Synchronized Mammalian Cells in Culture: A Comparison of Normal and KB Cancer Cell Growth

Experimentation and tests with cells in culture and cell synchronization or synchrony are important in order to be able to make both reliable and high-sensitivity measurements. This is also very important for mechanistic studies of cell division control, oncogenesis and tumor growth. A comparison is made in this article between the initially synchronized cell growth of rabbit and KB cells in synchronized cultures

Quantum Genetics and Quantum Automata Models of Quantum-Molecular Evolution Involved in the Evolution of Organisms and Species

Previous theoretical or general approaches to the problems of Quantum Genetics and Molecular Evolution are considered in this article from the point of view of Quantum Automata Theory first published by the author in 1971 and further developed in several recent articles. The representation of genomes and Interactome networks in categories of many-valued logic LMn –algebras that are naturally transformed during biological evolution, or evolve through interactions with the environment provide a new insight into the mechanisms of molecular evolution, as well as organismal evolution, in terms of sequences of quantum automata. Phenotypic changes are expressed only when certain environmentally-induced quantum-molecular changes are coupled with an internal re-structuring of major submodules of the genome and Interactome networks related to cell cycling and cell growth. Contrary to the commonly held view of `standard’ Darwinist models of evolution, the evolution of organisms and species occurs through coupled multi-molecular transformations induced not only by the environment but actually realized through internal re-organizations of genome and interactome networks. The biological, evolutionary processes involve certain epigenetic transformations that are responsible for phenotypic expression of the genome and Interactome transformations initiated at the quantum-molecular level. It can thus be said that only quantum genetics can provide correct explanations of evolutionary processes that are initiated at the quantum--multi-molecular levels and propagate to the higher levels of organismal and species evolution.

Biological evolution should be therefore regarded as a multi-scale process which is initiated by underlying quantum (coupled) multi-molecular transformations of the genomic and interactomic networks, followed by specific phenotypic transformations at the level of organism and the variable biogroupoids associated with the evolution of species which are essential to the survival of the species. The theoretical framework introduced in this article also paves the way to a Quantitative Biology approach to biological evolution at the quantum-molecular, as well as at the organismal and species levels. This is quite a substantial modification of the 'established’ modern Darwinist, and also of several so-called `molecular evolution’ theories

Metabolic, Replication and Genomic Category of Systems in Biology, Bioinformatics and Medicine

Metabolic-repair models, or (M,R)-systems were introduced in Relational Biology by Robert Rosen. Subsequently, Rosen represented such (M,R)-systems (or simply MRs)in terms of categories of sets, deliberately selected without any structure other than the discrete topology of sets. Theoreticians of life’s origins postulated that Life on Earth has begun with the simplest possible organism, called the primordial. Mathematicians interested in biology attempted to answer this important question of the minimal living organism by defining the functional relations that would have made life possible in such a minimal system- a grandad and grandma of all living organisms on Earth. Genomic systems are also considered as molecular realizations of (M,R)-system subcatgeories

Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

Operational logic and bioinformatics models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes are proposed. Łukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Łukasiewicz Topos with an n-valued Łukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis

Early Diagnosis of Alzheimer's disease by NIRF Spectroscopy and Nuclear Medicine

There is an urgent need for the early detection of diseases such as Alzheimer’s (AD) and Cancers in order to enable their successful treatment. Cancer is the second major cause of death after Heart Disease, and AD is the third major cause of death with major, human and financial/economics trillion dollar consequences for the society. Nuclear Medicine is concerned with applications in Medicine of Nuclear Science and Engineering techniques and knowledge. Three major Nuclear Medicine techniques that are established for diagnostic and research purposes are: Positron Emission Tomography (PET) and CAT/CT, Nuclear Magnetic Resonance Imaging (NMRI/MRI). However, these three techniques have also major limitations in terms of either cost or image resolution, as well as patient irradiation in the case of CAT/CT and PET. On the other hand, Near Infrared Chemical Imaging Microspectroscopy and certain Fluorescence spectroscopic techniques are capable of single cancer cell and/or single molecule detection and/or imaging. Such powerful capabilities, combined with low cost of diagnostics, make these novel techniques very attractive means for early detection of diseases such as cancer and Alzheimer’s, that are promising to reduce the fatality rate of patients through adequate diagnosis and treatment of such diseases at early stages. 
Currently NIH provides only inadequate funding for the clinical and research aspects of these novel investigation and clinical diagnostic techniques by FT-NIRS and Fluorescence spectrocopy for early detection of Alzheimer's and Cancers

