<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AAR</journal-id><journal-title-group><journal-title>Advances in Aging Research</journal-title></journal-title-group><issn pub-type="epub">2169-0499</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/aar.2022.112003</article-id><article-id pub-id-type="publisher-id">AAR-115606</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject><subject> Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Beyond Biological Aging: Table Analysis
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jorge</surname><given-names>Barragán</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sebastián</surname><given-names>Sánchez</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Universidad del Gran Rosario, Rosario, Argentina</addr-line></aff><pub-date pub-type="epub"><day>01</day><month>03</month><year>2022</year></pub-date><volume>11</volume><issue>02</issue><fpage>27</fpage><lpage>34</lpage><history><date date-type="received"><day>5,</day>	<month>August</month>	<year>2021</year></date><date date-type="rev-recd"><day>26,</day>	<month>February</month>	<year>2022</year>	</date><date date-type="accepted"><day>1,</day>	<month>March</month>	<year>2022</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Keeping in mind the relationship between the basal metabolic rate and the change in weight in the aging process, we propose to verify the holographic description of the same. For this we set ourselves the following objectives: Verify the correlation between total energy dissipation and energy dissipation per unit body mass, and verify the correlation between the total energy dissipation and the body mass. As a result of the data analysis, we obtained a coherent representation of our proposal. A high degree of correlation between the total energy dissipation in an organism and the basal metabolic rate/dry kg was found. Such a condition implies that the stated biological system satisfies the Holographic Principle.
 
</p></abstract><kwd-group><kwd>Basal Metabolic Rate</kwd><kwd> Body Weight</kwd><kwd> Energy Dissipation</kwd><kwd> Geometric Phase</kwd><kwd> Information Density</kwd><kwd> Relative Surface</kwd><kwd> Structural Geometry</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>In previous works, we have tried to understand the biological aging process as a consequence of the relationship between Basal Metabolism Rate (BMR) and the body mass of an organism [<xref ref-type="bibr" rid="scirp.115606-ref1">1</xref>]. Specifically, we study the evolution of the values of the Basal Metabolism Rate BMR/unit of Dry Weight (BMR/dry weight), and the evolution of the values of the total body mass throughout a lifespan. We also proposed a vector model to explain this phenomenon [<xref ref-type="bibr" rid="scirp.115606-ref2">2</xref>].</p><p>This consideration is not a whim, but it derives from the following concept: the metabolic activity of a cell depends on its exchange of matter and energy within the environment, and this occurs through its surface [<xref ref-type="bibr" rid="scirp.115606-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref5">5</xref>]. More precisely, the metabolic activity depends on its relative surface area or the surface area per volume unit [<xref ref-type="bibr" rid="scirp.115606-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref7">7</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref9">9</xref>].</p><p>For these purposes, body mass is assimilable to volume, since there is a direct relationship between body mass and volume (the changes in the density are not enough to invalidate this relationship), so considering the values of the TMB/unit of body mass, they are consistent with the original concept of area per unit volume or relative area [<xref ref-type="bibr" rid="scirp.115606-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref11">11</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref13">13</xref>]. If we look at a cell, we can say that the energy it dissipates has a direct relationship with its relative surface area or the surface area per unit volume. The information of a human being is “encoded” in its DNA, and “expressed” in its structure. But the information is not expressed if it is not mediated before a process of dissipation of energy. This is related to the boundary of the human being (which in the case of the cell is its surface), rather than its body mass or volume [<xref ref-type="bibr" rid="scirp.115606-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref16">16</xref>].</p><p>This characteristic of the biological phenomenon bears a remarkable similarity to the holographic principle: in every limited spatial region, the information contained in that region is related to its surface, and not to its volume [<xref ref-type="bibr" rid="scirp.115606-ref17">17</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref18">18</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref19">19</xref>].</p><p>This has interesting consequences, such as the fact considering that there is an informational density limit for the spatial region in question (called the Bekenstein Boundary in the theoretical framework of the Holographic Principle), and that stated limit is related to the surface that limits the stated region and not with its volume [<xref ref-type="bibr" rid="scirp.115606-ref20">20</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref21">21</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref22">22</xref>].</p><p>If we reduce the problem to its simplest form in biology, we must consider that a cell has a limit to its size and that this expresses its limit for informational density. A high degree of correlation between the total energy dissipation in an organism and the BMR/dry kg (consistent with the concept of relative-surface), implies that the stated biological system satisfies the Holographic Principle. On the other hand, a low degree of correlation implies that the total energy dissipation is more related to its mass or total volume than to its BMR/dry kg. In such case, the system does not satisfy the Holographic Principle.