Low-Noise Single-Beam Detection of Cellular Vibrational Spectra
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Solution Overview
Problem
Existing methods for measuring vibrational spectra of living cells and tissue are limited by labor-intensity, variability, and inability to accurately capture sub-cellular vibrational signals, particularly at low amplitudes and frequencies.
Innovation Solution
A system and method using a low-noise photon beam to modulate and detect vibrational signals from cells and tissues, employing fluorescent markers to isolate sub-cellular structures, and signal processing techniques to analyze and characterize these signals, including Fourier and wavelet transforms, to provide precise vibrational spectra analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional light microscopy and video recording are used to measure cell movement, then cell motility can be visualized, but the measurement is labor-intensive and has high variability
Solution Approach 1:
The patent replaces manual video analysis and labor-intensive microscopy with an automated acoustic measurement system. The system uses acoustic sensors to directly detect vibrational spectra from cell movements, converting mechanical cell motions into acoustic signals that can be analyzed automatically by a computer, eliminating the need for manual video frame-by-frame analysis and reducing human variability.
Solution Approach 2:
The patent introduces an acoustic field as an intermediary to measure cell movements. Instead of directly observing and manually analyzing cell movements through microscopy, the system uses sound waves to detect and transduce the mechanical vibrations produced by cell motility, providing an automated measurement pathway that reduces labor and variability.
2Measurement precision
If time lapse video photography with Fourier transforms is used to analyze cell vibrations, then vibrational spectra can be obtained, but the method cannot accurately capture low-amplitude signals
Solution Approach 1:
The patent replaces optical video recording with an acoustic detection system that uses microphones or acoustic sensors to directly capture vibrational spectra. This substitution allows for more sensitive detection of low-amplitude signals because acoustic sensors can detect subtle pressure variations corresponding to cell vibrations without the noise and resolution limitations of video-based methods.
Solution Approach 2:
The patent changes the measurement parameter from optical intensity variations in video frames to acoustic pressure variations. By measuring sound pressure levels instead of pixel intensity changes, the system achieves higher sensitivity for detecting low-amplitude cell vibrations, as acoustic measurements can resolve smaller signal variations more effectively than conventional video analysis.
3Loss of information
If flow cytometry with fluorescent markers is used to measure cell properties, then specific molecular markers can be detected, but the method cannot capture dynamic vibrational spectra over time
Solution Approach 1:
The patent implements continuous acoustic monitoring that records vibrational spectra over extended periods without interruption. The system continuously captures acoustic signals from living cells, allowing for long-duration measurements of dynamic vibrational changes while the cells remain alive and active, unlike flow cytometry which provides only snapshot measurements at specific time points.
Solution Approach 2:
The patent replaces the static molecular marker detection of flow cytometry with dynamic acoustic vibration measurement. Instead of detecting fixed molecular properties at discrete time points, the system continuously measures the vibrational spectra produced by living cells, capturing temporal dynamics and behavioral changes that occur over time while preserving cell viability.
4Measurement precision
If patch-clamping is used to measure voltage changes across cell walls, then electrical properties can be measured, but the method is invasive and cannot measure mechanical vibrations
Solution Approach 1:
The patent replaces invasive electrical measurement methods like patch-clamping with non-invasive acoustic detection. The system uses acoustic sensors to detect mechanical vibrations produced by cell movements without making physical contact with or penetrating the cell membrane, thereby eliminating the harmful effects of invasive procedures while still achieving precise measurement of cell dynamics.
Solution Approach 2:
The patent introduces an acoustic field as a non-invasive intermediary to measure cell vibrations. Instead of directly contacting and electrically stimulating the cell membrane as in patch-clamping, the system uses sound waves to detect and measure mechanical vibrations from cell movements, providing precise measurements without causing cellular damage or stress.
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
Enables the detection and characterization of vibrational spectra from living cells and tissues, including sub-cellular structures, with high sensitivity and accuracy, revealing cellular responses to stimuli and dynamic changes over time.
Implementation Method 1
a low-noise photon beam to modulate and detect vibrational signals from cells and tissues
Implementation Method 2
employing fluorescent markers to isolate sub-cellular structures
Implementation Method 3
signal processing techniques to analyze and characterize these signals, including Fourier and wavelet transforms
Data Source
AI summary
An optical device includes a low-noise illumination source, a support device, an ultra low-noise detector, an analog-to-digital converter, and a controller. The low-noise illumination source is configured to generate a single beam of radiation. The support device is configured to support an object and to pass the single beam of radiation through the object. The object directly blocks, absorbs, or deflects portions of the single beam of radiation, thereby directly modulating the single beam of radiation. The low-noise detector is configured to detect the modulated single beam of radiation and to output an analog signal representative of vibrational spectra of the object. The modulated single beam of radiation is non-interferometric. The analog-to-digital converter is configured to convert the detected analog signal into a digital signal. The controller is configured to analyze and generate vibrational spectra of the object from the digital signal represented as a range of events over time.