Cosmology and Cell Biology as Empirical Evidence of Cosmic Consciousness:
From Astrology to Astronomy, From Chemiosmosis to Conformons, From Gnergons to Gnergitons
Sungchul Ji, Ph.D.
Emeritus Professor of Theoretical Cell Biology
Ernest Mario School of Pharmacy
Rutgers University, Piscataway, NJ.
What if cosmology and cell biology—two of the most fundamental sciences—offer more than just knowledge of stars and cells? What if they provide empirical evidence that consciousness is a fundamental aspect of Reality?
In this post, I present a synthesis of philosophical history, thermodynamic modeling, and systems biology to argue that the very structure of the universe and the living cell point to the existence of a deeper, conscious, triadic order of reality, which I call the Geometry of Reality (GOR).
1. From Kinematics to Dynamics: A Historical Analogy
In Table 1 below, we compare the evolution of cosmology and cell biology using the distinction between kinematics (descriptive motion) and dynamics (causal interaction):
In cosmology, the astrological models of Pythagoras and Ptolemy (600–150 BCE) were kinematic—they described how celestial bodies moved, but not why. It wasn’t until 1543, with Copernicus, followed by Kepler, Galilei, and Newton, that astronomical dynamics emerged to explain motion via physical laws.
In cell biology, a similar pattern is emerging. In 1961, Peter Mitchell's chemiosmotic model provided a kinematic description of ATP synthesis through proton gradients [1, 2]. But the deeper, dynamical mechanism—how chemical energy is coupled to mechanical motion—remained elusive until the Conformon Model, proposed by D. E. Green and me [3, 4], offered a quantum-mechanically and enzymologically realistic mechanism of chemomechanical coupling [5] (see Rows 1, 2, and 3, Table 1).
Conclusion: Just as it took humanity nearly two millennia to progress from astrology to astronomy, it may take at least six decades (1961–2025) to shift from the chemiosmotic model to the conformon model, if the paper in [5] is published in 2025.
2. Planckian Distributions and the Signature of Selection
One striking empirical observation emerges in both cosmology and cell biology: their key datasets exhibit long-tailed distributions that fit the Planck Distribution Equation (PDE) [10; 12, p. 334].
In cosmology, this appears in galactic structures (Cosmic Background Radiation) and energy distributions [7].
In cell biology, it manifests in gene (7-mers) expression patterns [14].
As shown in Row 5 of Table 10, the two histograms fit to PDE (Planckian Distribution Equation) [10], implying that non-random selection processes are involved [12] —the telltale sign of information generation, which we denote as Planckian Information (IP) [9].
These PDE-fitting histograms are the fingerprints of selection, strongly suggesting that both the universe and the cell are products of Iterative Reproduction with Variation and Selection by Environment (IRVSE) [9, 11].
Figure 2. The geometric mechanism of generating the Fibonacci series and the Golden spiral based on the Principle of IRVSE (Iterative Reproduction with Variations and Selection by Environment) [11].
(i) After squaring (or reproducing) 1 and adding the result to the original square, S1, you get rectangle R1 with the long side length 2.
(ii) After squaring (or reproducing) the long side of R1 and adding the result to R1, you get a rectangle R2 with the long side length 3.
(iii) After squaring (or reproducing) the long side of R2 and adding the result to R2, you get a rectangle R3 with the long side length 5.
(iv) Repeat (iii) with R3, namely, after squaring (or reproducing) the long side of R3 and adding the result to R3, you get a rectangle R4 with long side length 8.
(v) Form a spiral by connecting the opposite corners of each square with a circular arc (selected out of almost an infinite number of other possible curves).
3. From Gnergons to Gnergitons: Projecting Consciousness
In the Geometry of Reality (see Row 10, Table 1), we define three ontologically distinct yet interrelated layers:
Gnergons = Information (Gn) + Energy (-erg-) + Entity (-on)
→ These reside in the Gnergonic Universe, corresponding to observable, selected phenomena—like galaxies and cells.Gnergitons = Information (Gn) + Energy (-erg-) + Spirit (-it-) + Entity (-on)
→ These are 3D triadic holons, residing in the Origin of GOR, encompassing Consciousness, Self-Knowing, and Selection.
