Experimental Test and Applications of Correlation Metric Construction

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Time Series ◽  
Steady State ◽  
Reaction Mechanism ◽  
Experimental Test ◽  
Reaction Pathway ◽  
Chemical Species ◽  
Reaction Network ◽  
Sampling Period ◽  
The Matrix ◽  
Time Lagged

In this chapter we present an experimental test case of the deduction of a reaction pathway and mechanism by means of correlation metric construction from time-series measurements of the concentrations of chemical species. We choose as the system an enzymatic reaction network, the initial steps of glycolysis. Glycolysis is central in intermediary metabolism and has a high degree of regulation. The reaction pathway has been well studied and thus it is a good test for the theory. Further, the reaction mechanism of this part of glycolysis has been modeled extensively. The quantity and precision of the measurements reported here are sufficient to determine the matrix of correlation functions and, from this, a reaction pathway that is qualitatively consistent with the reaction mechanism established previously. The existence of unmeasured species did not compromise the analysis. The quantity and precision of the data were not excessive, and thus we expect the method to be generally applicable. This CMC experiment was carried out in a continuous-flow stirred-tank reactor (CSTR). The reaction network considered consists of eight enzymes, which catalyze the conversion of glucose into dihydroxyacetone phosphate and glyceraldehyde phosphate. The enzymes were confined to the reactor by an ultrafiltration membrane at the top of the reactor. The membrane was permeable to all low molecular weight species. The inputs are (1) a reaction buffer, which provides starting material for the reaction network to process, maintains pH and pMg, and contains any other species that act as constant constraints on the system dynamics, and (2) a set of “control species” (at least one), whose input concentrations are changed randomly every sampling period over the course of the experiment. The sampling period is chosen such that the system almost, but not quite, relaxes to a chosen nonequilibrium steady state. The system is kept near enough to its steady state to minimize trending (caused by the relaxation) in the time series, but far enough from the steady state that the time-lagged autocorrelation functions for each species decay to zero over three to five sampling periods. This long decay is necessary if temporal ordering in the network is to be analyzed.

Determination of Complex Reaction Mechanisms

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Reaction Mechanism ◽  
Reaction Mechanisms ◽  
Reaction Pathway ◽  
Chemical Species ◽  
Rate Coefficients ◽  
Chemical System ◽  
Evolutionary Development ◽  
Complex Reaction ◽  
Oscillatory Reactions

In a chemical system with many chemical species several questions can be asked: what species react with other species: in what temporal order: and with what results? These questions have been asked for over one hundred years about simple and complex chemical systems, and the answers constitute the macroscopic reaction mechanism. In Determination of Complex Reaction Mechanisms authors John Ross, Igor Schreiber, and Marcel Vlad present several systematic approaches for obtaining information on the causal connectivity of chemical species, on correlations of chemical species, on the reaction pathway, and on the reaction mechanism. Basic pulse theory is demonstrated and tested in an experiment on glycolysis. In a second approach, measurements on time series of concentrations are used to construct correlation functions and a theory is developed which shows that from these functions information may be inferred on the reaction pathway, the reaction mechanism, and the centers of control in that mechanism. A third approach is based on application of genetic algorithm methods to the study of the evolutionary development of a reaction mechanism, to the attainment given goals in a mechanism, and to the determination of a reaction mechanism and rate coefficients by comparison with experiment. Responses of non-linear systems to pulses or other perturbations are analyzed, and mechanisms of oscillatory reactions are presented in detail. The concluding chapters give an introduction to bioinformatics and statistical methods for determining reaction mechanisms.

