Automated Biological Subpopulation Classification via Impedance

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Solution Overview

Problem

Current methods for identifying cellular subpopulations in heterogeneous cellular systems, such as those involving rare stem cells and cancer cells, face challenges due to the lack of reliable biochemical markers and the limitations of fluorescent staining, which can cause cell perturbations and affect viability, and existing impedance cytometry techniques often rely on single variables without a comprehensive view of data dispersion and relationships between biometrics.

Innovation Solution

The use of machine learning-based, automated classification techniques that employ multi-shell dielectric models to analyze electrical impedance data, allowing for the identification and quantification of subpopulation proportions and predicting alterations under drug treatments, by extracting and processing electrical impedance parameters across various frequencies to distinguish subpopulations based on biophysical differences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If fluorescent staining techniques are used to identify cellular subpopulations, then biochemical markers can be detected, but cell perturbations occur and cell viability is affected

Engineering Contradiction:

Improvedetection of biochemical markersVSAvoidcell perturbations and viability loss

Core Design Contradiction:

Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent replaces fluorescent staining (chemical/optical method) with impedance-based detection (electrical method). The system uses electrical impedance spectroscopy to measure cell biophysical properties such as membrane capacitance, cytoplasmic conductivity, and cell size, thereby identifying cellular subpopulations without chemical labels that perturb cells.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces electrical impedance as an intermediary measurement parameter that indirectly reflects cellular biochemical characteristics. By measuring electrical properties (capacitance, conductivity, impedance spectra) of the cell membrane and cytoplasm, the system infers subpopulation identities without direct chemical interaction with cellular markers.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If single variable impedance measurements are used, then measurement simplicity is maintained, but comprehensive view of data dispersion and relationships between biometrics is lost

Engineering Contradiction:

Improvemeasurement simplicityVSAvoiddata dispersion and biometric relationships

Core Design Contradiction:

Ease of operationVSLoss of information

Solution Approach 1:

The patent transitions from single-variable impedance measurement to multi-dimensional electrical impedance spectroscopy. The system measures impedance across multiple frequencies (e.g., 100 Hz to 10 MHz), extracting multiple parameters including phase angle, impedance magnitude, membrane capacitance, and cytoplasmic conductivity. This dimensional expansion provides comprehensive characterization of cellular subpopulations while maintaining automated analysis simplicity.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The patent segments the impedance measurement into distinct frequency ranges, each probing different cellular components. Low frequencies (100 Hz-10 kHz) measure extracellular resistance and cell size; mid frequencies (10 kHz-1 MHz) measure membrane capacitance and surface area; high frequencies (1 MHz-10 MHz) measure cytoplasmic conductivity and internal structure. This segmentation enables comprehensive biometric analysis through systematic frequency-domain decomposition.

Inventive Principle:

Principle #1Segmentation

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 enables the accurate classification of cellular subpopulations in real-time, providing a comprehensive view of phenotypic and electrophysiological characteristics, thereby supporting personalized medicine by assessing drug resistance and cell cycle synchronicity, and differentiating between subpopulations in complex biological samples.

Implementation Method 1

measuring an electrical impedance of the biological specimen using a specified range of frequencies

Methodology Applied

Scientific EffectElectrical Impedance: Electrical Resistance

Implementation Method 2

fitting the frequency-dependent impedance spectra to establish dielectric shell models representing each cell type

Methodology Applied

Scientific EffectDielectric properties: Dielectric Permittivity

Data Source

PatentUS20230417694A1Automated classification of biological subpopulations using impedance parameters

Publication Date: 2023.12.28 UNIV OF VIRGINIA PATENT FOUND

AI summary

A technique for automated classification of biological subpopulations can include or use training a classifier by receiving an analyte biological specimen defining biophysical features characterized by corresponding electrical impedance parameters, within a test cell through which the biological specimen is flowing, measuring an electrical impedance of the biological specimen using a specified range of frequencies, extracting at least two electrical impedance parameters from the measured electrical impedance, and using the at least two electrical impedance parameters as an input to a trained classifier, training the classifier using training data from a plurality of other biological specimens and corresponding electrical impedance parameters of such training data.