Information dynamics in living systems: prokaryotes, eukaryotes, and cancer
Living systems use information and energy to maintain stable entropy while far from thermodynamic equilibrium. The underlying first principles have not been established. We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (m...
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description | Living systems use information and energy to maintain stable entropy while far from thermodynamic equilibrium. The underlying first principles have not been established.
We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers.
We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype. |
doi_str_mv | 10.1371/journal.pone.0022085 |
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We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers.
We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0022085</identifier><identifier>PMID: 21818295</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Biological evolution ; Biology ; Breast cancer ; Cancer ; Cancer research ; Carcinogenesis ; Carcinogens ; Cell Proliferation ; Dehydrogenases ; Disease prevention ; Divergence ; Energy balance ; Energy consumption ; Entropy ; Equilibrium ; Eukaryotes ; Eukaryotic Cells - metabolism ; Evolution ; Evolution (Biology) ; Glycolysis ; Humans ; Hypotheses ; Information systems ; Information Theory ; Mammography ; Medical prognosis ; Medical screening ; Metabolism ; Minima ; Mitochondria ; Mutation ; Neoplasms - metabolism ; Neoplasms - pathology ; Organelles ; Phase transitions ; Physical characteristics ; Population ; Prokaryotes ; Prokaryotic Cells - metabolism ; Proteins ; Statistical mechanics ; Thermodynamic equilibrium ; Thermodynamics</subject><ispartof>PloS one, 2011-07, Vol.6 (7), p.e22085</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Frieden and Gatenby. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Frieden and Gatenby. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c691t-703b0f97ce16537a09813779d27bb782f2c1c392261fc6f91b7d239c7cac57463</citedby><cites>FETCH-LOGICAL-c691t-703b0f97ce16537a09813779d27bb782f2c1c392261fc6f91b7d239c7cac57463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3139603/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3139603/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,2096,2915,23847,27905,27906,53772,53774,79349,79350</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21818295$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Oresic, Matej</contributor><creatorcontrib>Frieden, B Roy</creatorcontrib><creatorcontrib>Gatenby, Robert A</creatorcontrib><title>Information dynamics in living systems: prokaryotes, eukaryotes, and cancer</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Living systems use information and energy to maintain stable entropy while far from thermodynamic equilibrium. The underlying first principles have not been established.
We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers.
We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype.</description><subject>Analysis</subject><subject>Biological evolution</subject><subject>Biology</subject><subject>Breast cancer</subject><subject>Cancer</subject><subject>Cancer research</subject><subject>Carcinogenesis</subject><subject>Carcinogens</subject><subject>Cell Proliferation</subject><subject>Dehydrogenases</subject><subject>Disease prevention</subject><subject>Divergence</subject><subject>Energy balance</subject><subject>Energy consumption</subject><subject>Entropy</subject><subject>Equilibrium</subject><subject>Eukaryotes</subject><subject>Eukaryotic Cells - metabolism</subject><subject>Evolution</subject><subject>Evolution (Biology)</subject><subject>Glycolysis</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Information systems</subject><subject>Information Theory</subject><subject>Mammography</subject><subject>Medical prognosis</subject><subject>Medical screening</subject><subject>Metabolism</subject><subject>Minima</subject><subject>Mitochondria</subject><subject>Mutation</subject><subject>Neoplasms - metabolism</subject><subject>Neoplasms - pathology</subject><subject>Organelles</subject><subject>Phase transitions</subject><subject>Physical characteristics</subject><subject>Population</subject><subject>Prokaryotes</subject><subject>Prokaryotic Cells - metabolism</subject><subject>Proteins</subject><subject>Statistical mechanics</subject><subject>Thermodynamic equilibrium</subject><subject>Thermodynamics</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNkmuL1DAUhoso7rr6D0QLgiA4Y25NGj8Iy-JlcGHB29eQpkknY5uMSbo4_96M012noCD5kHDynDcn57xF8RiCJcQMvtr4MTjZL7fe6SUACIG6ulOcQo7RgiKA7x6dT4oHMW4AqHBN6f3iBMEa1ohXp8XHlTM-DDJZ78p25-RgVSytK3t7bV1Xxl1Meoivy23w32XY-aTjy1KPf87StaWSTunwsLhnZB_1o2k_K76-e_vl4sPi8ur96uL8cqEoh2nBAG6A4UxpSCvMJOB1_hDjLWJNw2pkkIIKc4QoNIoaDhvWIswVU1JVjFB8Vjw96G57H8XUhyggBhRigjnMxOpAtF5uxDbYIZcrvLTid8CHTsiQrOq1aGGlG1JxQIgkrVYyF9NAU3NaEcxMm7XeTK-NzaBbpV0Ksp-Jzm-cXYvOXwsMMacAZ4Fnk0DwP0Yd0z9KnqhO5qpsnkoWU4ONSpwTRuuaELqnln-h8mp1Hlx2grE5Pkt4MUvITNI_UyfHGMXq86f_Z6--zdnnR-xayz6to-_HvY_iHCQHUAUfY9DmtnMQiL2Rb7oh9kYWk5Fz2pPjrt8m3TgX_wLJ6u0f</recordid><startdate>20110719</startdate><enddate>20110719</enddate><creator>Frieden, B