Positive and Negative Feedback in Engineering and Biology

Zeron, Eduardo S.

doi:10.1051/mmnp:2008055

Cited by 6 publications

(3 citation statements)

References 31 publications

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“…The binding of active repressors to the first two operators occurs cooperatively and this increases the sigmoidicity of the regulatory function accounting for repression [4,14]. Furthermore, it has been shown that a high level on sigmoidicity is necessary for the the bacteria to maintain a constant intracellular tryptophan concentration, regardless of variations in the amino acid concentration in the extracellular medium [16].…”

Section: Discussionmentioning

confidence: 99%

On the Use of the Hill Functions in Mathematical Models of Gene Regulatory Networks

Santillán

2008

Math. Model. Nat. Phenom.

144

108

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Abstract. Hill functions follow from the equilibrium state of the reaction in which n ligands simultaneously bind a single receptor. This result if often employed to interpret the Hill coefficient as the number of ligand binding sites in all kinds of reaction schemes. Here, we study the equilibrium states of the reactions in which n ligand bind a receptor sequentially, both non-cooperatively and in a cooperative fashion. The main outcomes of such analysis are that: n is not a good estimate, but only an upper bound, for the Hill coefficient; while the Hill coefficient depends quite strongly on the cooperativity level among ligands. We finally use these results to discuss the feasibility and constrains of using Hill functions to model the regulatory functions in mathematical models of gene regulatory networks.

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Section: Discussionmentioning

confidence: 99%

On the Use of the Hill Functions in Mathematical Models of Gene Regulatory Networks

Santillán

2008

Math. Model. Nat. Phenom.

144

108

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“…Positive feedback can amplify the properties of thermal input/concentration output systems processed by chemical reactions. Such properties have been studied mathematically through systems biology [47][48][49][50][51]. It is thus interesting experimentally to study such properties, which can promote understanding of biological phenomena and development of novel material functions.…”

Section: Positive Feedback By Self-catalytic Chemical Reactionmentioning

confidence: 99%

Thermal Input/Concentration Output Systems Processed by Chemical Reactions of Helicene Oligomers

Zhang¹,

Bao²,

Yamaguchi³

2022

Reactions

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This article describes thermal input/concentration output systems processed by chemical reactions. Various sophisticated thermal inputs can be converted into concentration outputs through the double-helix formation of helicene oligomers exhibiting thermal hysteresis. The inputs include high or low temperature, cooling or heating state, slow or fast cooling state, heating state, and cooling history. The chemical basis for the properties of the chemical reactions includes the reversibility out of chemical equilibrium, sigmoidal relationship and kinetics, bistability involving metastable states, positive feedback by self-catalytic chemical reactions, competitive chemical reactions, and fine tunability for parallel processing. The interfacing of concentration outputs in other systems is considered, and biological cells are considered to have been utilizing such input/output systems processed by chemical reactions.

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“…While feedback is a function of interest in both SB and EB and it has been known for at least half a century in medicine and two millennia in physics [22]–[25], feedback has only marginally been explored in infections. In October of 2012, more than 200,000 bibliographic hits could be retrieved under ‘feedback’ and ∼1700 hits were yielded when ‘feedback’ and ‘definition’ were searched for, but less than 50 hits were found when ‘infection’ was added.…”

Section: Introductionmentioning

confidence: 99%

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

et al. 2013

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BackgroundImproved characterization of infectious disease dynamics is required. To that end, three-dimensional (3D) data analysis of feedback-like processes may be considered.MethodsTo detect infectious disease data patterns, a systems biology (SB) and evolutionary biology (EB) approach was evaluated, which utilizes leukocyte data structures designed to diminish data variability and enhance discrimination. Using data collected from one avian and two mammalian (human and bovine) species infected with viral, parasite, or bacterial agents (both sensitive and resistant to antimicrobials), four data structures were explored: (i) counts or percentages of a single leukocyte type, such as lymphocytes, neutrophils, or macrophages (the classic approach), and three levels of the SB/EB approach, which assessed (ii) 2D, (iii) 3D, and (iv) multi-dimensional (rotating 3D) host-microbial interactions.ResultsIn all studies, no classic data structure discriminated disease-positive (D+, or observations in which a microbe was isolated) from disease-negative (D–, or microbial-negative) groups: D+ and D– data distributions overlapped. In contrast, multi-dimensional analysis of indicators designed to possess desirable features, such as a single line of observations, displayed a continuous, circular data structure, whose abrupt inflections facilitated partitioning into subsets statistically significantly different from one another. In all studies, the 3D, SB/EB approach distinguished three (steady, positive, and negative) feedback phases, in which D– data characterized the steady state phase, and D+ data were found in the positive and negative phases. In humans, spatial patterns revealed false-negative observations and three malaria-positive data classes. In both humans and bovines, methicillin-resistant Staphylococcus aureus (MRSA) infections were discriminated from non-MRSA infections.ConclusionsMore information can be extracted, from the same data, provided that data are structured, their 3D relationships are considered, and well-conserved (feedback-like) functions are estimated. Patterns emerging from such structures may distinguish well-conserved from recently developed host-microbial interactions. Applications include diagnosis, error detection, and modeling.

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Positive and Negative Feedback in Engineering and Biology

Cited by 6 publications

References 31 publications

On the Use of the Hill Functions in Mathematical Models of Gene Regulatory Networks

On the Use of the Hill Functions in Mathematical Models of Gene Regulatory Networks

Thermal Input/Concentration Output Systems Processed by Chemical Reactions of Helicene Oligomers

Feedback-Based, System-Level Properties of Vertebrate-Microbial Interactions

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