 25–52.

  6. Mantsch JR, Baker DA, Funk D, Lê AD, Shaham Y. Stress-induced reinstatement of drug seeking: 20 years of progress. Neuropsychopharmacology. 2016;41:335–56.

    Article  CAS  Google Scholar 

  7. Crombag HS, Bossert JM, Koya E, Shaham Y. Context-induced relapse to drug seeking: a review. Philos Trans R Soc Lond B Biol Sci. 2008;363:3233–43.

    Article  Google Scholar 

  8. Ray LA, Roche DJO. Neurobiology of craving: current findings and new directions. Curr Addict Rep. 2018;5:102–9.

    Article  Google Scholar 

  9. Ron D, Barak S. Molecular mechanisms underlying alcohol-drinking behaviours. Nat Rev Neurosci. 2016;17:576–91.

    Article  CAS  Google Scholar 

  10. Stefaniuk M, Beroun A, Lebitko T, Markina O, Leski S, Meyza K, et al. Matrix Metalloproteinase-9 and synaptic plasticity in the central amygdala in control of alcohol-seeking behavior. Biol Psychiatry. 2017;81:907–17.

    Article  CAS  Google Scholar 

  11. Warlow SM, Robinson MJF, Berridge KC. Optogenetic central amygdala stimulation intensifies and narrows motivation for cocaine. J Neurosci. 2017;37:8330–48.

    Article  CAS  Google Scholar 

  12. Warlow SM, Naffziger EE, Berridge KC. The central amygdala recruits mesocorticolimbic circuitry for pursuit of reward or pain. Nat Commun. 2020;11:2716.

    Article  CAS  Google Scholar 

  13. Douglass AM, Kucukdereli H, Ponserre M, Markovic M, Gründemann J, Strobel C, et al. Central amygdala circuits modulate food consumption through a positive-valence mechanism. Nat Neurosci. 2017;20:1384–94.

    Article  CAS  Google Scholar 

  14. Robinson MJF, Warlow SM, Berridge KC. Optogenetic excitation of central amygdala amplifies and narrows incentive motivation to pursue one reward above another. J Neurosci. 2014;34:16567–80.

    Article  CAS  Google Scholar 

  15. Radwanska K, Wrobel E, Korkosz A, Rogowski A, Kostowski W, Bienkowski P, et al. Alcohol relapse induced by discrete cues activates components of AP-1 transcription factor and ERK pathway in the rat basolateral and central amygdala. Neuropsychopharmacology. 2008;33:1835–46.

  16. Li X, Zeric T, Kambhampati S, Bossert JM, Shaham Y. The central amygdala nucleus is critical for incubation of methamphetamine craving. Neuropsychopharmacology. 2015;40:1297–306.

    Article  CAS  Google Scholar 

  17. Kruzich PJ, See RE. Differential contributions of the basolateral and central amygdala in the acquisition and expression of conditioned relapse to cocaine-seeking behavior. J Neurosci. 2001;21:RC155.

    Article  CAS  Google Scholar 

  18. Lu L, Hope BT, Dempsey J, Liu SY, Bossert JM, Shaham Y. Central amygdala ERK signaling pathway is critical to incubation of cocaine craving. Nat Neurosci. 2005;8:212–9.

    Article  CAS  Google Scholar 

  19. Knapska E, Radwanska K, Werka T, Kaczmarek L. Functional internal complexity of amygdala: focus on gene activity mapping after behavioral training and drugs of abuse. Physiol Rev. 2007;87:1113–73.

    Article  CAS  Google Scholar 

  20. Shepherd JD, Bear MF. New views of Arc, a master regulator of synaptic plasticity. Nat Neurosci. 2011;14:279–84.

    Article  CAS  Google Scholar 

  21. Nikolaienko O, Patil S, Eriksen MS, Bramham CR. Arc protein: a flexible hub for synaptic plasticity and cognition. Semin Cell Dev Biol. 2018;77:33–42.

