{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:57:06Z","timestamp":1760241426178,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,3,26]],"date-time":"2018-03-26T00:00:00Z","timestamp":1522022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>A cell signaling system is in a non-equilibrium state, and it includes multistep biochemical signaling cascades (BSCs), which involve phosphorylation of signaling molecules, such as mitogen-activated protein kinase (MAPK) pathways. In this study, the author considered signal transduction description using information thermodynamic theory. The ideal BSCs can be considered one type of the Szilard engine, and the presumed feedback controller, Maxwell\u2019s demon, can extract the work during signal transduction. In this model, the mutual entropy and chemical potential of the signal molecules can be redefined by the extracted chemical work in a mechanicochemical model, Szilard engine, of BSC. In conclusion, signal transduction is computable using the information thermodynamic method.<\/jats:p>","DOI":"10.3390\/e20040224","type":"journal-article","created":{"date-parts":[[2018,3,26]],"date-time":"2018-03-26T03:43:29Z","timestamp":1522035809000},"page":"224","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Information Thermodynamics of the Cell Signal Transduction as a Szilard Engine"],"prefix":"10.3390","volume":"20","author":[{"given":"Tatsuaki","family":"Tsuruyama","sequence":"first","affiliation":[{"name":"Clinical Research Center for Medical Equipment Development, Department of Pathology, Kyoto University Hospital, Shogoin-Kawahara-cho 54, Sakyo-ku, Kyoto 606-8057, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1140\/epje\/i2011-11026-7","article-title":"Stochastic thermodynamics of single enzymes and molecular motors","volume":"34","author":"Seifert","year":"2011","journal-title":"Eur. Phys. J. E Soft Matter"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"126001","DOI":"10.1088\/0034-4885\/75\/12\/126001","article-title":"Stochastic thermodynamics, fluctuation theorems and molecular machines","volume":"75","author":"Seifert","year":"2012","journal-title":"Rep. Prog. Phys."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Tsuruyama, T. (2014). A model of cell biological signaling predicts a phase transition of signaling and provides mathematical formulae. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0102911"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Tsuruyama, T. (2017). Kinetic stability analysis of protein assembly on the center manifold around the critical point. BMC Syst. Biol., 11.","DOI":"10.1186\/s12918-017-0391-7"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"18063","DOI":"10.1103\/PhysRevLett.111.180603","article-title":"Information Thermodynamics on Causal Networks","volume":"111","author":"Ito","year":"2013","journal-title":"Phys. Rev. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1016\/j.bpj.2014.06.017","article-title":"Single-cell E. coli response to an instantaneously applied chemotactic signal","volume":"107","author":"Sagawa","year":"2014","journal-title":"Biophys. J."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tsuruyama, T. (2018). Information Thermodynamics Derives the Entropy Current of Cell Signal Transduction as a Model of a Binary Coding System. Entropy, 20.","DOI":"10.3390\/e20020145"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1146\/annurev-biochem-061516-044813","article-title":"Cyclic GMP-AMP as an Endogenous Second Messenger in Innate Immune Signaling by Cytosolic DNA","volume":"86","author":"Kato","year":"2017","journal-title":"Annu. Rev. Biochem."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"250602","DOI":"10.1103\/PhysRevLett.102.250602","article-title":"Minimal energy cost for thermodynamic information processing: Measurement and information erasure","volume":"102","author":"Sagawa","year":"2009","journal-title":"Phys. Rev. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"090602","DOI":"10.1103\/PhysRevLett.104.090602","article-title":"Generalized Jarzynski equality under nonequilibrium feedback control","volume":"104","author":"Sagawa","year":"2010","journal-title":"Phys. Rev. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1002\/bs.3830090402","article-title":"On the decrease of entropy in a thermodynamic system by the intervention of intelligent beings","volume":"9","author":"Szilard","year":"1964","journal-title":"Behav. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"180602","DOI":"10.1103\/PhysRevLett.109.180602","article-title":"Fluctuation theorem with information exchange: Role of correlations in stochastic thermodynamics","volume":"109","author":"Sagawa","year":"2012","journal-title":"Phys. Rev. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"7498","DOI":"10.1038\/ncomms8498","article-title":"Maxwell\u2019s demon in biochemical signal transduction with feedback loop","volume":"6","author":"Ito","year":"2015","journal-title":"Nat Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"080403","DOI":"10.1103\/PhysRevLett.100.080403","article-title":"Second law of thermodynamics with discrete quantum feedback control","volume":"100","author":"Sagawa","year":"2008","journal-title":"Phys. Rev. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1126\/science.1204553","article-title":"Information transduction capacity of noisy biochemical signaling networks","volume":"334","author":"Cheong","year":"2011","journal-title":"Science"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1370","DOI":"10.1126\/science.1254933","article-title":"Systems biology. Accurate information transmission through dynamic biochemical signaling networks","volume":"346","author":"Selimkhanov","year":"2014","journal-title":"Science"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tsuruyama, T. (2017). Channel Capacity of Coding System on Tsallis Entropy and q-Statistics. Entropy, 19.","DOI":"10.3390\/e19120682"},{"key":"ref_18","unstructured":"Aharon, K.K., and Curran, P.F. (2013). Nonequilibrium Thermodynamics in Biophysics, Harvard University Press."},{"key":"ref_19","unstructured":"Br\u00d8nsted, J.N. (1955). Principles and Problems in Energetics, Interscience Publishers, Inc."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1038\/nature10874","article-title":"Large-scale vortex lattice emerging from collectively moving microtubules","volume":"483","author":"Sumino","year":"2012","journal-title":"Nature"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"15599","DOI":"10.1038\/ncomms15599","article-title":"Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome","volume":"8","author":"Teschendorff","year":"2017","journal-title":"Nat. Commun."},{"key":"ref_22","first-page":"1","article-title":"scEpath: Energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data","volume":"1","author":"Jin","year":"2018","journal-title":"Bioinformatics"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Sato, M., Kawana, K., Adachi, K., Fujimoto, A., Yoshida, M., Nakamura, H., Nishida, H., Inoue, T., Taguchi, A., and Ogishima, J. (2017). Intracellular signaling entropy can be a biomarker for predicting the development of cervical intraepithelial neoplasia. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0176353"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Teschendorff, A.E., Banerji, C.R., Severini, S., Kuehn, R., and Sollich, P. (2015). Increased signaling entropy in cancer requires the scale-free property of protein interaction networks. Sci. Rep.","DOI":"10.1038\/srep09646"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Banerji, C.R., Severini, S., Caldas, C., and Teschendorff, A.E. (2015). Intra-tumour signalling entropy determines clinical outcome in breast and lung cancer. PLoS Comput. Biol., 11.","DOI":"10.1371\/journal.pcbi.1004115"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Dopazo, J., and Erten, C. (2017). Graph-theoretical comparison of normal and tumor networks in identifying BRCA genes. BMC Syst. Biol., 11.","DOI":"10.1186\/s12918-017-0495-0"}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/20\/4\/224\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:58:29Z","timestamp":1760194709000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/20\/4\/224"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3,26]]},"references-count":26,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2018,4]]}},"alternative-id":["e20040224"],"URL":"https:\/\/doi.org\/10.3390\/e20040224","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2018,3,26]]}}}