Flow Cytometry Scatter Waveform Air Bubble Detection
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Solution Overview
Problem
High-throughput flow cytometry systems face challenges in accurately identifying individual sample wells due to temporal gaps in particle detection, leading to identification errors, as existing methods are not sufficient to distinguish air bubbles from sample data.
Innovation Solution
The method involves using the scatter waveform output of a flow cytometer to detect air bubbles by generating and sampling a voltage output signal from a scatter detector, recording timestamps and voltage values greater than a separation gap threshold, and analyzing these signals to identify air bubbles and accurately delineate individual sample wells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If temporal gaps in particle detection are used to identify individual sample wells, then high-throughput flow cytometry data acquisition is enabled, but identification errors occur due to insufficient distinction between air bubbles and sample data
Solution Approach 1:
The patent applies the principle of detecting optical property changes by analyzing scatter waveform characteristics. Air bubbles and sample particles produce distinct scatter light patterns that are detected and differentiated by the flow cytometer, enabling accurate identification of sample wells while maintaining high-throughput operation
Solution Approach 2:
The system uses feedback from scatter waveform analysis to identify and distinguish air bubbles from sample particles. By continuously monitoring the optical detection signals and comparing them against expected patterns, the system can accurately delineate sample well boundaries and correct identification errors in real-time
2Use of energy by stationary object
If air bubbles are used to separate adjacent samples in the flow stream, then continuous delivery of multiple samples is achieved, but accurate detection and differentiation of air bubbles from samples becomes difficult
Solution Approach 1:
The patent utilizes differences in optical scattering properties between air bubbles and sample particles to enable their detection and differentiation. The scatter waveform analysis captures distinct optical signatures that allow the system to identify air bubbles as separation elements while maintaining continuous sample delivery
Solution Approach 2:
The scatter waveform signal serves as an intermediary that carries information about both samples and air bubbles. By analyzing the characteristics of this intermediate signal, the system can differentiate between the two components and maintain accurate sample identification throughout continuous flow operation
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 significantly reduces well identification errors by providing a consistent and accurate method to differentiate air bubbles from sample events, enhancing the precision of sample well identification in high-throughput flow cytometry systems.
Implementation Method 1
detect scattered light by the scatter detector as the fluid flow stream passes through the flow cytometer
Data Source
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AI summary
A method for detecting a separation gas in a fluid flow stream is provided herein. In one example, a voltage output signal is generated by a scatter detector of a flow cytometer as a flow stream of a plurality of gas-separated samples passes through the flow cytometer. The voltage output signal is sampled, and a timestamp and a voltage value are recorded for each sampled voltage of the voltage output signal that is greater than a separation gap threshold. In some examples the separation gap threshold is at least two times greater than a maximum voltage output of the samples. Flow cytometry systems including software configured to perform these method steps are also described.