ZebraX: An Innovative Artificial Intelligence Approach to Analyzing Zebrafish Behavioral Biomarkers for Herbal Diabetes Treatment

Danio rerio, commonly known as zebrafish, have been used as model organisms for studying various diseases, including diabetes, because of its genetic similarity to humans, its fast reproductive capacity, and low-cost maintenance. However, current studies using zebrafish are mainly focused on non-metabolic diseases, and most importantly, these studies largely depend on manual data collection techniques that are prone to errors, time-consuming, and decrease the sample size of fish maintained. To aid the development and analysis of treatments for diabetes, this study presents a novel Artificial Intelligence (AI)-based approach- ZebraX-designed to bridge these gaps by analyzing diabetes-related behavioral biomarkers in zebrafish and evaluate the therapeutic potential of herbal remedies. This study successfully induced type 2 diabetes in zebrafish through dietary and environmental adjustments, from a baseline of 2.71 mmol/L to 12.73 mmol/L(p<0.001). The ZebraX system was used to detect the behavioral patterns of zebrafish by integrating automated tracking and predictive algorithms. Initial results indicated that zebrafish movement patterns, average speed, swimming episode duration, and episode frequency were all negatively affected by increasing the severity of diabetes. The maximum speed during swimming episodes of zebrafish with diabetes was reduced by 50% and irregular movements increased when compared to healthy control group fish. In addition, natural treatments consisting of mulberry leaves, aloe vera, and bitter melon extracts were evaluated for therapeutic effects. The most significant effect was in lowering blood sugar, which decreased blood sugar by about 52% to 6.08 mmol/L(p<0.001). This study's novel approach not only establishes zebrafish as an expandable model for diabetes-related research but also opens a tremendous possibility of integrating AI technologies with herbal remedies to improve the management of diabetes.