The idea for this contribution has its root in exact formulas connecting between measurable variable intensity of mass spectrometric peak of analyte ion and its stochastic dynamic diffusion parameter introduced, more recently in our works devoted to quantitative mass spectrometry. Herein, we present innovative functional relations connecting among not only DSD- and I-parameters, but also the experimental factor temperature and the concentration of analyte in solution. The temperature is one of the most important parameter determining the ionization efficiency of analytes under soft-ionization mass spectrometric conditions.
The focus of the work is not only on outlining quantitative conjunctions among experimental factors, respectively, parameters; measurable outcomes; and molecular properties, but also to help readers achieve in-depth understanding of governing factors determining the ionization efficiency of analyte ions with respect to temperature at a molecular level. Another important aspect for studying is that, all theoretical proposals introduced, so far, are based on stochastic dynamics. The latter field, however, is very broad. It encompasses a large set of mathematical methods applicable to explain diverse phenomena not only in the Chemistry, but also in the Physics, Astronomy, Economy, and many more research areas.
The methodology used to our principle theory behind the derivation of model functional relations; our innovative empirical modification of known relationship; and corresponding definition of the DSD parameter as a function of the measurable variable intensity are based on Box-Müller method, Einstein’s concept of diffusion within his molecular kinetic theory of heat; the forward Fokker-Planck equation (or the forward Kolmogorov equation,) where we empirically modify the characteristic function diffusion and its (their) application to Ornstein-Uhlenbeck process; approximations to a Wiener process; Gillespie’s interpretation of Ornstein-Uhlenbeck process and its exact numerical solution, respectively.
Due to, complexity of many of the soft-ionization mass spectrometric phenomena and the interconnection of different concepts behind our stochastic dynamic theory of exact quantification of the variable intensity, we hope that the readers will be able to gain the background to the different mass spectrometric phenomena and theories to more advanced primary literature sources, which can be found in the corresponding reference sections.
Table of Contents
Chapter 1. Temperature dependence on stochastic dynamic diffusion coefficients of heated electrospray ionization and atmospheric pressure chemical ionization mass spectrometric intensities of analyte ions of configurationally locked polyenes
1. Introduction
2. Experimental
2.1. Materials and methods
2.2. Chemometrics
2.3. Method performances
3. Results
3.1 Mass spectrometric data
3.1.1 Qualitative analysis
3.1.2 Determination of the stochastic dynamic diffusion parameters
3.1.3 Temperature dependence on stochastic dynamic diffusion parameters
3.1.4 Mutual correlation between stochastic dynamic diffusion parameters and total intensity of analyte ions
4. Discussion
5. Conclusion
Chapter 2. Quantification of the experimental mass spectrometric variable intensity with respect to the analyte concentration in solution — the stochastic dynamic approach
1. Introduction
2. Experimental
2.1. Materials and methods
2.2. Chemometrics
3. Results
3.1. Quantitative mass spectrometric analysis of steroids
3.1.1. Figure of merits
3.1.2. Mass spectrometric diffusion parameters according to the stochastic dynamic concept
3.2 Quantitative mass spectrometric analysis of drug
4. Discussion
5. Conclusion
Chapter 3. Mass spectrometric diffusion parameters and 3D structural analysis of oligomeric associates of glycylhomopeptides — a stochastic dynamics approach
1. Introduction
2. Results and discussion
2.1. Mass spectrometric analysis
2.1.1 Figures of merit
2.1.2 Determination of stochastic dynamic mass spectrometric diffusion parameters
2.2 Correlative analysis between stochastic dynamic diffusion parameters and kinetics
2.3 Temperature dependency of the stochastic dynamic diffusion parameters
2.4 Theoretical analysis
2.4.1 Assignment of experimental mass spectrometric peaks to molecular ions of organics
2.4.2 Metal-organics of AgI-ion
2.4.3 Thermodynamics of fragment reactions
2.5 Correlations between stochastic dynamic and quantum chemical diffusion parameters
3 Conclusion
Objective and Research Focus
This work aims to develop and validate a quantitative theoretical framework based on stochastic dynamics to correlate mass spectrometric intensity with experimental parameters such as temperature and analyte concentration in solution, thereby enabling precise 3D structural analysis of ions.
- Development of functional relations connecting mass spectrometric intensity with diffusion parameters and experimental factors.
- Empirical verification of the proposed stochastic dynamic models using HESI and APCI mass spectrometry.
- Chemometric analysis to enhance the accuracy and reliability of quantitative mass spectrometric protocols.
- Application of stochastic dynamic theories to study temperature dependence and concentration effects on ionization efficiency.
- Extension of the methodology to 3D structural analysis of complex peptide associates and metal-organic complexes.
