Gene Expression Analysis for Wound Classification
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Solution Overview
Problem
Current methods lack a specific laboratory test to distinguish between acute and chronic wounds, and there is no clear way to predict the healing process or a patient's response to treatment in wound care, leading to inefficient and costly healthcare interventions.
Innovation Solution
A method involving the examination of specific gene expression patterns in wound tissue using a subset of molecular markers to classify wounds as acute or chronic, allowing for informed treatment decisions and prediction of treatment outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current clinical/pathological factors are used to judge wound healing, then treatment decisions can be made, but there is no specific laboratory test to distinguish wound type and prediction accuracy is insufficient
Solution Approach 1:
The patent replaces clinical/pathological assessment with a molecular biological system (gene expression analysis) to achieve precise wound classification. By measuring the expression levels of specific genes (ARP2, CREB1L, VEGF-C, IL8RB, IL17BR, Claudin-5, CAR1, Endomuscin-2, TEM4, Psoriasin, IL22R, KAI1, PTPRK, TEM7R) in wound tissue, the system provides objective, quantifiable data to distinguish acute from chronic wounds, eliminating the need for subjective clinical judgment alone.
2Reliability
If comprehensive wound treatment is provided to all patients, then patient outcomes improve, but healthcare costs increase significantly
Solution Approach 1:
The patent applies preliminary action by conducting gene expression analysis before initiating treatment to classify wound type in advance. This allows healthcare providers to select appropriate treatments based on whether the wound is acute or chronic, avoiding unnecessary expensive interventions for acute wounds while ensuring adequate treatment for chronic wounds, thus optimizing resource allocation before treatment begins.
Solution Approach 2:
The patent changes the decision-making parameter from subjective clinical assessment to objective molecular markers (gene expression levels). By using specific gene expression patterns as the classification criterion, the system enables evidence-based treatment selection that matches the actual biological state of the wound, improving treatment effectiveness while reducing unnecessary healthcare spending.
3Measurement precision
If multiple gene markers are analyzed, then classification accuracy improves, but test complexity and cost increase
Solution Approach 1:
The patent applies segmentation by dividing the complex wound healing process into discrete, measurable molecular components. Instead of analyzing all possible genes, the system segments the analysis into a specific set of 14 genes known to be differentially expressed in acute versus chronic wounds. This segmented approach maintains high classification accuracy while making the test manageable and cost-effective.
Solution Approach 2:
The patent extracts only the essential molecular markers from the broader genomic landscape. By identifying and focusing on the specific set of genes (ARP2, CREB1L, VEGF-C, IL8RB, IL17BR, Claudin-5, CAR1, Endomuscin-2, TEM4, Psoriasin, IL22R, KAI1, PTPRK, TEM7R) that provide the most discriminatory power for wound classification, the system removes unnecessary complexity while preserving diagnostic accuracy.
Data Source
AI summary
The invention relates to a method and kit for identifying chronic or acute mammalian wound tissue or for determining the prognosis of mammalian wound tissue based upon the identification of at least one key set of molecular markers or genes whose expression pattern is indicative of a given wound type and so representative of a given prognosis.