Introduction

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Reaction Mechanism ◽  
Chemical Kinetics ◽  
Chemical Engineering ◽  
Reaction Pathway ◽  
Reaction System ◽  
Chemical Species ◽  
Pulse Method ◽  
Elementary Reaction ◽  
Elementary Reactions ◽  
Arbitrary Strength

Chemical kinetics as a science has existed for more than a century. It deals with the rates of reactions and the details of how a given reaction proceeds from reactants to products. In a chemical system with many chemical species, there are several questions to be asked: What species react with what other species? In what temporal order? With what catalysts? And with what results? The answers constitute the macroscopic reaction mechanism. The process can be described macroscopically by listing the reactants, intermediates, products, and all the elementary reactions and catalysts in the reaction system. The present book is a treatise and text on the determination of complex reaction mechanisms in chemistry and in chemical reaction systems that occur in chemical engineering, biochemistry, biology, biotechnology, and genomics. A basic knowledge of chemical kinetics is assumed. Several approaches are suggested for the deduction of information on the causal chemical connectivity of the species, on the elementary reactions among the species, and on the sequence of the elementary reactions that constitute the reaction pathway and the reaction mechanism. Chemical reactions occur by the collisions of molecules, and such an event is called an elementary reaction for specified reactant and product molecules. A balanced stoichiometric equation for an elementary reaction yields the number of each type of molecule according to conservation of atoms, mass, and charge. Figure 1.1 shows a relatively simple reaction mechanism for the decomposition of ozone by light, postulated to occur in a series of three elementary steps. (The details of collisions of molecules and bond rearrangements are not discussed.) All approaches are based on the measurements of the concentrations of chemical species in the whole reaction system, not on parts, as has been the practice. One approach is called the pulse method, in which a pulse of concentration of one or more species of arbitrary strength is applied to a reacting system and the responses of as many species as possible are measured. From these responses causal chemical connectivities may be inferred. The basic theory is explained, demonstrated on a model mechanism, and tested in an experiment on a part of glycolysis.

Lifetime and Transit Time Distributions and Response Experiments in Chemical Kinetics

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Reaction Mechanism ◽  
Stationary State ◽  
Linear Response ◽  
Reaction Pathway ◽  
Kinetic Equations ◽  
Chemical Species ◽  
Main Idea ◽  
Stable Stationary State ◽  
Probability Densities ◽  
Mathematical Techniques

We discussed some aspects of the responses of chemical systems, linear or nonlinear, to perturbations on several earlier occasions. The first was the responses of the chemical species in a reaction mechanism (a network) in a nonequilibrium stable stationary state to a pulse in concentration of one species. We referred to this approach as the “pulse method” (see chapter 5 for theory and chapter 6 for experiments). Second, we studied the time series of the responses of concentrations to repeated random perturbations, the formulation of correlation functions from such measurements, and the construction of the correlation metric (see chapter 7 for theory and chapter 8 for experiments). Third, in the investigation of oscillatory chemical reactions we showed that the responses of a chemical system in a stable stationary state close to a Hopf bifurcation are related to the category of the oscillatory reaction and to the role of the essential species in the system (see chapter 11 for theory and experiments). In each of these cases the responses yield important information about the reaction pathway and the reaction mechanism. In this chapter we focus on the design of simple types of response experiments that make it possible to extract mechanistic and kinetic information from complex nonlinear reaction systems. The main idea is to use “neutral” labeled compounds (tracers), which have the same kinetic and transport properties as the unlabeled compounds. In our previous work we have shown that by using neutral tracers a class of response experiments can be described by linear response laws, even though the underlying kinetic equations are highly nonlinear. The linear response is not the result of a linearization procedure, but it is due to the use of neutral tracers. As a result the response is linear even for large perturbations, making it possible to investigate global nonlinear kinetics by making use of linear mathematical techniques. Moreover, the susceptibility functions from the response law are related to the probability densities of the lifetimes and transit times of the various chemical species, making it easy to establish a connection between the response data and the mechanism and kinetics of the process.

