AI digital-twin ecosystem translating gut-microbiome-neuroimmune signals into precision sleep-mood interventions

We present a novel AI-powered "gut-brain-sleep" digital-twin nursing ecosystem (G-B-S DT-N) that translates microbiome and neuroimmune signals into precision interventions for sleep and mood disorders. The ecosystem integrates four key layers: Microbiome Dynamics, Neuro-immune Interface, Sleep-Cognition-Emotion Circuits, and Person-Nurse-Environment Triad. These layers leverage multi-omics data, EEG sleep microstructure, real-time sensors, and EMR feeds to create a dynamic, patient-specific architecture. Uncertainty-aware explainable AI (XAI) modules ensure privacy and interpretability, enabling causal inference through advanced machine learning techniques. Adaptive care pathways, including precision pre-/post-biotic delivery and circadian light prescriptions, are optimized via nurse-in-the-loop reinforcement learning. The digital twin is operationalized through a five-step closed-loop workflow in hospital and community settings. Quantum-accelerated simulations and a proposed RCT (D-TWIN-RCT) will assess efficacy compared to standard care. Social, legal, and ethical frameworks protect data sovereignty and autonomy. This ecosystem offers a scalable solution for managing complex comorbidities, positioning nursing as a key driver of microbiome-precision medicine.