Tooth Fluorescence Profiling for Non-Invasive ASD Prediction
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Solution Overview
Problem
There is a need for accurate, non-invasive methods to diagnose biological conditions such as autism spectrum disorder (ASD) in young children, as existing diagnostic methods are inadequate for early detection and prediction.
Innovation Solution
A method involving immunohistochemistry staining of teeth using C-reactive protein stains, followed by fluorescence intensity analysis and machine learning models to predict diagnostic status based on fluorescence intensity patterns, utilizing techniques like Raman spectroscopy and LA-ICP-MS for enhanced diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing diagnostic methods are used for early detection of autism spectrum disorder, then diagnostic accuracy is insufficient, but non-invasive early detection capability is needed
Solution Approach 1:
The patent extracts and analyzes specific biomarkers (C-reactive protein, heat shock protein-70, and elemental signatures) from tooth samples to diagnose autism spectrum disorder. By focusing on these specific extracted markers rather than comprehensive analysis, the method achieves high diagnostic accuracy while maintaining practical feasibility
Solution Approach 2:
The patent uses tooth samples as an intermediary medium to indirectly assess neurological development and stress responses related to autism spectrum disorder. This intermediary approach enables non-invasive early detection without requiring direct neurological assessment, resolving the contradiction between accuracy and complexity
2Reliability
If invasive diagnostic procedures are used to improve diagnostic accuracy, then detection reliability improves, but patient comfort and ease of operation deteriorate
Solution Approach 1:
The patent utilizes tooth samples that can be easily obtained through routine dental procedures or even shed baby teeth, allowing the diagnostic system to serve itself without requiring specialized invasive procedures. The tooth naturally provides the biomarker reservoir, eliminating the need for painful or complex sample collection methods
3Measurement precision
If comprehensive biomarker analysis is performed to improve diagnostic precision, then measurement accuracy improves, but analysis time and loss of time increase
Solution Approach 1:
The patent segments the diagnostic analysis into distinct components: elemental composition analysis, protein expression analysis (C-reactive protein and heat shock protein-70), and fluorescence intensity measurement. This segmentation allows parallel processing of multiple biomarkers simultaneously, improving precision without proportionally increasing total analysis time
Solution Approach 2:
The patent employs fluorescence imaging to detect biomarker expression levels, where different fluorescence intensities and colors indicate varying concentrations of C-reactive protein and heat shock protein-70. This optical detection method provides rapid, high-precision quantification without requiring time-consuming sequential analysis
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
The method achieves sensitivity and specificity of at least 80% in predicting ASD diagnosis, providing a reliable and non-invasive tool for early detection in children under 12 years old.
Implementation Method 1
obtaining by imaging a fluorescence image of a stained tooth sample
Implementation Method 2
staining the tooth sample comprises using a C-reactive protein immunohistochemistry stain
Data Source
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AI summary
The present disclosure provides methods and systems for predicting a subject's diagnostic status with respect to a disease or disorder. The method may comprise staining a tooth, hair, or nail sample of the subject to produce a stained tooth sample, analyzing a fluorescence intensity spatially across the stained tooth, hair, or nail sample, and predicting a subject's diagnostic status with respect to a disease or disorder based at least in part on the analysis of the fluorescence intensity.