    Article  CAS  Google Scholar 

  22. Plath N, Ohana O, Dammermann B, Errington ML, Schmitz D, Gross C, et al. Arc/Arg3.1 is essential for the consolidation of synaptic plasticity and memories. Neuron. 2006;52:437–44.

    Article  CAS  Google Scholar 

  23. Shepherd JD, Rumbaugh G, Wu J, Chowdhury S, Plath N, Kuhl D, et al. Arc/Arg3.1 mediates homeostatic synaptic scaling of AMPA receptors. Neuron. 2006;52:475–84.

    Article  CAS  Google Scholar 

  24. Chowdhury S, Shepherd JD, Okuno H, Lyford G, Petralia RS, Plath N, et al. Arc interacts with the endocytic machinery to regulate AMPA receptor trafficking. Neuron. 2006;52:445–59.

    Article  CAS  Google Scholar 

  25. Nielsen LD, Pedersen CP, Erlendsson S, Teilum K. The Capsid domain of Arc changes its oligomerization propensity through direct interaction with the NMDA receptor. Structure. 2019;27:1071–81.e5.

    Article  CAS  Google Scholar 

  26. Alasmari F, Goodwani S, McCullumsmith RE, Sari Y. Role of glutamatergic system and mesocorticolimbic circuits in alcohol dependence. Prog Neurobiol. 2018;171:32–49.

    Article  CAS  Google Scholar 

  27. Meyers JL, Salling MC, Almli LM, Ratanatharathorn A, Uddin M, Galea S, et al. Frequency of alcohol consumption in humans; the role of metabotropic glutamate receptors and downstream signaling pathways. Transl Psychiatry. 2015;5:e586.

    Article  CAS  Google Scholar 

  28. Rao PSS, Bell RL, Engleman EA, Sari Y. Targeting glutamate uptake to treat alcohol use disorders. Front Neurosci. 2015;9:144.

    Article  CAS  Google Scholar 

  29. Eisenhardt M, Leixner S, Luján R, Spanagel R, Bilbao A. Glutamate receptors within the mesolimbic dopamine system mediate alcohol relapse behavior. J Neurosci. 2015;35:15523–38.

    Article  CAS  Google Scholar 

  30. Radwanska K, Kaczmarek L. Characterization of an alcohol addiction-prone phenotype in mice: Characterization of an alcohol addiction-prone phenotype. Addict Biol. 2012;17:601–12.

    Article  CAS  Google Scholar 

  31. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. 2013;339:819–23.

    Article  CAS  Google Scholar 

  32. Schumann G, Loth E, Banaschewski T, Barbot A, Barker G, Büchel C, et al. The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology. Mol Psychiatry. 2010;15:1128–39.

    Article  CAS  Google Scholar 

  33. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25:402–8.

    Article  CAS  Google Scholar 

  34. Sanjana NE, Shalem O, Zhang F. Improved vectors and genome-wide libraries for CRISPR screening. Nat Methods. 2014;11:783–4.

  35. Hirano Y, Ihara K, Masuda T, Yamamoto T, Iwata I, Takahashi A, et al. Shifting transcriptional machinery is required for long-term memory maintenance and modification in Drosophila mushroom bodies. Nat Commun. 2016;7:13471.

    Article  CAS  Google Scholar 

  36. IMAGEN Consortium, Mielenz D, Reichel M, Jia T, Quinlan EB, Stöckl T, et al. EFhd2/Swiprosin-1 is a common genetic determinator for sensation-seeking/low anxiety and alcohol addiction. Mol Psychiatry. 2018;23:1303–19.

    Article  Google Scholar 

  37. Schilling S, DeStefano AL, Sachdev PS, Choi SH, Mather KA, DeCarli CD, et al. APOE genotype and MRI markers of cerebrovascular disease. Neurology. 2013;81:292–300.

    Article  CAS  Google Scholar 

  38. Richardson NR, Roberts DC. Progressive ratio schedules in drug self-administration studies in rats: a method to evaluate reinforcing efficacy. J Neurosci Methods. 1996;66:1–11.