Excerpt from the Book
1. INTRODUCTION
In outlining the major aims at this work we have mentioned that it attempts to employ our own functional relation accounting quantitatively for the experimental temporal behavior of the MS intensity (equation (1)) of peaks of analyte ions with respect to different spans of the scan time, which has been developed, more recently, as a powerful approach to study various classes of molecules in complex multicomponent mixtures. The method is applicable to a broad spectrum of soft ionization approaches, for instance, these are the ESI, APCI, MALDI and CID methods, respectively [1,3–6]. The contributions to the latter reference, encompassing a small-scale experiments to a relatively representative set of analyses of organic compounds of few classes of molecules, for instance, amino acids, oligopeptides, nucleic bases and nucleosides together with metal-organics of these compounds with transition metal AgI-, ZnII- and CuII-ions provide very encouraging experimental evidences on a universal applicability of equation (1) to different chemical compounds and ionization methods. In parallel, there is highlighted that the stochastic dynamic diffusion DSD parameter according to equation (1) is characterized by superior accuracy, precision, and, importantly, high selectivity toward analyte MS ions.
Summary of Chapters
Chapter 1. Temperature dependence on stochastic dynamic diffusion coefficients of heated electrospray ionization and atmospheric pressure chemical ionization mass spectrometric intensities of analyte ions of configurationally locked polyenes: This chapter establishes the functional relationship between the stochastic dynamic diffusion parameter, mass spectrometric intensity, and temperature, validated through experimental data of configurationally locked polyenes.
Chapter 2. Quantification of the experimental mass spectrometric variable intensity with respect to the analyte concentration in solution — the stochastic dynamic approach: This chapter extends the theoretical framework to account for analyte concentration in solution, providing a precise model to quantify mass spectrometric responses for steroids and drugs.
Chapter 3. Mass spectrometric diffusion parameters and 3D structural analysis of oligomeric associates of glycylhomopeptides — a stochastic dynamics approach: This chapter utilizes the stochastic dynamic approach to perform 3D structural analysis and kinetic evaluation of complex peptide associates and metal-organic complexes under various ionization conditions.
Keywords
Stochastic dynamics, mass spectrometry, diffusion, temperature, analyte concentration, chemometrics, ionization efficiency, 3D structural analysis, peptide associates, metal-organic complexes, Fokker-Planck equation, Ornstein-Uhlenbeck process, quantitative analytical chemistry, electrospray ionization, APCI.
Frequently Asked Questions
What is the primary objective of this research?
The work aims to create an exact, empirically testable quantitative framework based on stochastic dynamics to relate mass spectrometric ion intensity with experimental variables like temperature and concentration, thereby improving the reliability of quantitative mass spectrometry.
What are the core research themes?
The core themes include the stochastic dynamic treatment of ion diffusion, the influence of experimental conditions (temperature, concentration) on mass spectrometric responses, and the application of these models to 3D structural analysis.
What is the key research question?
The research asks how stochastic dynamic approaches can be effectively used to develop functional relations that accurately quantify mass spectrometric variables, transcending the limitations of traditional, less robust quantitative protocols.
Which scientific methodology is employed?
The methodology relies on stochastic dynamics, utilizing concepts like the Box-Müller method, the forward Fokker-Planck equation, and the Ornstein-Uhlenbeck process, complemented by rigorous chemometric testing (t-tests, F-tests, ANOVA).
What topics are discussed in the main body?
The main body covers the theoretical derivation of diffusion-based model equations, experimental proof-of-concept using various analytes (polyenes, steroids, peptides), and an in-depth discussion on the applicability of these models across different soft-ionization mass spectrometric methods.
Which keywords define this work?
Stochastic dynamics, mass spectrometry, diffusion, temperature, concentration in solution, chemometrics, ionization efficiency, and 3D structural analysis are the defining keywords.
How do the authors define the DSD parameter?
The DSD parameter is defined as a stochastic dynamic diffusion parameter that accounts for the temporal behavior of ion intensity, allowing for the quantitative description of molecular ions under various soft-ionization conditions.
How is the transition from solution to gas phase addressed?
The authors provide a nuanced discussion regarding the ESI process, arguing that the structure of the analyte in the continuum often reflects its solution-phase conformation and that stochastic models can successfully interpret the associated mass spectrometric phenomena.
- Citar trabajo
- Prof. Dr. Bojidarka Ivanova (Autor), Michael Spiteller (Autor), 2020, Quantitative Relations Among Temperature, Analyte Concentration in Solution, Stochastic Dynamic Diffusions and Mass Spectometric Variable Intensity, Múnich, GRIN Verlag, https://www.grin.com/document/520262