</p><p>The proposed objectives are:</p><p>&#173; Verify the correlation between total energy dissipation and energy dissipation per unit body mass throughout the lifespan in human beings.</p><p>&#173; Verify the correlation between the total energy dissipation and the body mass throughout the lifespan in human beings.</p></sec><sec id="s2"><title>2. Material and Method</title><p>Data on the evolution of the BMR/dry kg, the total energy dissipation expressed in Kcal/day, and the total body mass expressed in kg throughout the lifespan in human beings are from Tables of previous works [<xref ref-type="bibr" rid="scirp.115606-ref23">23</xref>].</p><p>A correlation test of R<sup>2</sup> (coefficient of determination) applied to the evolution of these variables, permits knowing the degree of association between them. An adequate analysis of data can reveal associations that support the hypothesis of the authors or discard it in case of not obtaining statistically significant results.</p><p>When we refer to a unit of body mass, we take the values of the unit of body mass free of water (dry weight), to consider the metabolically active body mass as a reference. In <xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>, we find data on the total body mass (second column), the total BMR per day (third column) and BMR/dry kg (fourth column).</p></sec><sec id="s3"><title>3. Results</title><p>When comparing the total BMR/day with the dry BMR/Kg, R<sup>2</sup> has a value of 0.96 (p &lt; 0.02), which is statistically significant as can be seen in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p><p>But when comparing the total BMR/day with the total body mass, R<sup>2</sup> has a value of 0.84 (NS), showing that there is no statistically significant association, as can be seen in <xref ref-type="fig" rid="fig2">Figure 2</xref>.</p><p>These results are nothing more than the formalization of simple reasoning that arises from analyzing <xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>: If 6 kg of total body mass dissipates 320 Kcal/day, it would be expected that 65 kg of total body mass dissipates 3466 Kcal/day. However, that is not what happens. An older adult, weighing 65 kg, dissipates 1280 Kcal/day.</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref></label><caption><title> Shows total weight values, total kcal dissipated per day, and BMR/dry kg for different ages. Sample demographic characteristics: Argentine population white (Hispanic) race. Sample size: n = 10,960</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Age (years)</th><th align="center" valign="middle" >Total Weight (kg)</th><th align="center" valign="middle" >Total BMRl/day (Kcal/day)</th><th align="center" valign="middle" >BMR/kg (Kcal/dry weight)</th><th align="center" valign="middle" >Dry weight (kg)</th></tr></thead><tr><td align="center" valign="middle" >0 - 0.5</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >320</td><td align="center" valign="middle" >228</td><td align="center" valign="middle" >1.4</td></tr><tr><td align="center" valign="middle" >0.5 - 1</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >500</td><td align="center" valign="middle" >172</td><td align="center" valign="middle" >2.9</td></tr><tr><td align="center" valign="middle" >1 - 3</td><td align="center" valign="middle" >13</td><td align="center" valign="middle" >740</td><td align="center" valign="middle" >160</td><td align="center" valign="middle" >4.6</td></tr><tr><td align="center" valign="middle" >4 - 6</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >950</td><td align="center" valign="middle" >125</td><td align="center" valign="middle" >7.6</td></tr><tr><td align="center" valign="middle" >7 - 10</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >1130</td><td align="center" valign="middle" >103</td><td align="center" valign="middle" >10.9</td></tr><tr><td align="center" valign="middle" >11 - 14</td><td align="center" valign="middle" >46</td><td align="center" valign="middle" >1310</td><td align="center" valign="middle" >68</td><td align="center" valign="middle" >19.3</td></tr><tr><td align="center" valign="middle" >15 - 18</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >1370</td><td align="center" valign="middle" >56</td><td align="center" valign="middle" >24.2</td></tr><tr><td align="center" valign="middle" >19 - 24</td><td align="center" valign="middle" >58</td><td align="center" valign="middle" >1350</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >26.6</td></tr><tr><td align="center" valign="middle" >25 - 50</td><td align="center" valign="middle" >63</td><td align="center" valign="middle" >1380</td><td align="center" valign="middle" >45</td><td align="center" valign="middle" >30.2</td></tr><tr><td align="center" valign="middle" >51 or more</td><td align="center" valign="middle" >65</td><td align="center" valign="middle" >1280</td><td align="center" valign="middle" >39</td><td align="center" valign="middle" >32.5</td></tr></tbody></table></table-wrap><p>If instead, we observe the BMR/dry kg (fourth column) and the dry weight (fifth column) for each age, the following can be seen: A newborn whose dry BMR/kg is 228 Kcal and whose dry weight is 1.4 kg, dissipates 319.2 Kcal. An older adult, weighing 65 kg, whose BMR/dry kg is 39 Kcal and whose dry weight is 32.5 kg, dissipates 1267 Kcal/day. That is exactly what happens: a newborn dissipates 320 Kcal/day, and an older adult 1280 Kcal/day (third column of <xref ref-type="table" rid="table1"><xref ref-type="table" rid="table">Table </xref>1</xref>). For illustrative purposes only, <xref ref-type="fig" rid="fig3">Figure 3</xref> shows this relationship.