Atomic Force Microscopy Local Deviational Volume Quantification
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Solution Overview
Problem
Current methods for imaging and quantifying biological surfaces using atomic force microscopy face challenges in identifying and classifying distinct structures, particularly on whole cells, due to the difficulty in reproducible quantification of morphological features, which often requires overlay with fluorescence markers, and are hindered by incompatible fixation protocols.
Innovation Solution
A method involving the determination and quantification of local deviational volume (LDV) on biological surfaces using atomic force microscopy, where a predefined mask in the xy-plane is used to evaluate nanoscale excursions in the z-direction, allowing for the normalization and quantification of topographical elements, and the use of neural networks for data analysis to generate parameter sets for image production and disease-related pattern recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional AFM measurements are used to investigate topography of biological objects, then high resolution imaging is achieved, but distinct structures are difficult to identify and reproducible quantification is hard to perform
Solution Approach 1:
The patent segments the continuous topographical data into discrete morphological features by defining specific geometric criteria for identification. Structures are divided into classified categories (protrusions, depressions, ridges, valleys) with quantifiable parameters, transforming continuous AFM height data into discrete, countable morphological units that can be systematically analyzed and compared.
Solution Approach 2:
The patent transitions from two-dimensional AFM height profiles to three-dimensional volumetric analysis by calculating the volume of morphological features. This dimensional transformation enables quantitative comparison of structural prominence and provides an additional parameter for distinguishing between different biological structures that may appear similar in 2D profiles.
2Loss of information
If fluorescence markers are used to identify structures, then structural identification is improved, but fixation protocols become incompatible and procedure-derived artefacts increase
Solution Approach 1:
The patent extracts and quantifies structural information directly from the topographical data obtained by AFM, eliminating the need for fluorescence markers. By focusing on geometric and volumetric properties of morphological features, the method separates structural identification from biochemical labeling, avoiding the harmful effects of incompatible fixation protocols and marker-induced artefacts.
Solution Approach 2:
The patent replaces the biochemical identification system (fluorescence markers and antibodies) with a mechanical/physical measurement system based on AFM topography analysis. Morphological features are identified and classified through their physical shape, volume, and spatial characteristics rather than through biochemical properties, substituting a mechanical measurement approach for a biochemical labeling approach.
3Ease of operation
If qualitative descriptive approach is used for morphological features, then investigation simplicity is maintained, but reproducible quantification is hard to perform
Solution Approach 1:
The patent transforms qualitative morphological descriptions into quantitative parameters by measuring specific geometric properties of identified features. Each morphological feature is characterized by numerical parameters such as height, width, volume, and position, which can be objectively measured and compared. This parameterization enables reproducible quantification while maintaining the simplicity of automated analysis through software-based measurement.
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 precise quantification and classification of topographical elements on biological surfaces, facilitating the detection of disease-related changes and cellular mechanical properties, applicable for diagnostic and therapeutic monitoring across various diseases, including tumour, cardiovascular, and inflammatory conditions, without the need for biochemical characterization.
Implementation Method 1
Atomic force microscopy (AFM) was invented two decades ago and became a versatile tool for biological studies on single biomolecules, aggregates, viruses, cells or tissues
Data Source
Figure 1A~1B
Figure 2
AI summary
The present invention relates to a method based on atomic force microscopy and the use thereof on biological surfaces. A method is provided to detect the Local Deviational Volume (LDV) of defined subcellular structures irrespective of a biochemical characterisation