The Gnergons are 2D projections of Gnergitons. Therefore, the existence of gnergons (observable PDE-fitting data) logically necessitates the existence of their gnergitonic sources, which are intrinsically triadic and conscious.
In other words:
The empirical fact that the cosmos and the cell exhibit Planckian structures (gnergons) provides indirect but compelling evidence that they are shadows of a pre-existing and conscious gnergitons.
4. Consciousness as a Foundational Category of Reality
GOR assigns Consciousness/Spirit to the Z-axis, completing the triad alongside Matter and Mind. This assignment is not arbitrary; it is justified by:
The irreducible triadicity of Firstness (Object), Secondness (Sign), and Thirdness (Interpretant) from Peircean semiotics [15].
The need for a selection process to create information from randomness [12].
The philosophical convergence of physics, biology, and metaphysics through top-down selection mechanisms, as exemplified by IRVSE [11] and the PDE fits [12].
Thus, GOR supports the conclusion:
Consciousness is not an emergent property of matter—it is a fundamental dimension of Reality, detectable through the gnergonic footprints left by gnergitonic origins.
Closing Thought
If PDE-fitting distributions in both galaxies and genes (see Row 5, Table 1) are manifestations of selection, and if selection implies consciousness, then perhaps the cell and the cosmos can be viewed as the shadows of Cosmic Consciousness.
References:
[1] Mitchell, P. (1961). Coupling of phosphorylation to electron and hydrogen transfer by a chemiosmotic type of mechanism. Nature 191:144-148.
[2] Mitchell, P. (1966). Chemiosmotic coupling in oxidative and photosynthetic phosphorylation. Biol. Rev. 41: 445-502
[3] Green, D. E. and Ji, S. (1972). The Electromechanochemical Model of Mitochondrial Structure and Function, in: Molecular Basis of Electron Transport (Schulz, J. and Cameron, B. F., eds.), Academic Press, New York, pp. 1-44.
[4] Ji, S. (1976). A Model of Oxidative Phosphorylation that Accommodates the Chemical Intermediate, Chemiosmotic, Localized Proton, and Conformational Hypotheses. J. theoret. Biol. 59, 319-330.
[5] Ji, S. (2025). Chemiosmotic vs Conformon Models of Oxidative Phosphorylation: Theory and Mechanistic Insights. BioSytems (accepted).
[6] Ji, S. (2020). The Planck-Shannon plot: A quantitative method for identifying ‘superstructures’ in cell biology and consciousness study. Cosmos & History: The Journal of Natural and Social Philosophy 16 (2): 142-164.
[7] Ade, P. A. R., Aikin, R. W., Barkats, D. et al. (2014) BICEP2 I: Detection Of B-mode Polarization at Degree Angular Scales. arXiv:1403.3985v3 [astro-ph.CO].
[8] Ji, S. (1991). The Shillongator: A Self-Knowing Universe. In: Molecular Theories of Cell Life and Death (S. Ji, ed.), Rutgers University Press, New Brunswick, N.J. Pp. 152-163, 230-237
[9] Ji, S. (2020). The Planck-Shannon plot: A quantitative method for identifying ‘superstructures’ in cell biology and consciousness study. Cosmos & History: The Journal of Natural and Social Philosophy, 16(2): 142–164.
[10] Ji, S. (2015). Planckian distributions in molecular machines, living cells, and brains: The wave-particle duality in biomedical sciences. Proceedings of the International Conference on Biology and Biomedical Engineering. Vienna, March 15-17, pp. 115-137. PDF at http://www.inase.org/library/2015/vienna/BICHE.pdf
[11] Ji, S. (2018). The Cell Language Theory: Connecting Mind and Matter. World Scientific Publishing, New Jersey. P.389.
[12] Ji, S. (2018). Op. Cit. Derivation of PDE from the Gaussian Distribution. P. 357.
[13] Ji, S., and Davis, J.J.J. (2025). Causality vs. Codality: Information encoded in space-time. Journal of Consciousness Exploration & Research 16 (1): 16-25.
[14] Zhou, Y. and Mishra, B. (2004). Models of Genome Evolution. In: Modeling in Molecular Biology (Ciobanu G and Rozenberg G, eds), Springer, Berlin, pp. 287-304.
[15] Semiotics. https://en.wikipedia.org/wiki/Semiotics