</p><p>The choice of a surface graphic for this illustration is no accident. The authors consider it necessary to highlight, that in the case of the aging of a human being, the situation is assimilable to a surface that curves when reaching the information density limit shortly after puberty [<xref ref-type="bibr" rid="scirp.115606-ref1">1</xref>].</p><p>We know it seems too simple. However it&#180;s a concrete evaluation of a simple and novelty idea: information is proportional to energy dissipated, and energy dissipated is proportional to surface area rather than volume. Then the information is proportional to the surface rather than the volume (Holographic Principle).</p></sec><sec id="s4"><title>4. Discussion</title><p>The principles and relationships that support the results are easy to explain: According to the holographic principle, in every limited spatial region, the information contained in that region is related to its surface, and not to its volume.</p><p>In the case of living beings, the information is related to the dissipated energy. So, if the dissipated energy is more related to its relative surface than to its volume, it is possible to apply the holographic principle to living beings. In the particular case of humans, this implies that the total energy dissipation is more related to the BMR/dry weight (consistent with the concept of relative-surface) than to the total mass or volume of the organism.</p><p>In the proposed theoretical framework, we can consider that the results obtained confirm that human beings satisfy the holographic principle since the total dissipation of energy is related to the dissipation values per unit of body</p><p>mass, and not to the values of the total body mass. This is the novelty point of our contribution.</p><p>In previous paragraphs, we have mentioned the concept of informational density limits, and we must specify that this depends on the quantity of information. The case of fertilization and segmentation is eloquent. The oocyte is a large cell with little relative surface area. This implies a low metabolic rate, and a high informational density, to which is added the genetic information of the sperm. Soon it reaches the informational density limit and segmentation begins.</p><p>With this, the amount of information in each cell does not vary, but its density decreases because the size is reduced and the relative surface area increases. The metabolic rate shoots up and the differentiation processes begin [<xref ref-type="bibr" rid="scirp.115606-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.115606-ref25">25</xref>].</p><p>There is a minimum amount of information to support the identity of the human being. The limit of the least retainable complexity is named by Stephen Gould as “the left wall of minimal complexity” [<xref ref-type="bibr" rid="scirp.115606-ref26">26</xref>]. There is also a maximum limit, or limit of informational density, which is reached when the system no longer supports additional information. This occurs in a cell when its relative surface area decreases and its metabolic capacity declines.</p><p>In a human being we can observe the same change when, after puberty, growth ceases. The system does not increase in size but increases the informational density until it reaches its limit. This will have two consequences: one is the decline in the BMR per body mass unit, and the other is the appearance of geometric phase changes that will be seen as aging [<xref ref-type="bibr" rid="scirp.115606-ref1">1</xref>].</p><p>This is directly linked to the complexity and size of living things [<xref ref-type="bibr" rid="scirp.115606-ref27">27</xref>]. A cell cannot indefinitely increase in size. Once the informational density limit is reached, cells divide and associate, forming complex multicellular structures [<xref ref-type="bibr" rid="scirp.115606-ref28">28</xref>]. Therefore, the system that results from this association has more information. But the most remarkable fact is that each of its parts, and its cells, contains information regarding the entire system. Having the same DNA in all cells is an effective way of observing it.</p><p>This condition also satisfies another characteristic of holograms: each of their parts contains information about the entire system [<xref ref-type="bibr" rid="scirp.115606-ref29">29</xref>]. This complexity is not the result of chance, but of the existence of an informational density limit. This in turn influences the geometry of the system. When a cell reaches its limit, it generates multicellular structures called tissues. These do not have the shape of their cells, in the same way that a human being does not have the shape of its organs, its tissues or its cells.</p><p>However, all levels of the biological organization have one characteristic in common: their geometry is determined by the density of their information. This can be seen in biological aging, and in the consistency of physical-biological systems using the holographic principle.</p></sec><sec id="s5"><title>5. Conclusions</title><p>We can conclude that the proposed objectives are met. The evaluation of the correlation between the total BMR/day and the BMR/dry weight throughout the lifespan in human beings is significant.</p><p>On the other hand, the evaluation of the correlation between the total BMR/day and the total body mass (total weight) is not significant.</p><p>This permits us to assume that in the proposed theoretical framework, human beings satisfy the holographic principle at their different levels of the organization.</p><p>Within the same framework, it is worth highlighting the primary role of the concept of the informational density limit: wherever it occurs, that is the boundary for human beings, beyond which organisms age, generate a new level of organization, or simply die.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s7"><title>Cite this paper</title><p>Barrag&#225;n, J. and S&#225;nchez, S. 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