Protein Pattern Determination Using Multidimensional Mass Spectrometry Data
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Solution Overview
Problem
Current methods for determining protein and peptide patterns in liquid samples are not quick or reproducible, and existing technologies struggle to efficiently distinguish wanted signals from noise in mass spectrometry data.
Innovation Solution
The process involves continuous storage of mass components from proteins and peptides to create a multidimensional data field, using computational algorithms to calculate real masses and amplitudes, and employing calibration with reference values to enhance signal acquisition and resolution, while eliminating noise by distinguishing it from wanted signals based on non-repeating spectral patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous storage of individual mass spectra is performed to create a multidimensional data field, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent performs preliminary storage of all individual mass spectra in a multidimensional data field before final evaluation. This preliminary action allows comprehensive data collection without immediate processing complexity, as the data is organized in advance for subsequent algorithmic analysis.
Solution Approach 2:
The patent replaces manual or step-by-step data processing with computational algorithms that automatically evaluate the multidimensional data field. This substitution of mechanical processing with automated computational methods resolves the complexity issue while maintaining high measurement precision.
2Measurement precision
If elimination of interferences and noise is performed after storing spectra, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent extracts and eliminates interference components from the mass spectra after storage but before final evaluation. By separating the noise elimination step from the main evaluation流程 and performing it on the stored data, the system improves signal resolution without adding significant processing time to the critical path.
Solution Approach 2:
The spectra are stored in advance with all their information intact, allowing interference elimination to be performed as a preliminary cleaning step before the actual protein and peptide pattern determination. This preliminary action prevents noise from interfering with subsequent analysis without delaying the main measurement process.
3Reliability
If calibration with reference values is performed, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent uses reference values from previously determined protein and peptide patterns to automatically calibrate new measurements. The system serves itself by using its own historical data for calibration, eliminating the need for external calibration standards or complex manual calibration procedures, thus improving reliability without significantly increasing device complexity.
4Productivity
If only masses and amplitudes above preset thresholds are evaluated, then productivity is improved, but measurement precision may be compromised
Solution Approach 1:
The patent applies threshold filtering as a partial evaluation action, where only masses and amplitudes above preset thresholds are fully evaluated. This partial action approach significantly improves productivity by reducing the evaluation scope, while the threshold levels are set to preserve detection of biologically relevant low amplitude signals, minimizing precision compromise.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for precise and reproducible determination of protein and peptide patterns, enabling effective comparison with stored values and facilitating differential diagnosis by identifying typical protein patterns associated with specific diseases.
Implementation Method 1
determination by mass spectrometry
Implementation Method 2
directly ionized and transferred through an interface to an on-line coupled mass spectrometer
Implementation Method 3
Proteins and/or peptides of a liquid sample are separated by means of capillary electrophoresis
Data Source
AI summary
Provided are a process and a device for the qualitative and/or quantitative determination of a protein and/or peptide pattern of a liquid sample taken from a human or animal body for checking its state. The peptides and proteins of the liquid sample are processed and then subjected to analysis, wherein reference and sample values describing states of a human or animal body as well as deviations and correspondences derived therefrom are established, automatically stored in a data base, and when the protein and/or peptide pattern is again determined, a search for optimum correspondence is automatically performed. In this process, mass components or structural components of the proteins and/or peptides are established and stored. Subsequently, real masses or real structures are calculated from a common evaluation of the stored mass components or structural components, and an assignment to the proteins and/or peptides contained in the liquid sample is performed from a combination of the calculated real masses or real structures.