Quantum Genetics, Quantum Automata and Quantum Computation

The concepts of quantum automata and quantum computation are studied in the context of quantum genetics and genetic networks with nonlinear dynamics. In a previous publication (Baianu,1971a) the formal concept of quantum automaton was introduced and its possible implications for genetic and metabolic activities in living cells and organisms were considered. This was followed by a report on quantum and abstract, symbolic computation based on the theory of categories, functors and natural transformations (Baianu,1971b). The notions of topological semigroup, quantum automaton,or quantum computer, were then suggested with a view to their potential applications to the analogous simulation of biological systems, and especially genetic activities and nonlinear dynamics in genetic networks. Further, detailed studies of nonlinear dynamics in genetic networks were carried out in categories of n-valued, Lukasiewicz Logic Algebras that showed significant dissimilarities (Baianu, 1977) from Bolean models of human neural networks (McCullough and Pitts,1945). Molecular models in terms of categories, functors and natural transformations were then formulated for uni-molecular chemical transformations, multi-molecular chemical and biochemical transformations (Baianu, 1983,2004a). Previous applications of computer modeling, classical automata theory, and relational biology to molecular biology, oncogenesis and medicine were extensively reviewed and several important conclusions were reached regarding both the potential and limitations of the computation-assisted modeling of biological systems, and especially complex organisms such as Homo sapiens sapiens(Baianu,1987). Novel approaches to solving the realization problems of Relational Biology models in Complex System Biology are introduced in terms of natural transformations between functors of such molecular categories. Several applications of such natural transformations of functors were then presented to protein biosynthesis, embryogenesis and nuclear transplant experiments. Other possible realizations in Molecular Biology and Relational Biology of Organisms are here suggested in terms of quantum automata models of Quantum Genetics and Interactomics. Future developments of this novel approach are likely to also include: Fuzzy Relations in Biology and Epigenomics, Relational Biology modeling of Complex Immunological and Hormonal regulatory systems, n-categories and Topoi of Lukasiewicz Logic Algebras and Intuitionistic Logic (Heyting) Algebras for modeling nonlinear dynamics and cognitive processes in complex neural networks that are present in the human brain, as well as stochastic modeling of genetic networks in Lukasiewicz Logic Algebras

Complex Systems Analysis of Cell Cycling Models in Carcinogenesis

A new approach to the modular, complex systems analysis of nonlinear dynamics in cell cycling network transformations involved in carcinogenesis is proposed. Carcinogenesis is a complex process that involves dynamically inter-connected biomolecules in the intercellular, membrane, cytosolic, nuclear and nucleolar compartments that form numerous inter-related pathways referred to as networks.
The variable biotopology of such dynamic networks is highly complex, and has a number of interesting properties that can be formally characterized at one level of organization by mathematical structures called 'biogroupoids'. 
One such family of pathways contains the cell cyclins. Cyclins are proteins that link several critical pro-apoptotic and other cell cycling/ division components, including the tumor suppressor gene TP53 and its product, the Thomsen-Friedenreich antigen (T antigen), Rb, mdm2, c-Myc, p21, p27, Bax, Bad and Bcl-2, which all play major roles in carcinogenesis of many cancers. A novel theoretical analysis is thus possible based on recently published studies of cyclin signaling, with special emphasis placed on the roles of cyclins D1 and E, suggests novel clinical trials and rational therapies of cancer through reestablishment of cell cycling inhibition in metastatic cancer cells

Applications Of Microspectroscopy, Hyperspectral Chemical Imaging And Fluorescence Microscopy In Chemistry, Biochemistry, Biotechnology, Molecular And Cell Biology

Chemical imaging is a technique for the simultaneous measurement of spectra (chemical information) and images or pictures (spatial information)^1,2^. The technique is most often applied to either solid or gel samples, and has applications in chemistry, biology^3-8^, medicine^9,10^, pharmacy^11^ (see also for example: Chemical Imaging Without Dyeing), food science, Food Physical Chemistry, Biotechnology^12,13^, Agriculture and industry. NIR, IR and Raman chemical imaging is also referred to as hyperspectral, spectroscopic, spectral or multi-spectral imaging (also see micro-spectroscopy). However, other ultra-sensitive and selective, chemical imaging techniques are also in use that involve either UV-visible or fluorescence microspectroscopy

Translational Oncogenomics and Human Cancer Interactome Networks

An overview of translational, human oncogenomics, transcriptomics and cancer interactomic networks is presented together with basic concepts and potential, new applications to Oncology and Integrative Cancer Biology. Novel translational oncogenomics research is rapidly expanding through the application of advanced technology, research findings and computational tools/models to both pharmaceutical and clinical problems. A self-contained presentation is adopted that covers both fundamental concepts and the most recent biomedical, as well as clinical, applications. Sample analyses in recent clinical studies have shown that gene expression data can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, ‘personalized medicine’. Several cancer detection techniques are currently under development both in the direction of improved detection sensitivity and increased time resolution of cellular events, with the limits of single molecule detection and picosecond time resolution already reached. The urgency for the complete mapping of a human cancer interactome with the help of such novel, high-efficiency / low-cost and ultra-sensitive techniques is also pointed out