Complexity in Biological Organization: Deconstruction (and Subsequent Restating) of Key Concepts

Bizzarri, Mariano; Naimark, Oleg; Nieto-Villar, J.M.; Fedeli, Valeria; Giuliani, Alessandro

doi:10.3390/e22080885

Cited by 25 publications

(24 citation statements)

References 84 publications

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“…For example, recent advances in real-time analysis of the dynamics and changes of cellular activity by quantitative phase imaging (QPI) techniques have shown promises for the cellular-level understanding of the pathophysiology of diseases [45]. The concepts developed in a recent review [35] concern the metabolic activity of cells, including pathological transformations and their viability as metabolic processes in substantially non-equilibrium thermodynamic systems. A feature of these processes is the "subordination" of the evolution of biological systems to universal (self-similar) scenarios, when morphogenetic processes are determined by collective (mesoscopic) variables.…”

Section: Resultsmentioning

confidence: 99%

“…There are many studies [49][50][51][52] of the spectral (in terms of the Fourier and wavelet analysis) and multifractal properties of a biological system dynamics. Particularly, a recent paper [35] showed that the dynamics of living breast human cells in cancerous and normal states differ according to multifractal properties. Cancer cells evince monofractal dynamics, while normal cells are characterized by multifractal spectra.…”

Section: Resultsmentioning

confidence: 99%

“…In this method, the dynamics of the phase thickness of a single cell was recorded in real-time, near to the vicinity of the nucleolus boundary and considered as an integrating signal of cellular metabolic activity. Recently [34,35], the coherent dynamics of DNA open states was suggested to qualitatively characterize different scenarios of DNA gene expression for normal and cancer cells, with transitions among them being caused by various critical events. Generally, the changes occurring on the DNA scale, especially the critical events bringing a system out of the equilibrium state, correlate with the ones in the metabolic activity of cells.…”

Section: Introductionmentioning

confidence: 99%

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Label-Free Single Cell Viability Assay Using Laser Interference Microscopy

Beloglazova

Nikitiuk

Voronina

et al. 2021

Biology

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Laser interference microscopy (LIM) is a promising label-free method for single-cell research applicable to cell viability assessment in the studies of mammalian cells. This paper describes the development of a sensitive and reproducible method for assessing cell viability using LIM. The method, based on associated signal processing techniques, has been developed as a result of real-time investigation in phase thickness fluctuations of viable and non-viable MCF-7 cells, reflecting the presence and absence of their metabolic activity. As evinced by the values of the variable vc, this variable determines the viability of a cell only in the attached state (vc exceeds 20 nm2 for viable attached cells). The critical value of the power spectrum slope βc of the phase thickness fluctuations equals 1.00 for attached MCF-7 cells and 0.71 for suspended cells. The slope of the phase fluctuations’ power spectrum for MCF-7 cells was determined to exceed the threshold value of βc for a living cell, otherwise the cell is dead. The results evince the power spectrum slope as the most appropriate indicator of cell viability, while the integrated evaluation criterion (vc and βc values) can be used to assay the viability of attached cells.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Label-Free Single Cell Viability Assay Using Laser Interference Microscopy

Beloglazova

Nikitiuk

Voronina

et al. 2021

Biology

Self Cite

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“…The mechanobiology of living cells is associated with the cytoskeleton (CSK) dynamics revealing the fundamental property of the cells qualified as the cell plasticity and the cell damage [69]. Plasticity is the phenomenon inherently linked to the collective behavior of mesodefects in the "biological crystals" and provides the unique mechanism of the defects induced momentum transfer and the structural memory as the expression scenario.…”

Section: Discussionmentioning

confidence: 99%

DNA Transformation, Cell Epigenetic Landscape and Open Complex Dynamics in Cancer Development

Naimark¹,

Bayandin²,

Beloglazova³

et al. 2020

Math.Biol.Bioinf.

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Statistical thermodynamics allowed the formulation of mesoscopic approach of DNA transformation in course of the excitation of collective distortion modes (denaturation bubbles) associated with hydrogen bond breaking between the base pairs. Intermediate (non-continual limit) of DNA modeling (the Peyrard-Bishop model) is combined with the field description (generalized Ginzburg-Landau approach) to analyze the dynamics of collective open complex modes associated with mesodefects in the DNA ensemble. Collective modes dynamics describes different scenario of gene expression according to statistically predicted form of out-of-equilibrium potential (epigenetic landscape) reflecting specific type criticality of “soft matter” with mesodefects (open complexes) – the structural-scaling transition. Principal difference of thermodynamics of non-continual and continual models is thermalization conditions related to thermal fluctuations responsible for the DNA breathing (localized excitation with breather dynamics) and structural-scaling parameter responsible for spinodal decomposition of out-of-equilibrium potential metastability due to generation of open complex collective modes. Open complex collective modes have the nature of self-similar solutions (breathers, auto-solitary and blow-up modes) of open complex evolution equation accounting qualitative different types of potential metastabilities. Sub-sets of collective modes represent the phase variables of attractors associated with different scenario of expression dynamics, which allows the interpretation of multistability of the epigenetic landscape and the Huang diagram of gene expression. It was shown different epigenetic pathway in attractors phase space corresponding to normal and cancer expression scenario. These scenarios were supported by laser interference microscopy of living normal and cancer cells illustrating multi- and monofractal dynamics.

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“…For this reason, graphs are commonly used to model a plethora of real-world, possibly complex, systems [1]. Notable examples include biological systems and chemistry [2][3][4][5][6][7][8][9][10][11][12][13], social and collaboration networks [14], computer vision and image processing [15][16][17][18], natural language processing [19][20][21][22], and energy distribution networks [23].…”

Section: Introductionmentioning

confidence: 99%

(Hyper)graph Kernels over Simplicial Complexes

Martino

2020

Entropy

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Graph kernels are one of the mainstream approaches when dealing with measuring similarity between graphs, especially for pattern recognition and machine learning tasks. In turn, graphs gained a lot of attention due to their modeling capabilities for several real-world phenomena ranging from bioinformatics to social network analysis. However, the attention has been recently moved towards hypergraphs, generalization of plain graphs where multi-way relations (other than pairwise relations) can be considered. In this paper, four (hyper)graph kernels are proposed and their efficiency and effectiveness are compared in a twofold fashion. First, by inferring the simplicial complexes on the top of underlying graphs and by performing a comparison among 18 benchmark datasets against state-of-the-art approaches; second, by facing a real-world case study (i.e., metabolic pathways classification) where input data are natively represented by hypergraphs. With this work, we aim at fostering the extension of graph kernels towards hypergraphs and, more in general, bridging the gap between structural pattern recognition and the domain of hypergraphs.

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Complexity in Biological Organization: Deconstruction (and Subsequent Restating) of Key Concepts

Cited by 25 publications

References 84 publications

Label-Free Single Cell Viability Assay Using Laser Interference Microscopy

Label-Free Single Cell Viability Assay Using Laser Interference Microscopy

DNA Transformation, Cell Epigenetic Landscape and Open Complex Dynamics in Cancer Development

(Hyper)graph Kernels over Simplicial Complexes

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