Roy</creator><creator>Gatenby, Robert A</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110719</creationdate><title>Information dynamics in living systems: prokaryotes, eukaryotes, and cancer</title><author>Frieden, B Roy ; Gatenby, Robert A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c691t-703b0f97ce16537a09813779d27bb782f2c1c392261fc6f91b7d239c7cac57463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Analysis</topic><topic>Biological evolution</topic><topic>Biology</topic><topic>Breast cancer</topic><topic>Cancer</topic><topic>Cancer research</topic><topic>Carcinogenesis</topic><topic>Carcinogens</topic><topic>Cell Proliferation</topic><topic>Dehydrogenases</topic><topic>Disease prevention</topic><topic>Divergence</topic><topic>Energy balance</topic><topic>Energy consumption</topic><topic>Entropy</topic><topic>Equilibrium</topic><topic>Eukaryotes</topic><topic>Eukaryotic Cells - metabolism</topic><topic>Evolution</topic><topic>Evolution (Biology)</topic><topic>Glycolysis</topic><topic>Humans</topic><topic>Hypotheses</topic><topic>Information systems</topic><topic>Information Theory</topic><topic>Mammography</topic><topic>Medical prognosis</topic><topic>Medical screening</topic><topic>Metabolism</topic><topic>Minima</topic><topic>Mitochondria</topic><topic>Mutation</topic><topic>Neoplasms - metabolism</topic><topic>Neoplasms - pathology</topic><topic>Organelles</topic><topic>Phase transitions</topic><topic>Physical characteristics</topic><topic>Population</topic><topic>Prokaryotes</topic><topic>Prokaryotic Cells - metabolism</topic><topic>Proteins</topic><topic>Statistical mechanics</topic><topic>Thermodynamic equilibrium</topic><topic>Thermodynamics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frieden, B Roy</creatorcontrib><creatorcontrib>Gatenby, Robert A</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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The underlying first principles have not been established.
We propose that stable entropy in living systems, in the absence of thermodynamic equilibrium, requires an information extremum (maximum or minimum), which is invariant to first order perturbations. Proliferation and death represent key feedback mechanisms that promote stability even in a non-equilibrium state. A system moves to low or high information depending on its energy status, as the benefit of information in maintaining and increasing order is balanced against its energy cost. Prokaryotes, which lack specialized energy-producing organelles (mitochondria), are energy-limited and constrained to an information minimum. Acquisition of mitochondria is viewed as a critical evolutionary step that, by allowing eukaryotes to achieve a sufficiently high energy state, permitted a phase transition to an information maximum. This state, in contrast to the prokaryote minima, allowed evolution of complex, multicellular organisms. A special case is a malignant cell, which is modeled as a phase transition from a maximum to minimum information state. The minimum leads to a predicted power-law governing the in situ growth that is confirmed by studies measuring growth of small breast cancers.
We find living systems achieve a stable entropic state by maintaining an extreme level of information. The evolutionary divergence of prokaryotes and eukaryotes resulted from acquisition of specialized energy organelles that allowed transition from information minima to maxima, respectively. Carcinogenesis represents a reverse transition: of an information maximum to minimum. The progressive information loss is evident in accumulating mutations, disordered morphology, and functional decline characteristics of human cancers. The findings suggest energy restriction is a critical first step that triggers the genetic mutations that drive somatic evolution of the malignant phenotype.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21818295</pmid><doi>10.1371/journal.pone.0022085</doi><tpages>e22085</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Biological evolution Biology Breast cancer Cancer Cancer research Carcinogenesis Carcinogens Cell Proliferation Dehydrogenases Disease prevention Divergence Energy balance Energy consumption Entropy Equilibrium Eukaryotes Eukaryotic Cells - metabolism Evolution Evolution (Biology) Glycolysis Humans Hypotheses Information systems Information Theory Mammography Medical prognosis Medical screening Metabolism Minima Mitochondria Mutation Neoplasms - metabolism Neoplasms - pathology Organelles Phase transitions Physical characteristics Population Prokaryotes Prokaryotic Cells - metabolism Proteins Statistical mechanics Thermodynamic equilibrium Thermodynamics |
title | Information dynamics in living systems: prokaryotes, eukaryotes, and cancer |
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