Spectrometric Cell Substrate Classification Using Reference Sub-Libraries
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Solution Overview
Problem
Existing methods for spectrometric characterization of cell substrates, particularly microorganisms, lack specificity and reliability in taxonomic classification and property determination, especially under varying conditions or in the presence of inhomogeneities.
Innovation Solution
The method involves creating sub-libraries from a reference dataset library based on initial taxonomic classification, using first and second sub-libraries for comparing further spectrometric measurements to improve specificity and reliability, including the use of mass-spectrometric techniques like MALDI-TOF for bacterial classification and property determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a comprehensive library containing all reference datasets is used for taxonomic classification, then the coverage and potential identification capability is improved, but the complexity of data processing and the risk of false-positive results increases
Solution Approach 1:
The patent divides the comprehensive reference library into multiple sub-libraries based on initial classification results. Each sub-library contains reference datasets specific to certain taxonomic groups or spectral characteristics. This segmentation reduces the complexity of comparing measurement data against the entire library while maintaining comprehensive coverage through hierarchical classification stages.
Solution Approach 2:
The patent extracts and isolates specific reference datasets that are most relevant to the initial classification results into separate sub-libraries. By taking out only the necessary reference data for subsequent comparison, the system reduces processing complexity and minimizes false-positive results caused by irrelevant reference datasets in the comprehensive library.
2Adaptability or versatility
If a comprehensive library containing all reference datasets is used for taxonomic classification, then the coverage and potential identification capability is improved, but the reliability and specificity of classification results deteriorates due to false-positive results
Solution Approach 1:
The patent segments the reference library into specialized sub-libraries that contain only relevant reference datasets for specific taxonomic groups. This segmentation improves classification reliability by preventing false-positive matches against unrelated reference data, while still maintaining comprehensive coverage through the hierarchical structure of multiple sub-libraries.
Solution Approach 2:
The patent extracts and isolates only the most relevant reference datasets into sub-libraries based on initial classification results. By removing irrelevant reference data from the comparison process, the system eliminates sources of false-positive results while preserving the ability to identify diverse microorganisms through the staged classification approach.
3Measurement precision
If the entire library is used for each measurement comparison, then comprehensive classification is achieved, but the time required for property determination increases
Solution Approach 1:
The patent implements a hierarchical classification system where the reference library is segmented into sub-libraries. Initial measurements are compared against the full library for comprehensive classification, then subsequent measurements are compared only against relevant sub-libraries. This segmentation maintains classification completeness while dramatically reducing the time required for repeated property determinations.
Solution Approach 2:
The patent performs preliminary classification using the entire library to establish the taxonomic group, then uses this preliminary result to guide subsequent comparisons against specialized sub-libraries. This preliminary action ensures comprehensive initial classification while enabling faster subsequent measurements by limiting the comparison scope to relevant reference data.
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
Enhances the specificity of taxonomic classification and property determination of cell substrates by reducing false positives and enabling faster, reliable identification of properties such as susceptibility to antimicrobial agents, even in the presence of inhomogeneities or contamination.
Implementation Method 1
a mass spectrometer for provision or generation of spectrometric measurement data from the test cell substrate
Implementation Method 2
mass time-of-flight (TOF) analysis using ionization by matrix-assisted laser desorption/ionization (MALDI)
Implementation Method 3
ionization by matrix-assisted laser desorption/ionization (MALDI)
Data Source
AI summary
The invention relates to methods for spectrometric characterization of a test cell substrate. The characterization comprises taxonomic classification and determination of a property of interest of the test cell substrate. The characterization may be based on mass-spectrometric measurement data. The property of interest may be a resistance or susceptibility to a growth-influencing factor. After comparing first spectrometric measurement data of the test cell substrate with a provided reference library, a sub-library is created comprising those reference datasets from the reference library that are classified as allowing a taxonomic classification of the test cell substrate. Second spectrometric measurement data after a second preparation of the test cell substrate under conditions that serve to determine a property of interest of the test cell substrate is compared with the sub-library and allow a reliable determination of the property of interest.