Published April 7, 2019 | Version v1
Journal article Open

Quantum entanglement in theoretical physics as a new insight into cancer biology

  • 1. Ph.D. in Cell and Molecular Biology, Board Member of Weston A Price Foundation, Washington, United States of America, Active member of American Physical Society (APS).
  • 2. 2Ph.D. in Clinical Phycology, CEO/President of Violet Cancer Institute (VCI), Member of Royal Society of Biology
  • 3. Senior Research Scientist, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA

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Description

Quantum entanglement is a phenomenon in theoretical physics that happens when pairs or groups of particles are generated in such a way that the quantum state of each particle cannot be described independently of the others, even when the particles are separated by a large distance. Instead, a quantum state must be described for the system as a whole. Based on the theory of cancer as an evolutionary metabolic disease (Evolutionary Metabolic Hypothesis of Cancer or EMHC), the cancerous cells are eukaryotic cells with different metabolic rate from healthy cells due to the damaged or shut down mitochondria in them. Assuming each human eukaryotic cell as a particle and the whole body as a Quantum Entangled System (QES), is a new perspective on the description of cancer disease, and this link between theoretical physics and biological sciences in the field of cancer therapies can be a new insight into the cause, prevention and treatment of cancer. Additionally, this perspective admits the Lamarckian evolution in the understanding of the mentioned disease. We have presented each human eukaryotic cell containing mitochondria as a QES, and the whole body containing healthy and normal cells as a QES as well. The difference between the entropy of the healthy cells and cancer cells has also been mentioned in this research.

Notes

We thank Weston A Price Foundation in Washington, USA, for their supportive help. We thank Prof. Stephanie Seneff, Senior Research Scientist at the Artificial Intelligence Laboratory of Massachusetts Institute of Technology, Prof. Thomas N. Seyfried, and Professor Dominic D'Agostino for their informative help. We also thank American Physical Society (APS).

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