Correlation Metric Construction: Theory of Statistical Construction of Reaction Mechanisms

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Time Series ◽  
Chemical Reactions ◽  
Reaction Pathway ◽  
Reaction System ◽  
Chemical Species ◽  
Biochemical Networks ◽  
Statistical Dependence ◽  
Nand Gate ◽  
Regulatory Structure ◽  
Genome Study

In chapter 5, we studied the responses of chemical species in a reaction system to pulse perturbations and showed the deduction of direct, causal connectivities by chemical reactions—the reaction pathway—and the reaction mechanism from such measurements. The causal connectivites give the information on how the chemical species are connected by chemical reactions. In this chapter we turn to another source of information about chemical species in a reaction system, that of correlations among the species. Correlations of concentrations are measures of the statistical dependence of the concentration of one species on that of one or more of the other species in the system. Such correlations can be determined from measurements of time series of concentrations collected around a stationary state (nonequilibrium or equilibrium). We shall show that from concentration correlations it is possible to construct a skeletal diagram of the reaction system that gives a graphical measure of strong control and regulatory structure in reaction networks, gives some information on connectivity, leads to information on the reaction pathway and mechanism, and may simplify the analysis of such networks by identifying possible, nearly separable subsystems. We begin with the demonstration and explanation of this approach by analyzing some abstract reaction models. In chapter 8 we show the utility of this “correlation metric construction” (CMC) with application to time-series measurements on a part of glycolysis, and in chapter 13 on an extensive genome study. Consider a chemical system as shown in fig. 7.1. Mechanisms of this type are common in biochemical networks. For example, the subnetwork of fig. 7.1 containing S3 to S5 is based on a simple model of fructose interconversion in glycolysis and the subnetwork composed of S6 to S7 is similar to the phosphorylation/dephosphorylation cycles found in cyclic cascades. As an aside, this mechanism performs the function of a biochemical NAND gate, another example of a chemical computational function (see chapter 4).

Experimental Test of the Pulse Perturbation Method for Determining Causal Connectivities of Chemical Species in a Reaction Network

2006 ◽  
Author(s):  
John Ross ◽  
Igor Schreiber ◽  
Marcel O. Vlad
Keyword(s):  
Perturbation Method ◽  
Stationary State ◽  
Experimental Test ◽  
Temporal Order ◽  
Reaction System ◽  
Chemical Species ◽  
Reaction Network ◽  
Quantitative Information ◽  
Pulse Perturbation ◽  
Relative Errors

For an experimental test of the pulse perturbation method we choose a part of glycolysis shown in fig. 6.1. There are similarities and some differences between the model in fig. 5.12 and the reaction system in fig. 6.1. The reaction system has reactants, enzymes, and some effectors. One point of interest in choosing this system is the test of detecting and identifying the split of the reaction chain, from glucose to F1,6BP, at the aldolase reaction into two chains, one terminating at G3P and the other at 3PG. The experiments were run in a continuous-flow stirred tank reactor (CSTR) with the reaction system at a nonequilibrium stationary state, such that the reactions run spontaneously from glucose to G3P and 3PG. The concentrations of the species at this state are close to those of physiological conditions. The metabolites G6P, F6P, F1,6BP, DHAP, G3P, and 3PG were detected and analyzed by capillary electrophoresis. Typical relative errors were 4% for G6P, 11% for F6P, 15% for F1,6BP, 9% for DHAP, 6% for 3PG, and 3% for G3P. Figure 6.3 shows the responses of the species to a pulse of G6P, in a plot of relative concentrations versus. time during the relaxation, after the pulse, back to the stationary state. Complete relaxation took about half an hour. As seen from the amplitudes of the responses in the plot, the temporal order of propagation of the pulse is: G6P, F6P, DHAP, G3P, and 3PG. The time ordering of the maximum deviations agrees with this ordering except perhaps for G3P and 3PG. In some experiments, as in this one, the species F1,6BP could not be measured adequately and is not shown. It is possible to extract qualitative information on rates but difficult to derive quantitative information. Following a pulse of F1,6BP, the temporal order of propagation in the maximum relative concentrations is F1,6BP, DHAP, and with similar amplitudes G6P (slightly higher), G3P, 3PG, and F6P (slightly lower). These small differences were within errors of measurement and are therefore not significant. In this experiment the measurements of F1,6BP are reliable.

