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For sample size, statistical methods were used (see figure legends)

In tier 2, a non-invasive screening strategy is applied to distinguish PDAC-associated diabetes from T2D by evaluating emerging blood biomarkers such as increased miRNAs, galectin-3, S100A9, adiponectin and IL-1Ra, glucagon/insulin ratio, vanin-1 and MPP9, cysteamine, lower GSH, lower PPAR-, and lower pancreatic polypeptide paired with an appropriate modeling strategy using the available clinical parameters for risk-assessment such as the Boursi multivariable model, ENDPAC, or machine-learning approaches such as XGBoost, to refine risk assessment (102108)

Engineered human cardiac models of FRDA have also been reported [11]