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Advancing Diabetes Reclassification Using the NexDi AI System With Multi-Omic Insights
Summary
The NexDi AI framework reconceptualizes diabetes as a fluid spectrum shaped by genetic, nutritional, and environmental pressures — including exposure to endocrine-disrupting agents and microplastics — which disturb metabolic and microbiome stability. This work highlights microplastics as a contributing environmental stressor in the growing global diabetes burden, supporting research into their systemic metabolic effects.
NexDi is introduced as an advanced framework that reconceptualizes diabetes as a fluid continuum of β-cell vulnerability shaped by genetic, nutritional, and environmental pressures. Type 1 diabetes is a state where autoimmune activity increasingly overlaps with insulin resistance pathways, whereas type 5 diabetes emerges from maternal anemia, hidden hunger, and early-life undernutrition. This spectrum reflects the dual burden observed in Egypt, where rising childhood diabetes coexists with persistent nutritional deficits. Environmental stressors, including exposure to endocrine-disrupting agents and microplastic, further disturb metabolic and polybiome stability. By integrating nutrigenomics, AI-enabled prediction, and polybiome analytics, NexDi provides a scalable and culturally grounded pathway toward predictive, preventive, and personalized diabetes care.