The textbook conceptualization of phenotype creation, "genotype (G) + environment (E) + genotype & environment interactions (GE) ↦ phenotype (Ph)", is modeled with open quantum systems theory (OQST) or more generally with adaptive dynamics theory (ADT). The model is quantum-like, i.e., it is not about quantum physical processes in biosystems. Generally such modeling is about applications of the quantum formalism and methodology outside of physics. Macroscopic biosystems, in our case genotypes and phenotypes, are treated as information processors which functioning matches the laws of quantum information theory. Phenotypes are the outputs of the E-adaptation processes described by the quantum master equation, Gorini-Kossakowski-Sudarshan-Lindblad equation (GKSL). Its stationary states correspond to phenotypes. We highlight the class of GKSL dynamics characterized by the camel-like graphs of (von Neumann) entropy: in the process of E-adaptation phenotype's state entropy (disorder) first increases and then falls down - a stable and well-ordered phenotype is created. Traits, an organism's phenotypic characteristics, are modeled within the quantum measurement theory, as generally unsharp observables given by positive operator valued measures (POVMs. This paper is also a review on the methods and mathematical apparatus of quantum information biology.
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http://dx.doi.org/10.1016/j.biosystems.2024.105261 | DOI Listing |
J Mol Model
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Laboratory of Nanostructures and Advanced Materials, Mechanics and Thermofluids, Faculty of Sciences and Technologies, Hassan II University of Casablanca, B.P 146, 20650, Mohammedia, Morocco.
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View Article and Find Full Text PDFNano Lett
January 2025
Max Planck Institute for Solid State Research, Heisenbergstr. 1, Stuttgart, 70569, Germany.
Spin Hall nano-oscillators convert DC to magnetic auto-oscillations in the microwave regime. Current research on these devices is dedicated to creating next-generation energy-efficient hardware for communication technologies. Despite intensive research on magnetic auto-oscillations within the past decade, the nanoscale mapping of those dynamics remained a challenge.
View Article and Find Full Text PDFInt J Legal Med
January 2025
Biological and Life Sciences, School of Arts and Sciences, Ahmedabad University, Central Campus, Navrangpura, Ahmedabad, Gujarat, India.
Polymerase Chain Reaction (PCR) has transformed forensic DNA analysis but is still limited when dealing with compromised trace or inhibitor-containing samples. Nanotechnology has been integrated into nanoPCR (nanoparticle-assisted PCR) to overcome these obstacles. Nanomaterials improve PCR sensitivity, selectivity, and efficiency.
View Article and Find Full Text PDFACS Appl Bio Mater
January 2025
Department of Chemistry, University of North Dakota, Grand Forks, North Dakota 58202, United States.
Synergistic photodynamic/photothermal therapy (PDT/PTT) can be used to target cancer cells by locally generating singlet oxygen species or increasing temperature under laser irradiation. This approach offers higher tumor ablation efficiency, lower therapeutic dose requirements, and reduced side effects compared to single treatment approaches. However, the therapeutic efficiency of PDT/PTT is still limited by the low oxygen levels within the solid tumors caused by abnormal vasculature and altered cancer cell metabolism.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Institute of Physical Chemistry, RWTH Aachen University, Aachen 52074, Germany.
Exploring the conformational space of molecules remains a challenge of fundamental importance to quantum chemistry: identification of relevant conformers at ambient conditions enables predictive simulations of almost arbitrary properties. Here, we propose a novel approach, called TTConf, to enable conformational sampling of large organic molecules where the combinatorial explosion of possible conformers prevents the use of a brute-force systematic conformer search. We employ tensor trains as a highly efficient dimensionality reduction algorithm, effectively reducing the scaling from exponential to polynomial.
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