    Article  CAS  Google Scholar 

  39. Epstein DH, Preston KL, Stewart J, Shaham Y. Toward a model of drug relapse: An assessment of the validity of the reinstatement procedure. Psychopharmacology. 2006;189:1–16.

    Article  CAS  Google Scholar 

  40. Namba MD, Tomek SE, Olive MF, Beckmann JS, Gipson CD. The winding road to relapse: forging a new understanding of cue-induced reinstatement models and their associated neural mechanisms. Front Behav Neurosci. 2018;12:17.

  41. Deroche-Gamonet V. Evidence for addiction-like behavior in the rat. Science. 2004;305:1014–7.

    Article  CAS  Google Scholar 

  42. Chen X, Nelson CD, Li X, Winters CA, Azzam R, Sousa AA, et al. PSD-95 is required to sustain the molecular organization of the postsynaptic density. J Neurosci. 2011;31:6329–38.

    Article  CAS  Google Scholar 

  43. Beroun A, Nalberczak-Skóra M, Harda Z, Piechota M, Ziółkowska M, Cały A, et al. Generation of silent synapses in dentate gyrus correlates with development of alcohol addiction. Neuropsychopharmacol. 2018;43:1989–99.

    Article  CAS  Google Scholar 

  44. Nalberczak-Skóra M, Pattij T, Beroun A, Kogias G, Mielenz D, de Vries T, et al. Personality driven alcohol and drug abuse: new mechanisms revealed. Neurosci Biobehav Rev. 2020;116:64–73.

    Article  Google Scholar 

  45. Venniro M, Russell TI, Ramsey LA, Richie CT, Lesscher HMB, Giovanetti SM, et al. Abstinence-dependent dissociable central amygdala microcircuits control drug craving. Proc Natl Acad Sci USA. 2020;117:8126–34.

    Article  CAS  Google Scholar 

  46. Kim J, Zhang X, Muralidhar S, LeBlanc SA, Tonegawa S. Basolateral to central amygdala neural circuits for appetitive behaviors. Neuron 2017;93:1464–1479.e5.

    Article  CAS  Google Scholar 

  47. Zakhari S. Alcohol metabolism and epigenetics changes. Alcohol Res. 2013;35:6–16.

    Google Scholar 

  48. Koob GF. Neurocircuitry of alcohol addiction. Handbook of Clinical Neurology, vol. 125, Elsevier; 2014. p. 33–54.

  49. Abrahao KP, Salinas AG, Lovinger DM. Alcohol and the brain: neuronal molecular targets, synapses, and circuits. Neuron 2017;96:1223–38.

    Article  CAS  Google Scholar 

  50. Morisot N, Ron D. Alcohol-dependent molecular adaptations of the NMDA receptor system. Genes Brain Behav. 2017;16:139–48.

    Article  CAS  Google Scholar 

  51. Roberto M, Schweitzer P, Madamba SG, Stouffer DG, Parsons LH, Siggins GR. Acute and chronic ethanol alter glutamatergic transmission in rat central amygdala: an in vitro and in vivo analysis. J Neurosci. 2004;24:1594–603.

    Article  CAS  Google Scholar 

  52. Salling MC, Faccidomo SP, Li C, Psilos K, Galunas C, Spanos M, et al. Moderate alcohol drinking and the amygdala proteome: identification and validation of calcium/calmodulin dependent kinase II and AMPA receptor activity as novel molecular mechanisms of the positive reinforcing effects of alcohol. Biol Psychiatry. 2016;79:430–42.

    Article  CAS  Google Scholar 

  53. Wernicke C, Samochowiec J, Schmidt LG, Winterer G, Smolka M, Kucharska-Mazur J, et al. Polymorphisms in the N-methyl-D-aspartate receptor 1 and 2B subunits are associated with alcoholism-related traits. Biol Psychiatry. 2003;54:922–8.