A Paramedic Treatment for Modeling Explicitly Solvated Chemical Reaction Mechanisms

2018 ◽  
Author(s):  
Yasemin Basdogan ◽  
John Keith
Keyword(s):  
Reaction Mechanism ◽  
Chemical Reaction ◽  
Reaction Mechanisms ◽  
Reaction Pathway ◽  
Optimization Procedure ◽  
Cost Effective ◽  
Chemical Reaction Mechanisms ◽  
Solvent Molecules ◽  
Dynamics Simulations ◽  
Mbh Reaction

<div> <div> <div> <p>We report a static quantum chemistry modeling treatment to study how solvent molecules affect chemical reaction mechanisms without dynamics simulations. This modeling scheme uses a global optimization procedure to identify low energy intermediate states with different numbers of explicit solvent molecules and then the growing string method to locate sequential transition states along a reaction pathway. Testing this approach on the acid-catalyzed Morita-Baylis-Hillman (MBH) reaction in methanol, we found a reaction mechanism that is consistent with both recent experiments and computationally intensive dynamics simulations with explicit solvation. In doing so, we explain unphysical pitfalls that obfuscate computational modeling that uses microsolvated reaction intermediates. This new paramedic approach can promisingly capture essential physical chemistry of the complicated and multistep MBH reaction mechanism, and the energy profiles found with this model appear reasonably insensitive to the level of theory used for energy calculations. Thus, it should be a useful and computationally cost-effective approach for modeling solvent mediated reaction mechanisms when dynamics simulations are not possible. </p> </div> </div> </div>

scholarly journals Interpretation of the Chemical and Physical Time-Series Retrieved from Sentik Glacier, Ladakh Himalaya, India

1984 ◽  
Vol 30 (104) ◽  
pp. 66-76 ◽  
Author(s):  
Paul A. Mayewski ◽  
W. Berry Lyons ◽  
N. Ahmad ◽  
Gordon Smith ◽  
M. Pourchet
Keyword(s):  
Time Series ◽  
Chemical Species ◽  
Data Sets ◽  
Reactive Iron ◽  
Physical Time ◽  
Ladakh Himalaya ◽  
Data Density ◽  
Mass Circulation ◽  
The Himalaya ◽  
Analysis Of Time Series

AbstractSpectral analysis of time series of a c. 17 ± 0.3 year core, calibrated for total ß activity recovered from Sentik Glacier (4908m) Ladakh, Himalaya, yields several recognizable periodicities including subannual, annual, and multi-annual. The time-series, include both chemical data (chloride, sodium, reactive iron, reactive silicate, reactive phosphate, ammonium, δD, δ(18O) and pH) and physical data (density, debris and ice-band locations, and microparticles in size grades 0.50 to 12.70 μm). Source areas for chemical species investigated and general air-mass circulation defined from chemical and physical time-series are discussed to demonstrate the potential of such studies in the development of paleometeorological data sets from remote high-alpine glacierized sites such as the Himalaya.

Tandem synthesis of tetrahydroquinolines and identification of reaction network by operando NMR

2021 ◽  
Author(s):  
Jingwen Chen ◽  
Long Qi ◽  
Biying Zhang ◽  
Minda Chen ◽  
Takeshi Kobayashi ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Complex Network ◽  
Reaction Network ◽  
Tandem Reactions ◽  
Organic P ◽  
Design And Optimization ◽  
Metal Organic ◽  
Tandem Synthesis

The study of the reaction mechanism and complex network for heterogeneously catalyzed tandem reactions is challenging but can guide reaction design and optimization. Here, we describe using a bifunctional metal-organic...

scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

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