Whole Wastewater Toxicity Prediction Using Zebrafish Behavior
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Solution Overview
Problem
Traditional methods for determining whole wastewater toxicity are time-consuming and require multiple concentration gradients and parallel experiments, using zebrafish embryos, which increases the number of embryos needed and limits the assessment to neurotoxicity, failing to provide a comprehensive toxicity index.
Innovation Solution
A method using zebrafish embryos to measure traditional and behavioral toxicity indexes, establishing prediction models with Lasso regression, and selecting appropriate models based on LC50 or LC10 values to determine whole wastewater toxicity quickly and accurately, reducing embryo usage and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional experimental methods with multiple concentration gradients and parallel experiments are used, then standardized toxicity indexes (LC10 or LC50) can be obtained, but the amount of embryos used increases and experimental operation time increases
Solution Approach 1:
The patent pre-establishes prediction models using behavioral toxicity indexes as inputs and traditional toxicity indexes (LC10, LC50) as outputs. These models are trained in advance on historical data, allowing rapid prediction of standardized toxicity indexes without performing time-consuming parallel experiments with multiple concentration gradients for each new wastewater sample.
Solution Approach 2:
The patent creates a virtual copy of the traditional toxicity testing process through machine learning prediction models. Instead of physically conducting multiple concentration gradient experiments, the system uses behavioral data to generate predicted toxicity values that replicate the outcomes of traditional methods, significantly reducing experimental time and embryo usage.
2Productivity
If water samples are filtered and concentrated to assess neurotoxicity, then the operation becomes simple and rapid, but the method can only obtain neurotoxicity index, not whole wastewater toxicity
Solution Approach 1:
The patent develops a multi-functional prediction system that can assess various types of toxicity (neurotoxicity, developmental toxicity, whole wastewater toxicity) using the same behavioral toxicity index measurements. The system selects different prediction models based on the desired output, allowing a single rapid measurement approach to serve multiple toxicity assessment purposes without requiring sample filtration or concentration.
Solution Approach 2:
The patent changes the output parameter of the toxicity assessment by using different prediction models to generate different toxicity indexes from the same behavioral input data. By adjusting which prediction model is applied, the system can output neurotoxicity indexes, developmental toxicity indexes, or whole wastewater toxicity indexes, expanding the assessment scope without modifying the sample preparation procedure.
3Measurement precision
If multiple concentration gradients and parallel experiments are conducted, then standardized toxicity indexes are obtained, but the number of embryos used increases
Solution Approach 1:
The patent replaces physical parallel experiments with virtual predictions generated by trained machine learning models. The models are trained once on historical experimental data, then used to predict toxicity indexes for new samples without requiring additional embryos, thereby dramatically reducing embryo consumption while maintaining standardized output indexes.
Solution Approach 2:
The patent performs preliminary training of prediction models using historical toxicity data and behavioral index data. This preliminary action creates a knowledge base that can be reused for multiple samples, eliminating the need to repeat embryo-based experiments for each new sample and thus reducing the total number of embryos required.
Data Source
AI summary
A method for determination of whole wastewater toxicity including: measuring the zebrafish embryo toxicity indexes of wastewater samples full-scale of a plurality of wastewater treatment plants and preprocessing obtained data, the zebrafish embryo toxicity indexes including traditional toxicity indexes and behavioral toxicity indexes; establishing whole wastewater toxicity prediction models for wastewater based on different target variables, with the traditional toxicity indexes as target variables and the behavioral toxicity indexes as features; and inputting behavioral toxicity index data of zebrafish embryos of a to-be-tested wastewater sample into the whole wastewater toxicity prediction models; selecting a corresponding prediction model based on a prediction result of the target variables, to obtain a whole wastewater toxicity of the to-be-tested wastewater sample.