    Article  CAS  Google Scholar 

  54. Karpyak VM, Geske JR, Colby CL, Mrazek DA, Biernacka JM. Genetic variability in the NMDA-dependent AMPA trafficking cascade is associated with alcohol dependence. Addict Biol. 2012;17:798–806.

    Article  CAS  Google Scholar 

  55. Bohnsack JP, Teppen T, Kyzar EJ, Dzitoyeva S, Pandey SC. The lncRNA BDNF-AS is an epigenetic regulator in the human amygdala in early onset alcohol use disorders. Transl Psychiatry. 2019;9:34.

    Article  Google Scholar 

  56. Yakout DW, Shree N, Mabb AM. Effect of pharmacological manipulations on Arc function. Curr Res Pharm Drug Discov. 2021;2:100013.

    Article  Google Scholar 

  57. Pandey SC, Zhang H, Ugale R, Prakash A, Xu T, Misra K. Effector immediate-early gene arc in the amygdala plays a critical role in alcoholism. J Neurosci. 2008;28:2589–600.

    Article  CAS  Google Scholar 

  58. Managò F, Mereu M, Mastwal S, Mastrogiacomo R, Scheggia D, Emanuele M, et al. Genetic disruption of Arc/Arg3.1 in mice causes alterations in dopamine and neurobehavioral phenotypes related to schizophrenia. Cell Rep. 2016;16:2116–28.

    Article  Google Scholar 

  59. Wall MJ, Collins DR, Chery SL, Allen ZD, Pastuzyn ED, George AJ, et al. The temporal dynamics of Arc expression regulate cognitive flexibility. Neuron. 2018;98:1124–32.e7.

    Article  CAS  Google Scholar 

  60. Penrod RD, Kumar J, Smith LN, McCalley D, Nentwig TB, Hughes BW, et al. Activity-regulated cytoskeleton-associated protein (Arc/Arg3.1) regulates anxiety- and novelty-related behaviors. Genes, Brain Behav. 2019;18:e12561.

    Article  Google Scholar 

  61. Penrod RD, Thomsen M, Taniguchi M, Guo Y, Cowan CW, Smith LN. The activity-regulated cytoskeleton-associated protein, Arc/Arg3.1, influences mouse cocaine self-administration. Pharmacol Biochem Behav. 2020;188:172818.

    Article  CAS  Google Scholar 

  62. Kyzar EJ, Zhang H, Pandey SC. Adolescent alcohol exposure epigenetically suppresses amygdala Arc enhancer RNA expression to confer adult anxiety susceptibility. Biol Psychiatry. 2019;85:904–14.

    Article  CAS  Google Scholar 

  63. Huentelman MJ, Muppana L, Corneveaux JJ, Dinu V, Pruzin JJ, Reiman R, et al. Association of SNPs in EGR3 and ARC with schizophrenia supports a biological pathway for schizophrenia risk. PLOS ONE. 2015;10:e0135076.

    Article  Google Scholar 

  64. Alzheimer’s Disease Neuroimaging Initiative BiR, Kong L-L, Xu M, Li G-D, Zhang D-F, et al. The Arc Gene Confers Genetic Susceptibility to Alzheimer’s Disease in Han Chinese. Mol Neurobiol. 2018;55:1217–26.

    Article  Google Scholar 

  65. Penner MR, Roth TL, Chawla MK, Hoang LT, Roth ED, Lubin FD, et al. Age-related changes in Arc transcription and DNA methylation within the hippocampus. Neurobiol Aging. 2011;32:2198–210.

    Article  CAS  Google Scholar 

  66. Wrase J, Makris N, Braus DF, Mann K, Smolka MN, Kennedy DN, et al. Amygdala volume associated with alcohol abuse relapse and craving. AJP. 2008;165:1179–84.

    Article  Google Scholar 

  67. Grace S, Rossetti MG, Allen N, Batalla A, Bellani M, Brambilla P, et al. Sex differences in the neuroanatomy of alcohol dependence: hippocampus and amygdala subregions in a sample of 966 people from the ENIGMA Addiction Working Group. Transl Psychiatry. 2021;11:156.

    Article  Google Scholar 

  68. Hill SY, Bellis MDD, Keshavan MS, Lowers L, Shen S, Hall J, et al. Right amygdala volume in adolescent and young adult offspring from families at high risk for developing alcoholism. Biol Psychiatry. 2001;49:894–905.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work has been supported by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement no 665735 (Bio4Med) and by the funding from Polish Ministry of Science and Higher Education within 2016-2020 funds for the implementation of international projects (agreement no 3548/H2020/COFUND/2016/2) and National Science Center (Poland) Harmonia and Opus grants (UMO-2016/22/M/NZ4/00674 and UMO-2015/19/B/NZ4/03163) to KR. This work was further supported by the German National Science Foundation (Deutsche Forschungsgemeinschaft [DFG]), grant MU 2789/8–2 and in part by the Federal Ministry of Education and Research (BMBF) under the e:Med Program (031L0190B and 01KC2004B) and by Japan Society for the Promotion of Science KAKENHI grants (17H06312 and 19H03328). This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (Reinforcement-related behavior in normal brain function and psychopathology) (LSHM-CT—2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the National Institute of Health (NIH) (R01DA049238, A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research (NIHR) Biomedical Research Center at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; Forschungsnetz AERIAL 01EE1406A, 01EE1406B; Forschungsnetz IMAC-Mind 01GL1745B), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-2, SFB 940, TRR 265, NE 1383/14-1), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1), the National Institutes of Health (NIH) funded ENIGMA (grants 5U54EB020403-05 and 1R56AG058854-01), NSFC grant 82150710554 and environMENTAL grant. Further support was provided by grants from:—the ANR (ANR-12-SAMA-0004, AAPG2019—GeBra), the Eranet Neuron (AF12-NEUR0008-01—WM2NA; and ANR-18-NEUR00002-01-ADORe), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), U.S.A. (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centers of Excellence. ImagenPathways “Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways” is a collaborative project supported by the European Research Area Network on Illicit Drugs (ERANID). This paper is based on independent research commissioned and funded in England by the National Institute for Health Research (NIHR) Policy Research Program (project ref. PR-ST-0416-10001. The views expressed in this article are those of the authors and not necessarily those of the national funding agencies or ERANID.

Author information

Authors and Affiliations

Authors

Consortia

Contributions

KR initiated the studies, designed experiments, supervised and coordinated research; RP, AS, ES, AB, MNS, AC and KR performed and analyzed mouse studies; HO, HB and KK provided materials and supervised in vitro experiments; IMAGEN consortium, NT, JZ, GS and CPM analyzed human data. RP, CPM, GS and KR wrote the paper. All authors discussed the results and commented on the paper.

Corresponding author

Correspondence to Kasia Radwanska.

Ethics declarations

Competing interests

TB served in an advisory or consultancy role for eye level, Infectopharm, Lundbeck, Medice, Neurim Pharmaceuticals, Oberberg GmbH, Roche, and Takeda. He received conference support or speaker’s fee by Janssen, Medice and Takeda. He received royalities from Hogrefe, Kohlhammer, CIP Medien, Oxford University Press; the present work is unrelated to these relationships. Dr Barker has received honoraria from General Electric Healthcare for teaching on scanner programming courses. LP served in an advisory or consultancy role for Roche and Viforpharm and received a speaker’s fee from Shire. She received royalties from Hogrefe, Kohlhammer and Schattauer. The present work is unrelated to the above grants and relationships. The other authors report no biomedical financial interests or potential competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The original online version of this article was revised: In Table 1 of this article, the columns are wrongly labelled in a published pdf file. They should be labelled as in the below. The original article has been corrected.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pagano, R., Salamian, A., Zielinski, J. et al. Arc controls alcohol cue relapse by a central amygdala mechanism. Mol Psychiatry 28, 733–745 (2023). https://doi.org/10.1038/s41380-022-01849-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01849-4

This article is cited by

Search

Quick links